Econstudentlog

Quotes

  1. “Originally, I set out to understand why the state has always seemed to be the enemy of “people who move around,” to put it crudely. […] Nomads and pastoralists (such as Berbers and Bedouins), hunter-gatherers, Gypsies, vagrants, homeless people, itinerants, runaway slaves, and serfs have always been a thorn in the side of states. Efforts to permanently settle these mobile peoples (sedentarization) seemed to be a perennial state project—perennial, in part, because it so seldom succeeded. The more I examined these efforts at sedentarization, the more I came to see them as a state’s attempt to make a society legible, to arrange the population in ways that simplified the classic state functions of taxation, conscription, and prevention of rebellion. Having begun to think in these terms, I began to see legibility as a central problem in statecraft. […] much of early modern European statecraft seemed […] devoted to rationalizing and standardizing what was a social hieroglyph into a legible and administratively more convenient format. The social simplifications thus introduced not only permitted a more finely tuned system of taxation and conscription but also greatly enhanced state capacity. […] These state simplifications, the basic givens of modern statecraft, were, I began to realize, rather like abridged maps. They did not successfully represent the actual activity of the society they depicted, nor were they intended to; they represented only that slice of it that interested the official observer. They were, moreover, not just maps. Rather, they were maps that, when allied with state power, would enable much of the reality they depicted to be remade. Thus a state cadastral map created to designate taxable property-holders does not merely describe a system of land tenure; it creates such a system through its ability to give its categories the force of law.” (James C. Scott, Seeing Like a State, pp.1-2)
  2. “No cynicism or mendacity need be involved. It is perfectly natural for leaders and generals to exaggerate their influence on events; that is the way the world looks from where they sit, and it is rarely in the interest of their subordinates to contradict their picture.” (-ll-, p.160)
  3. “Old-growth forests, polycropping, and agriculture with open-pollinated landraces may not be as productive, in the short run, as single-species forests and fields or identical hybrids. But they are demonstrably more stable, more self-sufficient, and less vulnerable to epidemics and environmental stress, needing far less in the way of external infusions to keep them on track. Every time we replace “natural capital” (such as wild fish stocks or old-growth forests) with what might be called “cultivated natural capital” (such as fish farms or tree plantations), we gain in ease of appropriation and in immediate productivity, but at the cost of more maintenance expenses and less “redundancy, resiliency, and stability.”[14] If the environmental challenges faced by such systems are both modest and predictable, then a certain simplification might also be relatively stable.[15] Other things being equal, however, the less diverse the cultivated natural capital, the more vulnerable and nonsustainable it becomes. The problem is that in most economic systems, the external costs (in water or air pollution, for example, or the exhaustion of nonrenewable resources, including a reduction in biodiversity) accumulate long before the activity becomes unprofitable in a narrow profit-and-loss sense.
    A roughly similar case can be made, I think, for human institutions — a case that contrasts the fragility of rigid, single-purpose, centralized institutions to the adaptability of more flexible, multipurpose, decentralized social forms. As long as the task environment of an institution remains repetitive, stable, and predictable, a set of fixed routines may prove exceptionally efficient. In most economies and in human affairs generally, this is seldom the case, and such routines are likely to be counterproductive once the environment changes appreciably.” (-ll-, pp. 353-354)
  4. “If the facts — that is, the behavior of living human beings — are recalcitrant to […] an experiment, the experimenter becomes annoyed and tries to alter the facts to fit the theory, which, in practice, means a kind of vivisection of societies until they become what the theory originally declared that the experiment should have caused them to be. (Isaiah Berlin, “On Political Judgment”)
  5. “Before a disaster strikes, all your preparation looks like waste. After a disaster strikes, it looks like you didn’t do enough. Every time.” (‘Coagulopath’, here)
  6. “The effort an interested party makes to put its case before the decisionmaker will be in proportion to the advantage to be gained from a favorable outcome multiplied by the probability of influencing the decision.” (Edward Banfeld, quote from Albert Otto Hirschman’s Exit, Voice and Loyalty, Harvard University Press)
  7. The argument to be presented [in this book] starts with the firm producing saleable outputs for customers; but it will be found to be largely — and, at times, principally — applicable to organizations (such as voluntary associations, trade unions, or political parties) that provide services to their members without direct monetary counterpart. The performance of a firm or an organization is assumed to be subject to deterioration for unspecified, random causes which are neither so compelling nor so durable as to prevent a return to previous performance levels, provided managers direct their attention and energy to that task. The deterioration in performance is reflected most typically and generally, that is, for both firms and other organizations, in an absolute or comparative deterioration of the quality of the product or service provided.1 Management then finds out about its failings via two alternative routes: (1) Some customers stop buying the firm’s products or some members leave the organization: this is the exit option. As a result, revenues drop, membership declines, and management is impelled to search for ways and means to correct whatever faults have led to exit. (2) The firm’s customers or the organization’s members express their dissatisfaction directly to management or to some other authority to which management is subordinate or through general protest addressed to anyone who cares to listen: this is the voice option.” (ibid.)
  8. “Voice has the function of alerting a firm or organization to its failings, but it must then give management, old or new, some time to respond to the pressures that have been brought to bear on it. […] In the case of any one particular firm or organization and its deterioration, either exit or voice will ordinarily have the role of the dominant reaction mode. The subsidiary mode is then likely to show up in such limited volume that it will never become destructive for the simple reason that, if deterioration proceeds, the job of destruction is accomplished single-handedly by the dominant mode. In the case of normally competitive business firms, for example, exit is clearly the dominant reaction to deterioration and voice is a badly underdeveloped mechanism; it is difficult to conceive of a situation in which there would be too much of it.” (-ll-)
  9. “The reluctance to exit in spite of disagreement with the organization of which one is a member is the hallmark of loyalist behavior. When loyalty is present exit abruptly changes character: the applauded rational behavior of the alert consumer shifting to a better buy becomes disgraceful defection, desertion, and treason. Loyalist behavior […] can be understood in terms of a generalized concept of penalty for exit. The penalty may be directly imposed, but in most cases it is internalized. The individual feels that leaving a certain group carries a high price with it, even though no specific sanction is imposed by the group. In both cases, the decision to remain a member and not to exit in the face of a superior alternative would thus appear to follow from a perfectly rational balancing of prospective private benefits against private costs.” (-ll-)
  10. “The preference that [an] individual ends up conveying to others is what I will call his public preference. It is distinct from his private preference, which is what he would express in the absence of social pressures. By definition, preference falsification is the selection of a public preference that differs from one’s private preference. […] It is public opinion, rather than private opinion, that undergirds political power. Private opinion may be highly unfavorable to a regime, policy, or institution without generating a public outcry for change. The communist regimes of Eastern Europe survived for decades even though they were widely despised. They remained in power as long as public opinion remained overwhelmingly in their favor, collapsing instantly when street crowds mustered the courage to rise against them.” (Timur Kuran, Private Truths, Public Lies, Harvard University Press).
  11. “Even in democratic societies, where the right to think, speak, and act freely enjoys official protection, and where tolerance is a prized virtue, unorthodox views can evoke enormous hostility. In the United States, for instance, to defend the sterilization of poor women or the legalization of importing ivory would be to raise doubts about one’s civility and morality, if not one’s sanity. […] strictly enforced, freedom of speech does not insulate people’s reputations from their expressed opinions. Precisely because people who express different opinions do get treated differently, individuals normally tailor their expressions to the prevailing social pressures. Their adjustments vary greatly in social impact. At one extreme are harmless, and possibly beneficial, acts of politeness, as when one tells a friend wearing a garish shirt that he has good taste. At the other are acts of spinelessness on issues of general concern, as when a politician endorses a protectionist measure that he recognizes as harmful to most of his constituents. The pressures generating such acts of insincerity need not originate from the government. Preference falsification is compatible with all political systems, from the most unyielding dictatorship to the most libertarian democracy.” (-ll-)
  12. “How will the individual choose what preference to convey? Three distinct considerations may enter his calculations: the satisfaction he is likely to obtain from society’s decision, the rewards and punishments associated with his chosen preference, and finally, the benefits he derives from truthful self-expression. If large numbers of individuals are expressing preferences on the issue, the individual’s capacity to influence the collective decision is likely to be negligible. In this case he will consider society’s decision to be essentially fixed, basing his own preference declaration only on the second and third considerations. Ordinarily, these offer a tradeoff between the benefits of self-expression and those of being perceived as someone with the right preference. Where the latter benefits dominate, our individual will engage in preference falsification.” (-ll-)
  13. “Issues of political importance present individuals with tradeoffs between outer and inner peace. Frequently, therefore, these matters force people to choose between their reputations and their individualities. There are contexts, of course, in which such tradeoffs are dealt with by remaining silent […]. Silence has two possible advantages and two disadvantages. On the positive side, it spares one the penalty of taking a position offensive to others, and it may lessen the inner cost of preference falsification. On the negative side, one gives up available rewards, and one’s private preference remains hidden. On some controversial issues, the sum of these various payoffs may exceed the net payoff to expressing some preference. Certain contexts present yet another option: abandoning the decision-making group that is presenting one with difficult choices. This option, “exit,” is sometimes exercised by group members unhappy with the way things are going, yet powerless to effect change. […] For all practical purposes, exit is not always a viable option. Often our choices are limited to expressing some preference or remaining silent.” (-ll-)
  14. “In a polarized political environment, individuals may not be able to position themselves on neutral ground even if they try. Each side may perceive a declaration of neutrality or moderation as collaboration with the enemy, leaving moderates exposed to attacks from two directions at once.” (-ll-)
  15. “[C]ontinuities [in societal/organizational structures] arise from obstacles to implementing change. One impediment, explored in Albert Hirschman’s Exit, Voice, and Loyalty, consists of individual decisions to “exit”: menacing elements of the status quo survive as people capable of making a difference opt to abandon the relevant decision-making group.2 Another such mechanism lies at the heart of Mancur Olson’s book on patterns of economic growth, The Rise and Decline of Nations: unpopular choices persist because the many who support change are less well organized than the few who are opposed.3 Here I argue that preference falsification is a complementary, yet more elementary, reason for the persistence of unwanted social choices. Hirschman’s exit is a form of public identification with change, as is his “voice,” which he defines as vocal protest. Preference falsification is often cheaper than escape, and it avoids the risks inherent in public protest. Frequently, therefore, it is the initial response of people who become disenchanted with the status quo.” (-ll-)
  16. “Public opinion can be divided yet heavily favor the status quo, with the few public dissenters being treated as deviants, opportunists, or villains. If millions have misgivings about a policy but only hundreds will speak up, one can sensibly infer that discussion on the policy is not free.” (-ll-)
  17. “…heuristics are most likely to be used under one or more of the following conditions: we do not have time to think carefully about an issue; we are too overloaded with information to process it fully; the issues at stake are unimportant; we have little other information on which to base a decision; and a given heuristic comes quickly to mind.” (-ll-)
  18. “What most people outside of analytics often fail to appreciate is that to generate what is seen, there’s a complex machinery that is unseen. For every dashboard and insight that a data analyst generates and for each predictive model developed by a data scientist, there are data pipelines working behind the scenes. It’s not uncommon for a single dashboard, or even a single metric, to be derived from data originating in multiple source systems. In addition, data pipelines do more than just extract data from sources and load them into simple database tables or flat files for analysts to use. Raw data is refined along the way to clean, structure, normalize, combine, aggregate, and at times anonymize or otherwise secure it. […] In addition, pipelines are not just built — they are monitored, maintained, and extended. Data engineers are tasked with not just delivering data once, but building pipelines and supporting infrastructure that deliver and process it reliably, securely, and on time.” (Data Pipelines Pocket Reference, James Densmore, O’Reilly Media)
  19. “The S in IoT stands for security.” (‘Windowsteak’, here)
  20. “Do not seek for information of which you cannot make use.” (Anna C. Brackett)

June 26, 2021 Posted by | Anthropology, Books, culture, Data, Quotes/aphorisms | Leave a comment

Quotes

i. “The advantage of living is not measured by length, but by use; some men have lived long, and lived little; attend to it while you are in it. It lies in your will, not in the number of years, for you to have lived enough.” (Michel de Montaigne)

ii. “All of the days go toward death and the last one arrives there.” (-ll-)

iii. “Nothing is so firmly believed as that which we least know.” (-ll-) (Variant: “Men are most apt to believe what they least understand.”)

iv. “The plague of man is boasting of his knowledge.” (-ll-)

v. “Saying is one thing and doing is another.” (-ll-)

vi. “Let no man be ashamed to speak what he is not ashamed to think.” (-ll-)

vii. “Few men have been admired by their own households.” (-ll-)

viii. “There is no wish more natural than the wish to know.” (-ll-)

ix. “It is not without good reason said, that he who has not a good memory should never take upon him the trade of lying.” (-ll-)

x. “Religion abhors the competition for truth. Science can’t live without it.” (Scott Atran, In gods we trust)

xi. “Imagination and intelligence enter into our existence in the part of servants of the primary instincts.” (Albert Einstein, Out of My Later Years (1950)), as quoted in Scott Atran’s In Gods we trust)

xii. “…yes, we are smart, but not because we stand on the shoulders of giants or are giants ourselves. We stand on the shoulders of a very large pyramid of hobbits. The hobbits do get a bit taller as the pyramid ascends, but it’s still the number of hobbits, not the height of particular hobbits, that’s allowing us to see farther.” (Joseph Heinrich, The Secret of Our Success)

xiii. “Underlying these failures is the assumption that we, as humans, all perceive the world similarly, want the same things, pursue these things based on our beliefs (the “facts” about the world), and process new information and experience in the same way. We already know all these assumptions are wrong. […] Different societies possess quite different social norms, institutions, languages, and technologies, and consequently they possess different ways of reasoning, mental heuristics, motivations, and emotional reactions. […] Culture, social norms, and institutions all shape our brains, biology, and hormones, as well as our perceptions, motivations, and judgments. We can’t pick our underlying cultural perceptions and motivations any more than we can suddenly speak a new language.” (-ll-)

xiv. “One of the debates in this literature involves opposing “innate” and “learned” in explaining our abilities and behaviors. [However,] much behavior is both 100% innate and 100% learned. For example, humans have clearly evolved to walk on two legs, and it’s one of our species’ behavioral signatures. Yet we also clearly learn to walk. […] showing that something is learned only tells us about the developmental process but not about whether it was favored by natural selection acting on genes.” (-ll-)

xv. “People always talk about the body as a beautiful well-oiled machine. But sometimes the body communicates with itself by messages written with radioactive ink on asbestos-laced paper, in the hopes that it’s killing itself slightly more slowly than it’s killing anyone who tries to send it fake messages. Honestly it is a miracle anybody manages to stay alive at all.” (Scott Alexander)

xvi. “It is better to be hated for what you are than to be loved for what you are not.” (André Gide)

xvii. “No matter how full a reservoir of maxims one may possess, and no matter how good one’s sentiments may be, if one have not taken advantage of every concrete opportunity to act, one’s character may remain entirely unaffected for the better.” (William James, Principles of Psychology)

xviii. “It is the duty of every man to endeavour that something may be added by his industry to the hereditary aggregate of knowledge and happiness. To add much can indeed be the lot of few, but to add something, however little, every one may hope” (Samuel Johnson, The Major Works of Samuel Johnson)

xix. ” …we should always wish to preserve the dignity of virtue by adorning her with graces which wickedness cannot assume.” (-ll-)

xx. “Let pain deserved without complaint be borne.” (“Leniter ex merito quicquid patiare ferendum est”) (Ovid, as quoted in -ll-)

 

August 20, 2019 Posted by | Anthropology, Books, culture, Quotes/aphorisms | Leave a comment

Trust

“A commonplace argument in contemporary writing on trust is that we would all be better off if we were all more trusting, and therefore we should all trust more […] Current writings commonly focus on trust as somehow the relevant variable in explaining differences across cases of successful cooperation. Typically, however, the crucial variable is the trustworthiness of those who are to be trusted or relied upon. […] It is not trust per se, but trusting the right people that makes for successful relationships and happiness.”

“If we wish to understand the role of trust in society […], we must get beyond the flaccid – and often wrong – assumption that trust is simply good. This supposition must be heavily qualified, because trusting the malevolent or the radically incompetent can be foolish and often even grossly harmful. […] trust only make[s] sense in dealings with those who are or who could be induced to be trustworthy. To trust the untrustworthy can be disastrous.”

That it’s stupid to trust people who cannot be trusted should in my opinion be blatantly obvious, yet somehow to a lot of people it doesn’t seem to be at all obvious; in light of this problem (…I maintain that this is indeed a problem) the above observations are probably among the most important ones included in Hardin’s book. The book includes some strong criticism of much of the current/extant literature on trust. The two most common fields of study within this area of research are game-theoretic ‘trust games’, which according to the author are ill-named as they don’t really seem to be dealing much, if at all, with the topic of trust, and (poor) survey research which asks people questions which are hard to answer and tend to yield answers which are even harder to interpret. I have included below a few concluding remarks from the chapter on these topics:

“Both of the current empirical research programs on trust are largely misguided. The T-games [‘trust-games’], as played […] do not elicit or measure anything resembling ordinary trust relations; and their findings are basically irrelevant to the modeling and assessment of trust and trustworthiness. The only thing that relates the so-called trust game […] to trust is its name, which is wrong and misleading. Survey questions currently in wide use are radically unconstrained. They therefore force subjects to assume the relevant degrees of constraint, such as how costly the risk of failed cooperation would be. […] In sum, therefore, there is relatively little to learn about trust from these two massive research programs. Without returning their protocols to address standard conceptions of trust, they cannot contribute much to understanding trust as we generally know it, and they cannot play a very constructive role in explaining social behavior, institutions, or social and political change. These are distressing conclusions because both these enterprises have been enormous, and in many ways they have been carried out with admirable care.”

There is ‘relatively little to learn about trust from these two massive research programs’, but one to me potentially important observation, hidden away in the notes at the end of the book, is perhaps worth mentioning here: “There is a commonplace claim that trust will beget trustworthiness […] Schotter [as an aside this guy was incidentally the author of the Micro textbook we used in introductory Microeconomics] and Sopher (2006) do not find this to be true in game experiments that they run, while they do find that trustworthiness (cooperativeness in the play of games) does beget trust (or cooperation).”

There were a few parts of the coverage which confused me somewhat until it occurred to me that the author might not have read Boyd and Richerson, or other people who might have familiarized him with their line of thinking and research (once again, you should read Boyd and Richerson).

Moving on, a few remarks on social capital:

“Like other forms of capital and human capital, social capital is not completely fungible but may be specific to certain activities. A given form of social capital that is valuable in facilitating certain actions may be useless or even harmful for others. […] [A] mistake is the tendency to speak of social capital as though it were a particular kind of thing that has generalized value, as money very nearly does […] it[‘s value] must vary in the sense that what is functional in one context may not be in another.”

It is important to keep in mind that trust which leads to increased cooperation can end up leading to both good outcomes and bad:

“Widespread customs and even very local practices of personal networks can impose destructive norms on people, norms that have all of the structural qualities of interpersonal capital. […] in general, social capital has no normative valence […] It is generally about means for doing things, and the things can be hideously bad as well as good, although the literature on social capital focuses almost exclusively on the good things it can enable and it often lauds social capital as itself a wonderful thing to develop […] Community and social capital are not per se good. It is a grand normative fiction of our time to suppose that they are.”

The book has a chapter specifically about trust on the internet which related to the coverage included in Barak et al.‘s book, a publication which I have unfortunately neglected to blog (this book of course goes into a lot more detail). A key point in that chapter is that the internet is not really all that special in terms of these things, in the sense that to the extent that it facilitates coordination etc., it can be used to accomplish beneficial things as well as harmful things – i.e. it’s also neutrally valenced. Barak et al.‘s book has a lot more stuff about how this medium impacts communication and optimal communication strategies etc., which links in quite a bit with trust aspects, but I won’t go into this stuff here and I’m pretty sure I’ve covered related topics before here on the blog, e.g. back when I covered Hargie.

The chapter about terrorism and distrust had some interesting observations. A few quotes:

“We know from varied contexts that people can have a more positive view of individuals from a group than they have of the group.”

“Mere statistical doubt in the likely trustworthiness of the members of some identifiable group can be sufficient to induce distrust of all members of the group with whom one has no personal relationship on which to have established trust. […] This statistical doubt can trump relational considerations and can block the initial risk-taking that might allow for a test of another individual’s trustworthiness by stereotyping that individual as primarily a member of some group. If there are many people with whom one can have a particular beneficial interaction, narrowing the set by excluding certain stereotypes is efficient […] Unfortunately, however, excluding very systematically on the basis of ethnicity or race becomes pervasively destructive of community relations.”

One thing to keep in mind here is that people’s stereotypes are often quite accurate. When groups don’t trust each other it’s always a lot of fun to argue about who’s to blame for that state of affairs, but it’s important here to keep in mind that both groups will always have mental models of both the in-group and the out-group (see also the coverage below). Also it should be kept in mind that to the extent that people’s stereotypes are accurate, blaming stereotyping behaviours for the problems of the people who get stereotyped is conceptually equivalent to blaming people for discriminating against untrustworthy people by not trusting people who are not trustworthy. You always come back to the problem that what’s at the heart of the matter is never just trust, but rather trustworthiness. To the extent that the two are related, trust follows trustworthiness, not the other way around.

“There’s a fairly extensive literature on so-called generalized trust, which is trust in the anonymous or general other person, including strangers, whom we might encounter, perhaps with some restrictions on what isues would come under that trust. […] [Generalized trust] is an implausible notion. In any real-world context, I trust some more than others and I trust any given person more about some things than about others and more in some contexts than in others. […] Whereas generalized trust or group-generalized trust makes little or no sense (other than as a claim of optimism), group-generalized distrust in many contexts makes very good sense. If you were Jewish, Gypsy, or gay, you had good reason to distrust all officers of the Nazi state and probably most citizens in Nazi Germany as well. American Indians of the western plains had very good reason to distrust whites. During Milosevic’s wars and pogroms, Serbs, Croatians, and Muslims in then Yugoslavia had increasingly good reasons to distrust most members of the other groups, especially while the latter were acting as groups. […] In all of these cases, distrust is defined by the belief that members of the other groups and their representatives are hostile to one’s interests. Trust relationships between members of these various groups are the unusual cases that require explanation; the relatively group-generalized distrust is easy to understand and justify.”

“In the current circumstances of mostly Arab and Islamic terrorism against israel and the West and much of the rest of the world, it is surely a very tiny fraction of all Arabs and Islamists who are genuinely a threat, but the scale of their threat may make many Israelis and westerners wary of virtually all Arabs and Islamists […] many who are not prospects for taking terrorist action evidently sympathize with and even support these actions”

“When cooperation is organized by communal norms, it can become highly exclusionary, so that only members of the community can have cooperative relations with those in the community. In such a case, the norms of cooperativeness are norms of exclusion […] For many fundamentalist groups, continued loyalty to the group and its beliefs is secured by isolating the group and its members from many other influences so that relations within the community are governed by extensive norms of exclusion. When this happens, it is not only trust relations but also basic beliefs that are constrained. If we encounter no one with contrary beliefs our own beliefs will tend to prevail by inertia and lack of questioning and they will be reinforced by our secluded, exclusionary community. There are many strong, extreme beliefs about religious issues as well as about many other things. […] The two matters for which such staunch loyalty to unquestioned beliefs are politically most important are probably religious and nationalist commitments […] Such beliefs are often maintained by blocking our alternative views and by sanctioning those within the group who stray. […] Narrowing one’s associations to others in an isolated extremist group cripples one’s epistemology by blocking out general questioning of the group’s beliefs […] To an outsider those beliefs might be utterly crazy. Indeed, virtually all strong religious beliefs sound crazy or silly to those who do not share them. […] In some ways, the internet allows individuals and small groups to be quite isolated while nevertheless maintaining substantial contact with others of like mind. Islamic terrorists in the West can be almost completely isolated individually while maintaining nearly instant, frequent contact with other and with groups in the Middle East, Pakistan, or Afghanistan, as well as with groups of other potential terrorists in target nations.”

December 7, 2015 Posted by | Anthropology, Books, culture, disagreement, Economics, Game theory, Psychology, Religion | Leave a comment

The Origin and Evolution of Cultures (V)

This will be my last post about the book. Go here for a background post and my overall impression of the book – I’ll limit this post to coverage of the ‘Simple Models of Complex Phenomena’-chapter which I mentioned in that post, as well as a few observations from the introduction to part 5 of the book, which talks a little bit about what the chapter is about in general terms. The stuff they write in the chapter is in a way a sort of overview over the kind of approach to things which you may well end up adopting unconsciously if you’re working in a field like economics or ecology and a defence of such an approach; I’ve as mentioned in the previous post about the book talked about these sorts of things before, but there’s some new stuff in here as well. The chapter is written in the context of Boyd and Richerson’s coverage of their ‘Darwinian approach to evolution’, but many of the observations here are of a much more general nature and relate to the application of statistical and mathematical modelling in a much broader context; and some of those observations that do not directly relate to broader contexts still do as far as I can see have what might be termed ‘generalized analogues’. The chapter coverage was actually interesting enough for me to seriously consider reading a book or two on these topics (books such as this one), despite the amount of work I know may well be required to deal with a book like this.

I exclude a lot of stuff from the chapter in this post, and there are a lot of other good chapters in the book. Again, you should read this book.

Here’s the stuff from the introduction:

“Chapter 19 is directed at those in the social sciences unfamiliar with a style of deploying mathematical models that is second nature to economists, evolutionary biologists, engineers, and others. Much science in many disciplines consists of a toolkit of very simple mathematical models. To many not familiar with the subtle art of the simple model, such formal exercises have two seemingly deadly flaws. First, they are not easy to follow. […] Second, motivation to follow the math is often wanting because the model is so cartoonishly simple relative to the real world being analyzed. Critics often level the charge ‘‘reductionism’’ with what they take to be devastating effect. The modeler’s reply is that these two criticisms actually point in opposite directions and sum to nothing. True, the model is quite simple relative to reality, but even so, the analysis is difficult. The real lesson is that complex phenomena like culture require a humble approach. We have to bite off tiny bits of reality to analyze and build up a more global knowledge step by patient step. […] Simple models, simple experiments, and simple observational programs are the best the human mind can do in the face of the awesome complexity of nature. The alternatives to simple models are either complex models or verbal descriptions and analysis. Complex models are sometimes useful for their predictive power, but they have the vice of being difficult or impossible to understand. The heuristic value of simple models in schooling our intuition about natural processes is exceedingly important, even when their predictive power is limited. […] Unaided verbal reasoning can be unreliable […] The lesson, we think, is that all serious students of human behavior need to know enough math to at least appreciate the contributions simple mathematical models make to the understanding of complex phenomena. The idea that social scientists need less math than biologists or other natural scientists is completely mistaken.”

And below I’ve posted the chapter coverage:

“A great deal of the progress in evolutionary biology has resulted from the deployment of relatively simple theoretical models. Staddon’s, Smith’s, and Maynard Smith’s contributions illustrate this point. Despite their success, simple models have been subjected to a steady stream of criticism. The complexity of real social and biological phenomena is compared to the toylike quality of the simple models used to analyze them and their users charged with unwarranted reductionism or plain simplemindedness.
This critique is intuitively appealing—complex phenomena would seem to require complex theories to understand them—but misleading. In this chapter we argue that the study of complex, diverse phenomena like organic evolution requires complex, multilevel theories but that such theories are best built from toolkits made up of a diverse collection of simple models. Because individual models in the toolkit are designed to provide insight into only selected aspects of the more complex whole, they are necessarily incomplete. Nevertheless, students of complex phenomena aim for a reasonably complete theory by studying many related simple models. The neo-Darwinian theory of evolution provides a good example: fitness-optimizing models, one and multiple locus genetic models, and quantitative genetic models all emphasize certain details of the evolutionary process at the expense of others. While any given model is simple, the theory as a whole is much more comprehensive than any one of them.”

“In the last few years, a number of scholars have attempted to understand the processes of cultural evolution in Darwinian terms […] The idea that unifies all this work is that social learning or cultural transmission can be modeled as a system of inheritance; to understand the macroscopic patterns of cultural change we must understand the microscopic processes that increase the frequency of some culturally transmitted variants and reduce the frequency of others. Put another way, to understand cultural evolution we must account for all of the processes by which cultural variation is transmitted and modified. This is the essence of the Darwinian approach to evolution.”

“In the face of the complexity of evolutionary processes, the appropriate strategy may seem obvious: to be useful, models must be realistic; they should incorporate all factors that scientists studying the phenomena know to be important. This reasoning is certainly plausible, and many scientists, particularly in economics […] and ecology […], have constructed such models, despite their complexity. On this view, simple models are primitive, things to be replaced as our sophistication about evolution grows. Nevertheless, theorists in such disciplines as evolutionary biology and economics stubbornly continue to use simple models even though improvements in empirical knowledge, analytical mathematics, and computing now enable them to create extremely elaborate models if they care to do so. Theorists of this persuasion eschew more detailed models because (1) they are hard to understand, (2) they are difficult to analyze, and (3) they are often no more useful for prediction than simple models. […] Detailed models usually require very large amounts of data to determine the various parameter values in the model. Such data are rarely available. Moreover, small inaccuracies or errors in the formulation of the model can produce quite erroneous predictions. The temptation is to ‘‘tune’’ the model, making small changes, perhaps well within the error of available data, so that the model produces reasonable answers. When this is done, any predictive power that the model might have is due more to statistical fitting than to the fact that it accurately represents actual causal processes. It is easy to make large sacrifices of understanding for small gains in predictive power.”

“In the face of these difficulties, the most useful strategy will usually be to build a variety of simple models that can be completely understood but that still capture the important properties of the processes of interest. Liebenstein (1976: ch. 2) calls such simple models ‘‘sample theories.’’ Students of complex and diverse subject matters develop a large body of models from which ‘‘samples’’ can be drawn for the purpose at hand. Useful sample theories result from attempts to satisfy two competing desiderata: they should be simple enough to be clearly and completely grasped, and at the same time they should reflect how real processes actually do work, at least to some approximation. A systematically constructed population of sample theories and combinations of them constitutes the theory of how the whole complex process works. […] If they are well designed, they are like good caricatures, capturing a few essential features of the problem in a recognizable but stylized manner and with no attempt to represent features not of immediate interest. […] The user attempts to discover ‘‘robust’’ results, conclusions that are at least qualitatively correct, at least for some range of situations, despite the complexity and diversity of the phenomena they attempt to describe. […] Note that simple models can often be tested for their scientific content via their predictions even when the situation is too complicated to make practical predictions. Experimental or statistical controls often make it possible to expose the variation due to the processes modeled, against the background of ‘‘noise’’ due to other ones, thus allowing a ceteris paribus prediction for purposes of empirical testing.”

“Generalized sample theories are an important subset of the simple sample theories used to understand complex, diverse problems. They are designed to capture the qualitative properties of the whole class of processes that they are used to represent, while more specialized ones are used for closer approximations to narrower classes of cases. […] One might agree with the case for a diverse toolkit of simple models but still doubt the utility of generalized sample theories. Fitness-maximizing calculations are often used as a simple caricature of how selection ought to work most of the time in most organisms to produce adaptations. Does such a generalized sample theory have any serious scientific purpose? Some might argue that their qualitative kind of understanding is, at best, useful for giving nonspecialists a simplified overview of complicated topics and that real scientific progress still occurs entirely in the construction of specialized sample theories that actually predict. A sterner critic might characterize the attempt to construct generalized models as loose speculation that actually inhibits the real work of discovering predictable relationships in particular systems. These kinds of objections implicitly assume that it is possible to do science without any kind of general model. All scientists have mental models of the world. The part of the model that deals with their disciplinary specialty is more detailed than the parts that represent related areas of science. Many aspects of a scientist’s mental model are likely to be vague and never expressed. The real choice is between an intuitive, perhaps covert, general theory and an explicit, often mathematical, one. […] To insist upon empirical science in the style of physics is to insist upon the impossible. However, to give up on empirical tests and prediction would be to abandon science and retreat to speculative philosophy. Generalized sample theories normally make only limited qualitative predictions. The logistic model of population growth is a good elementary example. At best, it is an accurate model only of microbial growth in the laboratory. However, it captures something of the biology of population growth in more complex cases. Moreover, its simplicity makes it a handy general model to incorporate into models that must also represent other processes such as selection, and intra- and interspecific competition. If some sample theory is consistently at variance with the data, then it must be modified. The accumulation of these kinds of modifications can eventually alter general theory […] A generalized model is useful so long as its predictions are qualitatively correct, roughly conforming to the majority of cases. It is helpful if the inevitable limits of the model are understood. It is not necessarily an embarrassment if more than one alternative formulation of a general theory, built from different sample models, is more or less equally correct. In this case, the comparison of theories that are empirically equivalent makes clearer what is at stake in scientific controversies and may suggest empirical and theoretical steps toward a resolution.”

“The thorough study of simple models includes pressing them to their extreme limits. This is especially useful at the second step of development, where simple models of basic processes are combined into a candidate generalized model of an interesting question. There are two related purposes in this exercise. First, it is helpful to have all the implications of a given simple model exposed for comparative purposes, if nothing else. A well-understood simple sample theory serves as a useful point of comparison for the results of more complex alternatives, even when some conclusions are utterly ridiculous. Second, models do not usually just fail; they fail for particular reasons that are often very informative. Just what kinds of modifications are required to make the initially ridiculous results more nearly reasonable? […]  The exhaustive analysis of many sample models in various combinations is also the main means of seeking robust results (Wimsatt, 1981). One way to gain confidence in simple models is to build several models embodying different characterizations of the problem of interest and different simplifying assumptions. If the results of a model are robust, the same qualitative results ought to obtain for a whole family of related models in which the supposedly extraneous details differ. […] Similarly, as more complex considerations are introduced into the family of models, simple model results can be considered robust only if it seems that the qualitative conclusion holds for some reasonable range of plausible conditions.”

“A plausibility argument is a hypothetical explanation having three features in common with a traditional hypothesis: (1) a claim of deductive soundness, of in-principle logical sufficiency to explain a body of data; (2) sufficient support from the existing body of empirical data to suggest that it might actually be able to explain a body of data as well as or better than competing plausibility arguments; and (3) a program of research that might distinguish between the claims of competing plausibility arguments. The differences are that competing plausibility arguments (1) are seldom mutually exclusive, (2) can seldom be rejected by a single sharp experimental test (or small set of them), and (3) often end up being revised, limited in their generality or domain of applicability, or combined with competing arguments rather than being rejected. In other words, competing plausibility arguments are based on the claims that a different set of submodels is needed to achieve a given degree of realism and generality, that different parameter values of common submodels are required, or that a given model is correct as far as it goes, but applies with less generality, realism, or predictive power than its proponents claim. […] Human sociobiology provides a good example of a plausibility argument. The basic premise of human sociobiology is that fitness-optimizing models drawn from evolutionary biology can be used to understand human behavior. […] We think that the clearest way to address the controversial questions raised by competing plausibility arguments is to try to formulate models with parameters such that for some values of the critical parameters the results approximate one of the polar positions in such debates, while for others the model approximates the other position.”

“A well-developed plausibility argument differs sharply from another common type of argument that we call a programmatic claim. Most generally, a programmatic claim advocates a plan of research for addressing some outstanding problem without, however, attempting to construct a full plausibility argument. […] An attack on an existing, often widely accepted, plausibility argument on the grounds that the plausibility argument is incomplete is a kind of programmatic claim. Critiques of human sociobiology are commonly of this type. […] The criticism of human sociobiology has far too frequently depended on mere programmatic claims (often invalid ones at that, as when sociobiologists are said to ignore the importance of culture and to depend on genetic variation to explain human differences). These claims are generally accompanied by dubious burden-of-proof arguments. […] We have argued that theory about complex-diverse phenomena is necessarily made up of simple models that omit many details of the phenomena under study. It is very easy to criticize theory of this kind on the grounds that it is incomplete (or defend it on the grounds that it one day will be much more complete). Such criticism and defense is not really very useful because all such models are incomplete in many ways and may be flawed because of it. What is required is a plausibility argument that shows that some factor that is omitted could be sufficiently important to require inclusion in the theory of the phenomenon under consideration, or a plausible case that it really can be neglected for most purposes. […] It seems to us that until very recently, ‘‘nature-nurture’’ debates have been badly confused because plausibility arguments have often been taken to have been successfully countered by programmatic claims. It has proved relatively easy to construct reasonable and increasingly sophisticated Darwinian plausibility arguments about human behavior from the prevailing general theory. It is also relatively easy to spot the programmatic flaws in such arguments […] The problem is that programmatic objections have not been taken to imply a promise to deliver a full plausibility claim. Rather, they have been taken as a kind of declaration of independence of the social sciences from biology. Having shown that the biological theory is in principle incomplete, the conclusion is drawn that it can safely be ignored.”

“Scientists should be encouraged to take a sophisticated attitude toward empirical testing of plausibility arguments […] Folk Popperism among scientists has had the very desirable result of reducing the amount of theory-free descriptive empiricism in many complex-diverse disciplines, but it has had the undesirable effect of encouraging a search for simple mutually exclusive hypotheses that can be accepted or rejected by single experiments. By our argument, very few important problems in evolutionary biology or the social sciences can be resolved in this way. Rather, individual empirical investigations should be viewed as weighing marginally for or against plausibility arguments. Often, empirical studies may themselves discover or suggest new plausibility arguments or reconcile old ones.”

“We suspect that most evolutionary biologists and philosophers of biology on both sides of the dispute would pretty much agree with the defense of the simple models strategy presented here. To reject the strategy of building evolutionary theory from collections of simple models is to embrace a kind of scientific nihilism in which there is no hope of achieving an understanding of how evolution works. On the other hand, there is reason to treat any given model skeptically. […] It may be possible to defend the proposition that the complexity and diversity of evolutionary phenomena make any scientific understanding of evolutionary processes impossible. Or, even if we can obtain a satisfactory understanding of particular cases of evolution, any attempt at a general, unified theory may be impossible. Some critics of adaptationism seem to invoke these arguments against adaptationism without fully embracing them. The problem is that alternatives to adaptationism must face the same problem of diversity and complexity that Darwinians use the simple model strategy to finesse. The critics, when they come to construct plausibility arguments, will also have to use relatively simple models that are vulnerable to the same attack. If there is a vulgar sociobiology, there is also a vulgar criticism of sociobiology.”

June 6, 2014 Posted by | Anthropology, Biology, Books, culture, Ecology, Economics, Evolutionary biology, Mathematics, Science | Leave a comment

The Origin and Evolution of Cultures (IV)

The first half of the book was not easy to read due to the technical nature of the coverage, and so I decided to put it away for a while. However I did pick it up again, and I’m really glad I did as there’s simply no way around the fact that this book is awesome. Some of the chapters in this book are chapters you need to read.

Highly recommended. Probably the best book I’ve read this year.”

I’ve finished the book – the above is my review of it on goodreads. I gave the book five stars.

The last part of it had (at least) two of those must-read chapters which I when I read them feel like I really ought to blog, and they both had a lot of stuff. The first of these chapters was an awesome chapter on agriculture. I wrote some stuff of my own about that stuff in my last post about the book (I’ve incidentally corrected a few minor inaccuracies in that post since it was posted – I thought I should mention this here), but I’m pretty sure I wouldn’t have done this if I’d known what was in that chapter; they cover this topic in a lot of detail and they do it really well. Many of the aspects they cover incidentally do not overlap with what I wrote though some of course do; you’ll surely get a lot out of reading this post despite having read my earlier comments on the topic (at least if you’re interested in these sorts of things). In my archaeology textbook, which is only a few years old, the idea that the dramatic climate change which took place around the Pleistocene/Holocene boundary was a crucial factor in the development of agriculture is taken for granted, but Boyd and Richerson’s coverage reminds us that archaeologists were not always so eager to accept this hypothesis (and it should be noted that other, weaker, hypotheses are mentioned/covered in the archaeology text as well – I was skeptical about some of these while reading the book (I wrote a couple of pretty harsh remarks in the margin) because they seemed implausible to me; Boyd and Richerson illustrates in the chapter e.g. through application of models of population dynamics that I had reason to be skeptical). I forgot to talk about climate in my last post on the topic probably because I assumed people knew this part, but it gets its fair share of the attention in this post anyway so I guess no harm is done.

The other chapter I consider to be best categorized as a ‘must-read’ chapter is chapter 19, on ‘Simple Models of Complex Phenomena’, which relates a little bit – but only a little – to a blog post of mine which has recently got some attention. When reading that chapter I was never in any doubt I’d cover that stuff here – this stuff is pure gold. The ‘Microevolutionary processes give rise to history’-chapter was also really interesting and the last chapter on memes there are probably more than a few people who’d benefit from reading, but I’ll not cover that stuff here; I don’t think I’d have problems writing 4 or 5 posts about the remaining parts of the book, and this is simply too much. I’ll talk about agriculture in this post and then I’ll probably cover the model chapter in a later post. It’s possible that the agriculture coverage in the book is less interesting to people with very limited knowledge of archaeology and human prehistory than it is to me (not that I’d say I know much about this stuff – actually on second thought I probably belong in the group of people with ‘very limited knowledge’ as well…), because a lot of things which relate closely to what they write about are perhaps hard to conceptualize without knowing anything about these things, but anyway I write about what I find interesting, so here we are.

Let’s move on to the book chapter coverage:

“Numerous subsequent investigations [after the Braidwood team] now provide a reasonably detailed picture of the origins of agriculture in several independent centers and its subsequent diffusion to almost all of the earth suitable for cultivation. These investigations have discovered no region in which agriculture developed earlier or faster than in the Near East, though a North Chinese center of domestication of millet may prove almost as early. Other centers seem to have developed later, or more slowly, or with a different sequence of stages, or all three. The spread of agriculture from centers of origin to more remote areas is well documented for Europe and North America [a major problem in relation to East Asia/China is incidentally the lack of ‘transitional sites’ dated around 8.000 to 6.000 years BC; we have very early sites and then we have “abundant and widespread evidence for sedentary Neolithic villages” by 6000 BC (Scarre et al.) – but we miss some evidence as to what happened in between – US]. Ethnography also gives us cases where hunters and gatherers persisted to recent times in areas seemingly highly suitable for agriculture, most notably much of western North America and Australia. Attempts to account for this rather complex pattern are a major focus of archaeology.”

“The processes involved in such a complex phenomenon as the origin of agriculture are many and densely entangled. Many authors have given climate change a key explanatory role […] The coevolution of human subsistence strategies and plant and animal domesticates must also play an important role […] Hunting-and-gathering subsistence may normally be a superior strategy to incipient agriculture […], and, if so, some local factor may be necessary to provide the initial impetus to heavier use of relatively low-quality, high-processing-effort plant resources that eventually result in plant domestication. Population pressure is perhaps the most popular candidate […] Quite plausibly, the complex details of local history entirely determine the evolutionary sequence leading to the origin and spread of agriculture in every region. Indeed, important advances in our understanding of the origins of agriculture have resulted from pursuit of the historical details of particular cases […] Nonetheless, we propose that much about the origin of agriculture can be understood in terms of two propositions:
Agriculture was impossible during the last glacial age. During the last glacial age, climates were variable and very dry over large areas. Atmospheric levels of CO2 were low. Probably most important, last-glacial climates were characterized by high-amplitude fluctuations on timescales of a decade or less to a millennium. Because agricultural subsistence systems are vulnerable to weather extremes, and because the cultural evolution of subsistence systems making heavy, specialized use of plant resources occurs relatively slowly, agriculture could not evolve.
In the long run, agriculture is compulsory in the holocene epoch. In contrast to the Pleistocene climates, stable Holocene climates allowed the evolution of agriculture in vast areas with relatively warm, wet climates, or access to irrigation. Prehistoric populations tended to grow rapidly to the carrying capacity set by the environment and the efficiency of the prevailing subsistence system. Local communities that discover or acquire more intensive subsistence strategies will increase in number and exert competitive pressure on smaller populations with less intensive strategies. Thus, in the Holocene epoch, such intergroup competition generated a competitive ratchet favoring the origin and diffusion of agriculture.”

This is the basic idea. But the chapter has a lot more:

“For the last 400,000 years, very high-resolution climate proxy data are available from ice cores taken from the deep ice sheets of Greenland and Antarctica. Resolution of events lasting little more than a decade is possible in Greenland ice 80,000 years old, improving to monthly resolution 3,000 years ago. During the last glacial, the ice core data show that the climate was highly variable on time scales of centuries to millennia […] The last glacial period was arid and extremely variable compared to the Holocene. Sharp millennial-scale excursions occur in estimated temperatures, atmospheric dust, and greenhouse gases. The intense variability of the last glacial carries right down to the limits of the nearly 10-year resolution of the ice core data. […] Even though diffusion and thinning within the ice core progressively erases high-frequency variation in the core […] the shift from full glacial conditions about 18,000 years ago to the Holocene interglacial is accompanied by a dramatic reduction in variation on timescales shorter than 150 years. The Holocene (the last relatively warm, ice-free 11,600 years) has been a period of very stable climate, at least by the standards of the last glacial age.[2] The climate fluctuations recorded in high-latitude ice cores are also recorded at latitudes where agriculture occurs today. Sediments overlain by anoxic water that inhibits sediment mixing by burrowing organisms are a source of low- and mid-latitude data with a resolution rivaling ice cores. Events recorded in North Atlantic sediment cores are closely coupled to those recorded in Greenland ice […], but so are records distant from Greenland. Hendy and Kennett (2000) report on water temperature proxies from sediment cores from the often-anoxic Santa Barbara Basin just offshore of central California. This data shows millennial- and submillennial-scale temperature fluctuations from 60–18 thousand years ago with an amplitude of about 8°C, compared to fluctuations of about 2°C in the Holocene epoch. As in the Greenland cores, the millennial-scale events often show very abrupt onsets and terminations and are often punctuated by brief spikes of warmth and cold.”

“We expect that opportunism was the most important strategy for managing the risks associated with plant foods during the last glacial age. Annual plants have dormant seed that spreads their risk of failure over many years, and perennials vary seed output or storage organ size substantially between years as weather dictates. In a highly variable climate, the specialization of exploitation on one or a few especially promising species would be highly unlikely, because ‘‘promise’’ in one year or even for a decade or two would turn to runs of years with little or no success. However, most years would likely be favorable for some species or another, so generalized plant-exploitation systems are compatible with highly variable climates. […] Plant food-rich diets take considerable time to develop. Plant foods are generally low in protein and often high in toxins. Some time is required to work out a balanced diet rich in plant foods, for example, by incorporating legumes to replace part of the meat in diets. Whether intensification and agriculture always lead to health declines due to nutritional inadequacy is debatable, but the potential for them to do so absent sometimes-subtle adaptations is clear […] The seasonal round of activities has to be much modified, and women’s customary activities have to be given more prominence relative to men’s hunting. Changes in social organization either by evolution in situ or by borrowing tend to be slow […] We doubt that even sophisticated last-glacial hunter-gatherers would have been able to solve the complex nutritional and scheduling problems associated with a plant-rich diet while coping with unpredictable high-amplitude change on timescales shorter than the equilibration time of plant migrations and shorter than actual Holocene trajectories of intensification.”

“Low mean productivity, along with greater variance in productivity, would have greatly decreased the attractiveness of plant resources during the last glacial age. Lower average rainfall and carbon dioxide during the last glacial age reduced the area of the earth’s surface suitable for agriculture […] On present evidence we cannot determine whether aridity, low CO2 levels, millennial-scale climate variability, or submillennial-scale weather variation was the main culprit in preventing the evolution of agriculture. Low CO2 and climate variation would handicap the evolution of dependence on plant foods everywhere and were surely more significant than behavioral or technological obstacles. Hominids evolved as plant-using omnivores (Milton, 2000), and the basic technology for plant exploitation existed at least 10 thousand years before the Holocene […] At least in favorable localities, appreciable use seems to have been made of plant foods, including large-seeded grasses, well back into the Pleistocene […] Significantly, we believe, the use of such technology over spans of last-glacial time that were sufficient for successive waves of intensification of subsistence in the Holocene led to only minor subsistence intensification, compared to the Mesolithic, Neolithic, and their ever-more-intensive successors. […] After 11,600 B.P., the Holocene period of relatively warm, wet, stable, CO2-rich environments began. Subsistence intensification and eventually agriculture followed. Thus, while not perfectly instantaneous, the shift from glacial to Holocene climates was a very large change and took place much more rapidly than cultural evolution could track.”

“Might we not expect agriculture to have emerged in the last interglacial 130,000 years ago or even during one of the even older interglacials? No archaeological evidence has come to light suggesting the presence of technologies that might be expected to accompany forays into intensive plant collecting or agriculture at this time. Anatomically modern humans may have appeared in Africa as early as 130,000 years ago […], but they were not behaviorally modern. Humans of the last interglacial were uniformly archaic in behavior. Very likely, then, the humans of the last interglacial were neither cognitively nor culturally capable of evolving agricultural subsistence. However, climate might also explain the lack of marked subsistence intensification during previous interglacials. Ice cores from the thick Antarctic ice cap at Vostok show that each of the last four interglacials over the last 420,000 years was characterized by a short, sharp peak of warmth, rather than the 11,600-year-long stable plateau of the Holocene (Petit et al., 1999).”

“Once a more productive subsistence system is possible, it will, over the long run, replace the less-productive subsistence system that preceded it. The reason is simple: all else being equal, any group that can use a tract of land more efficiently will be able to evict residents that use it less efficiently […] More productive uses support higher population densities, or more wealth per capita, or both. An agricultural frontier will tend to expand at the expense of hunter-gatherers as rising population densities on the farming side of the frontier motivate pioneers to invest in acquiring land from less-efficient users. […] Thus, subsistence improvement generates a competitive ratchet as successively more land-efficient subsistence systems lead to population growth and labor intensification. Locally, huntergatherers may win some battles (e.g., in the Great Basin; Madsen, 1994), but in the long run the more intensive strategies will win wherever environments are suitable for their deployment. The archaeology supports this argument […] Societies in all regions of the world undergo a very similar pattern of subsistence efficiency increase and population increase in the Holocene, albeit at very different rates. Holocene hunter-gatherers developed local equilibria that, while sometimes lasting for thousands of years, were almost always replaced by more intensive equilibria.”

“Cohen’s (1977) influential book argued that slowly accumulating global-scale population pressure was responsible for the eventual origins of agriculture beginning at the 11,600 B.P. time horizon. He imagines, quite plausibly, that subsistence innovation is driven by increases in population density, but, implausibly we believe, that a long, slow buildup of population gradually drove people to intensify subsistence systems to relieve shortages caused by population growth, eventually triggering a move to domesticates. Looked at one way, population pressure is just the population growth part of the competitive ratchet. However, this argument fails to explain why pre-agricultural hunter-gatherer intensification and the transition to agriculture began in numerous locations after 11,600 years ago […] Assuming that humans were essentially modern by the Upper Paleolithic, they would have had 30,000 years to build up a population necessary to generate pressures for intensification. Given any reasonable estimate of the human intrinsic rate of natural increase under hunting-and-gathering conditions (somewhat less than 1% yr-1 to 3% yr-1, populations substantially below carrying capacity will double in a century or less […] If agricultural technologies were quick and easy to develop, the population pressure argument would lead us to expect Pleistocene populations to shift in and out of agriculture and other intensive strategies as they find themselves in subsistence crises due to environmental deterioration or in periods of plenty due to amelioration. Most likely, minor intensifications and de-intensifications were standard operating procedure in the Pleistocene. However, the time needed to progress much toward plant-rich strategies was greater than the fluctuating climate allowed, especially given CO2- and aridity-limited plant production.”

This part is really important to understand, and I know I’ve talked about this before but I’ll say it again: Humans living, say, 25.000 years ago were not stupid. They weren’t monkeys walking around looking for berries in the woods. They probably tried and tried repeatedly to make this kind of stuff work, explore all kinds of creative ways to obtain enough/more food, always slightly adjusting their strategies in order to stay alive and keep having kids – but the climate wouldn’t allow them to ever achieve ‘take off’. As they put it towards the end of the chapter: “If climate variation did not limit intensification during the last glacial age to vanishingly slow rates compared to the Holocene epoch, the failure of intensive systems to evolve during the tens of millennia anatomically and culturally modern humans lived as sophisticated hunter-gatherers before the Holocene is a considerable mystery.” It seems climate is a big part of the explanation why we never got to where we are now before we did. Environmental constraints limit the activities of all lifeforms in all kinds of ways, and it would serve us well every once in a while to recall that we are in fact no different, even if we like to think we are, and that such effects may have played a crucial role in the history of our species.

I’ve added a bit more from the book. Some of the stuff below I talked about in the last post as well (do recall that I wrote that post before I read this chapter), but I figured it wouldn’t hurt to include it here anyway:

“The timing of initiation of agriculture varies quite widely […] The exact sequence of events also varies quite widely. For example, in the Near East, sedentism preceded agriculture, at least in the Levantine Natufian sequence, but in Mesoamerica crops seem to have been added to a hunting-and-gathering system that was dispersed and long remained rather mobile […] For example, squash seems to have been cultivated around 10,000 B.P. in Mesoamerica, some 4,000 years before corn and bean domestication began to lead to the origin of a fully agricultural subsistence system […] Some mainly hunting-and-gathering societies seem to have incorporated small amounts of domesticated plant foods into their subsistence system without this leading to full-scale agriculture for a very long time. […] the path forward through the whole intensification sequence varied considerably from case to case.”

“In all known cases, the independent centers of domestication show a late sequence of intensification beginning with a shift from a hunter-gatherer subsistence system based upon low-cost resources using minimal technological aids to a system based upon the procurement and processing of high-cost resources, including small game and especially plant seeds or other labor-intensive plant resources, using an increasing range of chipped and ground stone tools […] The reasons for this shift are the subject of much work among archaeologists […] The shifts at least accelerate and become widespread only in the latest Pleistocene or Holocene. However, a distinct tendency toward intensification is often suggested for the Upper Paleolithic more generally. […] Upper Paleolithic peoples often made considerable use of small mammals and birds in contrast to earlier populations. These species have much lower body fat than large animals, and excessive consumption causes ammonia buildup in the body due to limitations on the rate of urea synthesis […] Consequently, any significant reliance on low-fat small animals implies corresponding compensation with plant calories, and at least a few Upper Paleolithic sites, such as the Ohalo II settlement on the Sea of Galilee […], show considerable use of plant materials in Pleistocene diets. Large-seeded annual species like wild barley were no doubt attractive resources in the Pleistocene when present in abundance and would have been used opportunistically during the last glacial age. If our hypothesis is correct, in the last glacial age no one attractive species like wild barley would have been consistently abundant (or perhaps productive enough) for a long enough span of time in the same location to have been successfully targeted by an evolving strategy of intensification, even if their less intensive exploitation was common. The broad spectrum of species, including small game and plants, reflected in these cases is not per se evidence of intensification (specialized use of more costly but more productive resources using more labor and dedicated technology), as is sometimes argued […] In most hunter-gatherer systems, marginal diet cost and diet richness (number of species used) are essentially independent […], and prey size is far less important in determining prey cost than either mode or context of capture […] For all these reasons, quantitative features of subsistence technology are a better index of Pleistocene resource intensification than species used. We believe that the dramatic increase in the quantity and range of small chipped stone and groundstone tools only after 15,000 B.P. signals the beginning of the pattern of intensification that led to agriculture.”

“Early intensification of plant resource use would have tended to generate the same competitive ratchet as the later forms of intensification. Hunter-gatherers who subsidize hunting with plant-derived calories can maintain higher population densities and thus will tend to deplete big game to levels that cannot sustain hunting specialists […] Once the climate ameliorated, the rate of intensification accelerated immediately in the case of the Near East. In other regions changes right at the Pleistocene-Holocene transition were modest to invisible […] The full working out of agrarian subsistence systems took thousands of years. […] Fully agricultural subsistence systems in the sense of a dominance of domesticated species in the diet typically postdate the origin of agriculture [which they define as “dependence upon domesticated crops and animals for subsistence” – US] by a millennium or more. […] Zvelebil (1996) emphasizes the complexity and durability of frontiers between farmers and hunter-gatherers and the likelihood that in many places the diffusion of both genes and ideas about cultivation was a prolonged process of exchange across a comparatively stable ethnic and economic frontier.”

June 5, 2014 Posted by | Anthropology, Archaeology, Books, Botany, culture, Evolutionary biology | Leave a comment

The Origin and Evolution of Cultures (III)

I have read almost three-fourths of the book by now. In this post I have quoted extensively from chapter 14 because this chapter is somewhat different from most of the other chapters in the book; it has no math, but it has a lot of observations which relate to the work they’ve covered in previous chapters, and it’s much easier to blog than most of the stuff in this book.

I don’t always agree with the authors about the details and about the conclusions they draw, but this book is consistently interesting and provides high-quality coverage of the topic in question. Unless things go seriously downhill during the last part of the book, I’ll give it five stars on goodreads.

I wrote some comments and personal observations along the way when I wrote this post, many of which are not closely related to the book coverage. I have posted them below the quotes from the book, in the second half of the post proper. I actually did earlier on make the decision not to include the stuff I’d written in this post at all because I didn’t like what I’d written, but after making a few revisions I changed my mind. I may change it again. Either way writing about these things, rather than just reading about them, is a great way to force yourself to think more carefully about them.

“Evolutionary explanations are recursive. Individual behavior results from an interaction of inherited attributes and environmental contingencies. In most species, genes are the main inherited attributes, but inherited cultural information is also important for humans. Individuals with different inherited attributes may develop different behaviors in the same environment. Every generation, evolutionary processes — natural selection is the prototype — impose environmental effects on individuals as they live their lives. Cumulated over the whole population, these effects change the pool of inherited information, so that the inherited attributes of individuals in the next generation differ, usually subtly, from the attributes in the previous generation. Over evolutionary time, a lineage cycles through the recursive pattern of causal processes once per generation […] Note that in a recursive model, we explain individual behavior and population-level processes in the same model. Individual behavior depends, in any given generation, on the gene pool from which inherited attributes are sampled. The pool of inherited attributes depends in turn upon what happens to a population of individuals as they express those attributes. Evolutionary biologists have a long list of processes that change the gene frequencies, including natural selection, mutation, and genetic drift. However, no organism experiences natural selection. Organisms either live or die, or reproduce or fail to reproduce, for concrete reasons particular to the local environment and the organism’s own particular attributes. If, in a particular environment, some types of individuals do better than others, and if this variation has a heritable basis, then we label as “natural selection” the resulting changes in gene frequencies of populations. We use abstract categories like selection to describe such concrete events because we wish to build up — concrete case by concrete case — some useful generalizations about evolutionary process. Few would argue that evolutionary biology is the poorer for investing effort in this generalizing project. Although some of the processes that lead to cultural change are very different than those that lead to genetic change, the logic of the two evolutionary problems is very similar.”

“Evolutionary theory is always multi-level […] evolutionary theories are systemic, integrating every part of biology. In principle, everything that goes into causing change through time plays its proper part in the theory. […] In theorizing about human evolution, we must include processes affecting culture in our list of evolutionary processes along side those that affect genes. Culture is a system of inheritance. We acquire behavior by imitating other individuals much as we get our genes from our parents. A fancy capacity for high-fidelity imitation is one of the most important derived characters distinguishing us from our primate relatives […] We are also an unusually docile animal (Simon 1990) and unusually sensitive to expressions of approval and disapproval by parents and others (Baum 1994). Thus parents, teachers, and peers can rapidly, easily, and accurately shape our behavior compared to training other animals using more expensive material rewards and punishments. […] once children acquire language, parents and others can communicate new ideas quite economically. Our own contribution to the study of human behavior is a series of mathematical models in the Darwinian style of what we take to be the fundamental processes of cultural evolution”

“We make [the] claim that a dual gene-culture theory of some kind will be necessary to account for the evolution of human cooperative institutions. Understanding the evolution of contemporary human cooperation requires attention to two different time scales: First, a long period of evolution in the Pleistocene shaped the innate “social instincts” that underpin modern human behavior. During this period, much genetic change occurred as a result of humans living in groups with social institutions heavily influenced by culture, including cultural group selection […] On this timescale genes and culture coevolve, and cultural evolution is plausibly a leading rather than lagging partner in this process. We sometimes refer to the process as “culture-gene coevolution.” Then, only about 10,000 years ago, the origins of agricultural subsistence systems laid the economic basis for revolutionary changes in the scale of social systems. The evidence suggests that genetic changes in the social instincts over the last 10,000 years are insignificant. […] Our hypothesis is premised on the idea that selection between groups plays a much more important role in shaping culturally transmitted variation than it does in shaping genetic variation. As a result, humans have lived in social environments characterized by high levels of cooperation for as long as culture has played an im portant role in human development. […] We believe that the human capacity to live in larger scale forms of tribal social organization evolved through a coevolutionary ratchet generated by the interaction of genes and culture. Rudimentary cooperative institutions favored genotypes that were better able to live in more cooperative groups. Those individuals best able to avoid punishment and acquire the locally-relevant norms were more likely to survive. At first, such populations would have been only slightly more cooperative than typical nonhuman primates. However, genetic changes, leading to moral emotions like shame, and a capacity to learn and internalize local practices, would allow the cultural evolution of more sophisticated institutions that in turn enlarged the scale of cooperation. These successive rounds of coevolutionary change continued until eventually people were equipped with capacities for cooperation with distantly related people, emotional attachments to symbolically marked groups, and a willingness to punish others for transgression of group rules.”

“Upper Paleolithic societies were the culmination of a long period of coevolutionary increases in a tendency toward tribal social life. We suppose that the resulting “tribal instincts” are something like principles in the Chomskian linguists’ “principles and parameters” view of language […] The innate principles furnish people with basic predispositions, emotional capacities, and social dispositions that are implemented in practice through highly variable cultural institutions, the parameters. People are innately prepared to act as members of tribes, but culture tells us how to recognize who belongs to our tribes, what schedules of aid, praise, and punishment are due to tribal fellows, and how the tribe is to deal with other tribes — allies, enemies, and clients. […] Contemporary human societies differ drastically from the societies in which our social instincts evolved. Pleistocene hunter-gatherer societies were likely comparatively small, egalitarian, and lacking in powerful institutionalized leadership. […] To evolve largescale, complex social systems, cultural evolutionary processes, driven by cultural group selection, takes advantage of whatever support these instincts offer. […] cultural evolution must cope with a psychology evolved for life in quite different sorts of societies. Appropriate larger scale institutions must regulate the constant pressure from smaller-groups (coalitions, cabals, cliques), to subvert the large-group favoring rules. To do this cultural evolution often makes use of “work arounds” — mobilizing tribal instincts for new purposes. For example, large national and international (e.g. great religions) institutions develop ideologies of symbolically marked inclusion that often fairly successfully engage the tribal instincts on a much larger scale. Military and religious organizations (e.g., Catholic Church), for example, dress recruits in identical clothing (and haircuts) loaded with symbolic markings, and then subdivide them into small groups with whom they eat and engage in long-term repeated interaction. Such work-arounds are often awkward compromises […] In military and religious organizations, for example, excessive within-group loyalty often subverts higher-level goals […] Complex societies are, in effect, grand natural social-psychological experiments that stringently test the limits of our innate dispositions to cooperate.”

“Elements of coercive dominance are no doubt necessary to make complex societies work. Tribally legitimated self-help violence is a limited and expensive means of altruistic coercion. Complex human societies have to supplement the moralistic solidarity of tribal societies with formal police institutions. […] A common method of deepening and strengthening the hierarchy of command and control in complex societies is to construct a nested hierarchy of offices, using various mixtures of ascription and achievement principles to staff the offices. Each level of the hierarchy replicates the structure of a hunting and gathering band. A leader at any level interacts mainly with a few near-equals at the next level down in the system […] The hierarchical nesting of social units in complex societies gives rise to appreciable inefficiencies […] Leaders in complex societies must convey orders downward, not just seek consensus among their comrades. Devolving substantial leadership responsibility to sub-leaders far down the chain of command is necessary to create small-scale leaders with face-to-face legitimacy. However, it potentially generates great friction if lower-level leaders either come to have different objectives than the upper leader ship or are seen by followers as equally helpless pawns of remote leaders. Stratification often creates rigid boundaries so that natural leaders are denied promotion above a certain level, resulting in inefficient use of human resources and a fertile source of resentment to fuel social discontent. On the other hand, failure to properly articulate tribal scale units with more inclusive institutions is often highly pathological. Tribal societies often must live with chronic insecurity due to intertribal conflicts.”

“The high population density, division of labor, and improved communication made possible by the innovations of complex societies increased the scope for elaborating symbolic systems. The development of monumental architecture to serve mass ritual performances is one of the oldest archaeological markers of emerging complexity. Usually an established church or less formal ideological umbrella supports a complex society’s institutions. At the same time, complex societies extensively exploit the symbolic ingroup instinct to delimit a quite diverse array of culturally defined subgroups, within which a good deal of cooperation is routinely achieved. […] Many problems and conflicts revolve around symbolically marked groups in complex societies. Official dogmas often stultify desirable innovations and lead to bitter conflicts with heretics. Marked subgroups often have enough tribal cohesion to organize at the expense of the larger social system. […] Wherever groups of people interact routinely, they are liable to develop a tribal ethos. In stratified societies, powerful groups readily evolve self-justifying ideologies that buttress treatment of subordinate groups ranging from neglectful to atrocious.”

“Many individuals in modern societies feel themselves part of culturally labeled tribal-scale groups, such as local political party organizations, that have influence on the remotest leaders. In older complex societies, village councils, local notables, tribal chieftains, or religious leaders often hold courts open to humble petitioners. These local leaders in turn represent their communities to higher authorities. To obtain low-cost compliance with management decisions, ruling elites have to convince citizens that these decisions are in the interests of the larger community. As long as most individuals trust that existing institutions are reasonably legitimate and that any felt needs for reform are achievable by means of ordinary political activities, there is considerable scope for large scale collective social action. However, legitimate institutions, and trust of them, are the result of an evolutionary history and are neither easy to manage nor engineer. […] Without trust in institutions, conflict replaces cooperation along fault lines where trust breaks down. Empirically, the limits of the trusting community define the universe of easy cooperation […] At worst, trust does not extend outside family […] and potential for cooperation on a larger scale is almost entirely foregone.”

If I were the kind of person who were interested in political stuff, I might have decided to talk a bit about how the above remarks may relate to how to set up optimal policies aimed at maintaining cooperation and trust (perhaps subject to a few relevant constraints). Some ideas spring to mind, perhaps in relation to immigration policy in particular. But I’m not that kind of person, so I won’t talk about that here.

I figured it might be a good idea to cover some ‘related’ topics here, as I can’t be sure how much the people reading along here has read about this kind of stuff and what kind of background people have. Many of the remarks below are only tangentially related to the coverage above, but they’re arguably important if you want ‘a bigger picture’.

One thing to note is that in the context of this part:

“only about 10,000 years ago, the origins of agricultural subsistence systems laid the economic basis for revolutionary changes in the scale of social systems. The evidence suggests that genetic changes in the social instincts over the last 10,000 years are insignificant.”

…there are at least two important points to mention. One is that the 10.000 years number is ‘just a number’, and that there is no ‘one true number’ here – that number depends on geography and a lot of other stuff. The origins of agriculture are still somewhat murky, though we do know a lot. There are lots of problems archaeologists need to deal with when analyzing these sorts of things, like for instance the issue that locally the date for first observed/established case of agricultural adoption may not correlate well with the first actual adoption date, because we have this tendency to overlook the sort of evidence that has already evaded attention for thousands of years. Another problem is that the switch was often gradual and took a lot of time, and involved some trial and error. A related point is that switches in food procurement strategies likely happened at local levels in the far past – in some areas of the world it would seem likely that a strategy of mostly relying on a few select crops (‘agriculture’) in ‘good periods’ (perhaps lasting hundreds of years) and then relying more on a more diversified set of different crops as well as other complementary food sources (‘hunter-gathering’) in ‘bad periods’ may have been superior to a strategy of relying exclusively on one or the other, especially around the ‘border areas’ where people almost couldn’t make agriculture work at all due to climatic factors. It’s incidentally worth noting that “no single plant can provide the mix of amino acids that primates need for growth, so primates must either eat a variety of different plants to achieve an adequate amino-acid balance, or have a regular supplement of animal foods in their diet”, so the ‘rely-on-only-one-plant agricultural model and nothing else’ is not workable in practice and never was (quote from Sponheimer et al., p.361. Less extreme versions of dependence on a single crop is feasible if you can get the other stuff elsewhere, but it’s highly risky – ask e.g. the Irish. Despite how far we’ve come in other areas, we humans incidentally rely on quite few crops to supply a substantial part of the calories we need, making us somewhat vulnerable; for example more than one-fifth of all calories consumed by humans are derived from rice). Yet another problem is that ‘agriculture’ isn’t just ‘agriculture’ – people got better at this stuff over time and things like intensification and yield improvements were important, yet often difficult or frankly impossible to estimate, especially at the intensive margin. This means that ‘we think agriculture started here in 8900 BC’ may in some contexts not mean quite what you could be tempted to think it means.

But the above, and many related, issues aside, of course the main problem with a statement including words like ‘about 10,000 years ago’ is that the variation in when different people living different places ‘adopted agriculture’ (whatever that may mean) is astonishingly huge. Here are two illustrative passages from Scarre et al. – exhibit 1: “The site of Ohalo II in northern Israel, dated around 20,000 BC, provides a remarkable snapshot of lifeways in the Levant during the Last Glacial Maximum […] At Ohalo II […] we have evidence for the exploitation of a broad spectrum of plants and animals, the extensive use of storable plant foods, and the year-round occupation of a settlement. The starch traces found on the surfaces of grinding stones confirm that they were indeed used in the preparation of hard-seeded plant foods.” The site is a hunter-gatherer site, but these guys belonged to a sedentary hunter-gatherer settlement inhabited by people who were doing many, though not all, of the things we usually only associate with traditional farmers, illustrating how these sorts of categorizations sometimes get slightly complicated if you’re not very careful when you define your terms (and sometimes even if you do) – and perhaps illustrating that it makes sense to be cautious about which mental models of our hunter-gatherer forebears we apply. Either way more ‘proper’ farming communities, such as these, which started to pop up during the early Neolithic were themselves likely at least in part ‘the result’ of gradual changes that humans which came before them had had on their surrounding environments (especially local flora and fauna – in terms of the latter probably especially our impact on local megafauna) – the processes which eventually lead us to agriculture probably took a lot of time, though just how long into the past you need to look to get the full picture is an open question, and probably will remain so as the amount of evidence available to us is sparse (which impact had human activities taking place during the late Pleistocene had on the range and distribution of potential domesticables at the beginning of the Holocene? Such questions do not to me seem easy to answer, and they’re part of the story). Although agriculture in some areas of the world by now has a ‘shelf life’ of 10.000 years or more, in other areas of the world that ‘shelf life’ is much, much shorter – exhibit 2: “no agricultural colonization of Australia, the last completely hunter-gatherer continent to survive until European contact, ever occurred.”

Agriculture provided the economic foundation for achieving the scale of social complexity which humans have achieved. This is true, but an important point/caveat here is that the evolution of ‘(relatively) advanced cultural and societal complexity’ in prehistoric times was not always contingent upon agriculture; agriculture often did lead to societal complexity, but humans could rise in societal complexity and experience significant cultural evolution without it – there were sedentary populations of some size and organizational complexity living in communities without what we usually conceptualize as agriculture (viz farming or pastoralism), e.g. in areas well-endowed with natural resources such as those near major lakes or coasts full of fish. To take one example (again from Scarre et al.), “agriculture was not a necessary prerequisite for the emergence of chiefdoms in the Southeast [North America]” – another example would be the “longstanding “Maritime Hypothesis” […] which proposes […] that maritime resources sustained population growth and the rise of sedentary earthwork-building communities” along the Pacific coast of South America during prehistoric times. There were mound builders in pre-agricultural North America as well, see e.g. this and this.

It’s worth remembering when thinking about human societies which existed especially during transitional phases – which may include many different time periods, depending on which part of the world you’re looking at – where people were starting to use agriculture but perhaps hadn’t really gotten the hang of it yet, that hunter-gatherer groups occasionally simply outcompeted farmers at the local level because some places just plain aren’t very good places to engage in agriculture, meaning that the ‘cultural victory’ of agriculturalists was by no means universal or a given at the local level, even if it’s very easy to convince yourself otherwise if you don’t know very much about these aspects of human development. Sometimes new (‘cultural’) inventions, like irrigation systems, could turn the tide in situations and geographic localities where agricultural food procurement strategies were at a disadvantage, but occasionally even that wasn’t enough.

Food production practices are/were key to societal complexity, because in order to get complexity you need to produce enough ‘excess food’ for some people to be free to engage themselves in non-food-production/procuring-activities, but another related point is that how to actually categorize and delineate various prehistoric food production practices is not always completely obvious. Food production undertaken by humans can take on multiple forms, and sometimes an ‘agriculture’ vs ‘hunter-gatherers’ dichotomic conceptualization of the issues may make you overlook important details due to ‘misclassification’ or similar problems; to take a couple of examples, some prehistoric sedentary societies based on fishing were as mentioned more or less stable food producing societies, and on a different note the cultural practices of (mobile) pastoralist societies often shared some social dimensions with hunter-gatherer societies that e.g. sedentary rice farming societies did not. Worth keeping in mind in this context is also that present-day hunter-gatherer societies still in existence often do not well reflect the cultural aspects of hunter-gatherer societies which existed in the far past, meaning that you need to be very careful about which inferences you make and what you base them on.

An aspect really important to keep in mind in general when thinking about the Holocene ‘post-agricultural period’ of human development is that the cultural development which took place in agricultural societies did not take place in a vacuum. Agriculturalists interacted with hunter-gatherers, farmers interacted with pastoralists, different e.g. geographic (mountains, seas) and biological constraints (malaria, horses) shaped human development in all kinds of ways. Boyd and Richerson do talk about this in the book, but I figured I should as well in this post. One thing to note is that in some areas agricultural practices spread much faster than in others for reasons having nothing to do with ‘the type’ of people who were doing these things, for example due to reasons of physical geography or other environmental constraints or the lack of such, and both the speed and manner of adoption likely had important (and varied) cultural ramifications. These things had genetic ramifications as well; areas where agricultural spread was particularly easy saw population growth other areas did not. Climate and climatic variation post-adoption incidentally naturally had important cultural ramifications as well – for example looking over the (pre)history of pre-colonial South America, it’s obvious that climate here was a key parameter with a huge impact on ‘the rise and fall of civilizations’.

There were multiple ways for agriculture to spread, from pure displacement to pure local adoption, as well as any combination in between, and how it proceeded varied with geography and probably a lot of other stuff as well. Some places and times the optimal type of agriculture was variable over time; which didn’t just mean that it made sense for farming societies to diversify and rely on more than one crop with different responses to e.g. drought, but also that climate change sometimes caused people to switch away from farming and towards pastoralism in bad periods – a good example of the latter is Peru during the Late Intermediate Period, where it is clear that “intensification of pastoralism was an important respone to drought” (see Moseley, p.246). Aspects such as climate have certainly had various important cultural as well as genetic impacts around the globe, e.g. on cultural transmission patterns at the regional level even during the ‘post-agricultural’ period. I mentioned interaction patterns – themselves a result of cultural dynamics, but also a driver of them – between sedentary farming societies and more mobile hunter-gatherers or pastoralists above, and perhaps I should say a little more about this kind of stuff because people may not be clear on precisely what I’m getting at there. It seems clear that in some areas division of labour dynamics played an important role in explaining and shaping cultural evolution; for a great account of these aspects of cultural dynamics and evolution in mountainous terrains and their surrounding areas, I again refer to Moseley’s account here. Inhabitants of sedentary farming societies didn’t move around very much, so things which were far away from them were things they’d often be willing to trade with more mobile human groupings. From one point of view you have a type of (modified) core-periphery model where the people from the core produced ‘excess’ food, and/or things which the people living in the core area who did not have to work on food procurement could come up with, which they then traded for other stuff, e.g. various natural resources located elsewhere (metals and wood are classic examples), with people who lived on the periphery. People looking at these things today without knowing anything about how such interaction patterns looked like may, I think, have a tendency to think of mobile hunter-gatherer groups as the morons who were left behind in this story and the pastoralists as more ‘primitive’ than the farmers, but I don’t really think that’s necessarily how it was – sometimes quite neat systems of exchange benefited both groups and were arguably by themselves important drivers of ‘cultural progress’, in the sense that they enabled and facilitated increased social complexity in the societies engaged in such systems. Of course peaceful interaction patterns were not the only ones which were explored.

May 28, 2014 Posted by | Anthropology, Archaeology, Books, culture, Evolutionary biology, Religion | Leave a comment

The Origin and Evolution of Cultures (II)

“Brain tissue is quite expensive. All else equal, selection will favor the stupidest possible creatures.”

I really liked that quote. Here’s a related one from the book:

“On the cost side, selection will favor as small a nervous system as possible. If our hypothesis is correct, animals with complex cognition foot the cost of a large brain by adapting more swiftly and accurately to variable environments.”

This post doesn’t really deal in much more detail with the observations above, I just liked those quotes and they didn’t really fit in with the rest of the coverage, though I could probably have put them in there somewhere. Before moving on to the main coverage I should note that it would make a lot of sense for people who read this post to read my first post about the book before reading this one. If you’ve already done so, do carry on.

After I’d read the first couple hundred pages I was a bit exhausted, and I’ve taken a break from this book for a while; as I pointed out on goodreads when I started, “I’m far from certain I’ll manage to get through this one in one go.” Yesterday I decided to pick up the book again, and fortunately the next few chapters seem less technical than the ones that had me putting the book away for a while.

The book is really nice, but it feels hard for me to blog because of the technical nature of the coverage (much of this stuff is really just applied game theory). Most chapters will deal with a specific model and talk about the model results, and unless I actually tell you all about what the models are doing and which assumptions are made (i.e., basically repost the entire book here) a lot of critical details will be left out – there are a lot of caveats and nuances, and not including them in the coverage might give people the wrong idea about what’s going on in the book. Sometimes a complex model is compared to a simple model in a chapter and the complex model is the more interesting one; in those cases you may need to cover the simple model as well for it to make sense to talk about the details of the complex model, and we’re back to ‘it’s hard to exclude anything’. A general ‘problem’ with this book in terms of these things – which is of course properly to be considered a strength – is that there aren’t really that many pages with fluffy stuff you can just leave out. Fortunately they occasionally draw conclusions from the models and try to give a big-picture account of what’s going on, and I’ve disproportionately quoted from those passages in the post below. I’ve left a lot of details out, but there was no alternative to doing that. A lot of crucial context which I’ve not realized is missing is probably missing anyway – do ask questions if something is unclear here.

“Human brains […] are adapted to life in small-scale hunting and gathering societies of the Pleistocene. They will guide behavior within such societies with considerable precision, but behave unpredictably in other situations. […] Learning devices will be favored only when environments are variable in time or space in difficult to predict ways. Social learning is a device for multiplying the power of individual learning. […] Social learning can economize on the trial and error part of learning. […] Selection will favor individual learners who add social learning [‘learn from others, e.g. by imitating them‘] to their repertoire so long as copying is fairly accurate and the extra overhead cost of the capacity to copy is not too high. In some circumstances, the models suggest that social learning will be quite important relative to individual learning. It can be a great advantage compared to a system that relies on genes only to transmit information and individual learning to adapt to the variation. Selection will also favor heuristics that bias social learning in adaptive directions. When the behavior of models [‘people you might copy’] is variable, individuals who try to choose the best model by using simple heuristics like “copy dominants” or “go with the majority,” or by using complex cognitive analyses, are more likely to do well than those who blindly copy. Contrarily, if it is easy for individuals to learn the right thing to do by themselves, or if environments vary little, then social learning is of no utility.”

“We believe that the lessons of [the] model [they just talked about] are robust. It formalizes three basic assumptions:

1. The environment varies.
2. Cues about the environment are imperfect, so individuals make errors.
3. Imitation increases the accuracy (or reduces the cost) of learning.

We have analyzed several models that incorporate these assumptions but differ in other features. All of these models lead to the same qualitative conclusion: when learning is difficult and environments do not change too fast, most individuals imitate at evolutionary equilibrium. At that equilibrium, an optimally imitating population is better off, on average, than a population that does not imitate. […] for something to be a norm, there has to be a conformist element. People must agree on the appropriate behavior and disapprove of others who do not behave appropriately. We […] show that individuals who respond to such disapproval by conforming to the social norm are more likely to acquire the best behavior. […] as the tendency to conform increases, so does the equilibrium amount of imitation. […] all conditions that lead a substantial fraction of the population to rely on imitation also lead to very strong conformity. […] a tendency to conform increases the number of people who follow social norms and decreases the numbers who think for themselves.”

“Human populations are richly subdivided into groups marked by seemingly arbitrary symbolic traits, including distinctive styles of dress, cuisine, or dialect. Such symbolically marked groups often have distinctive moral codes and norms of behavior, and sometimes exhibit economic specialization. […] The following two chapters explore the idea that symbolically marked groups arise and are maintained because dress, dialect, and other markers allow people to identify in-group members. In chapter 6, we analyze a model that assumes that identifying in-group members is useful because it allows selective imitation. Rapid cultural adaption makes the local population a valuable source of information about what is adaptive in the local environment. Individuals are well advised to imitate locals and avoid learning from immigrants […] studies like those of Fredrik Barth […] suggest that contemporary ethnic groups often occupy different ecological niches. […] In chapter 7, we […] study a model in which markers allow selective social interaction. […] These models have several interesting and, at least to us, less-than-obvious properties. First, the same nonrandom interaction that makes markers useful also creates and maintains variation in symbolic marker traits as an unintended by-product. Nonrandom interaction acts to increase correlation between arbitrary markers and locally adaptive behaviors. This, in turn, makes markers more useful, setting up a positive feedback process that can amplify small differences in markers between groups. […] once groups have become sharply marked, the feedback process is sufficient by itself to maintain group marking even if groups are perfectly mixed and there is no population structure other than that caused by the markers. […] processes closely related to those modeled here can lead to the “runaway” evolution of marker and preference traits, which have no adaptive or functional explanation […] It is easy to imagine that the adaptive uses of cultural markers are common enough so that selection on genes maintains a cognitive capacity to use them despite the runaway process carrying some to maladaptive extremes. We are convinced that complexities of this sort are a pervasive feature of the coevolutionary process that links genes and culture. If this idea is correct, any attempt to reduce the problems of human evolution to binary choices between sociobiological and cultural explanations is bound to fail.”

“Studies of the diffusion of innovations […] suggest that people often use two simple rules to increase the likelihood that they acquire locally adaptive beliefs by imitation. The chance that individual A will adopt an innovation modeled by individual B [i.e., ‘do as B does’] often seems to depend upon (1) how successful B is, and (2) the similarity of A and B.”

“Many anthropologists believe that people follow the social norms of their society without much thought. According to this view, human behavior is mainly the result of social norms and rarely the result of considered decisions. […] Many anthropologists also believe that social norms lead to adaptive behaviors; by following norms, people can behave sensibly without having to understand why they do what they do. […] Norms will change behavior only if they prescribe behavior that differs from what people would do in the absence of norms. […] By this notion, people obey norms because they are rewarded by others if they do and punished if they do not. As long as the rewards and punishments are sufficiently large, norms can stabilize a vast range of different behaviors.”

One thing to note both in relation to the paragraph above and to the passage quoted below is that there’s a big conceptual difference between strategies which punish defection strategies by withholding future cooperation, and strategies which ‘actively’ punish defectors (presumably e.g. by beating them up, killing them…). Perhaps one way to conceptualize the difference between the two types of strategies is to think of the former set of strategies as a collection of strategies where punished individuals are limited to a payoff of 0, whereas punished individuals in the latter context might experience (unbounded?) negative payoffs as well. Reciprocating strategies, where you cooperate when others do and sanction defection with non-cooperation in the future, are what Boyd and Richerson look at first, and it turns out that such strategies actually don’t do very well in large groups, in the sense that it seems implausible that such strategies in their models on their own would support cooperative equilibria when n is large, which is the motivation for looking at actual ‘punishment strategies’ that go a bit further than that. A problem with punishment strategies is that they’re often (but not always) altruistic in the sense that if punishment works by making defectors switch to ‘cooperate’ in future periods and it’s costly for an individual to punish someone, then punishing someone is quite likely to mostly benefit other people (especially as n grows) while the person doing the punishing is the one incurring the cost – punishment is a public good. So people may decide to become ‘reluctant punishers’ that let the others do the punishing, and if enough people go that route these equilibria become unstable (this is a problem termed ‘the problem of second-order cooperation’ – you can defect at any stage in the game, and in this particular case it’s a two-stage game where you can either defect from the start, or you defect at the second stage and refuse to punish those that defected during the first period). If n is small, punishment strategies may not necessarily be altruistic – you may meet and interact with the guy enough times in the future for it to make sense to punish him now – and if the cost of punishment is small compared to the benefits from cooperation that will of course also help support equilibria of that nature. A general thing to note here, which is perhaps not made perfectly clear in the stuff above, is that finding out how ‘cooperative equilibria’ of one kind or another may come about and under which conditions they’re stable is really a big part of understanding what culture is all about and how it works, when you look at it from a certain point of view – it’s puzzling that humans cooperate with other humans to the extent that they do, and as people who’ve done theoretical work on this stuff have found out over the years, it’s actually not at all easy to figure out why they (we) do that. It’s certainly a lot more complicated than people who don’t know anything about such topics presumably think it is.

I really liked the stuff they had on moralistic strategies, a subset of the punishment strategies analyzed in chapter 9, and I’ve quoted from this below:

“Moralistic strategies [are] strategies that punish defectors, individuals who do not punish noncooperators, and individuals who do not punish nonpunishers […] moralistic strategies can cause any individually costly behavior to be evolutionarily stable, whether or not it creates a group benefit. Once enough individuals are prepared to punish any behavior, even the most absurd, and to punish those who do not punish, then everyone is best off conforming to the norm. Moralistic strategies are a potential mechanism for stabilizing a wide range of behaviors. […] moralistic punishment is inherently diversifying in the sense that many different behaviors may be stabilized in exactly the same environment. It may also provide the basis for stable among-group variation. […] In the model studied here, punishers collect private benefit by inducing cooperation in their group that compensates them for punishing, while providing a public good for reluctant cooperators. There are often polymorphic equilibria in which punishers are relatively rare, generating a simple political division of labor […] This finding invites study of further punishment strategies. Consider, for example, strategies that punish but do not cooperate. Such individuals might be able to coerce more reluctant cooperators than cooperator-punishers and therefore support cooperation in still larger groups.”

That chapter has a lot more details about those things. Anyway, behavioural strategies that look terribly maladaptive ‘from the outside’ (and/or may in fact be terribly maladaptive (…at the group level) – do note that these two do not necessarily overlap) may become fixed in a population even so, and such equilibria, once reached, may be very hard to break. This isn’t exactly an uplifting story, but of course if you’ve had a look around the world this shouldn’t be news. As mentioned, it’s very much worth having in mind that a strategy which outsiders might think is really quite awful, because it leads to behaviours the outsiders don’t like, may still be highly adaptive – the adaptiveness of a behavioural strategy set and whether said strategy set gives you a good feeling in your stomach has got nothing to do with each other, and there’s no Eternal Law of Progress, whatever that latter word might mean, guiding which strategy sets ‘win’.

May 11, 2014 Posted by | Anthropology, Books, culture, Evolutionary biology | Leave a comment

The Origin and Evolution of Cultures (1)

2845 before economics

(Smbc). The book is not really a book about economics, but I haven’t come across a similar comic with the words ‘mathematical anthropology’, or something along those lines, at the bottom and I think it’s close enough (besides I really love that cartoon).

I have talked about the book before on more than one occasion, as some of Boyd and Richerson’s results/ideas tend to naturally pop up in a lot of contexts when one is reading e.g. anthropology texts – and despite not having read the book I’ve been familiar with some of the ideas. I’ve considered it to be ‘a book I ought to read at some point’ for quite a while. I think Razib Khan said nice things about it at one point; given that I really liked a few of the other books he’s recommended I think that was what originally made me focus in on the book. I have long believed I would find the topic to be interesting as well as the suggested approach to dealing with the topic sensible; I have also, however, believed for a long time that the book would be a lot of work, which is part of what has kept me back.

I’ve now read enough, I think, to at least have an impression of what it’s about. It is, as expected, a technical book – there are quite a few remarks along these lines in the book:

“While we have not been able to solve (12) analytically, it is easy to solve numerically […] Because equation (13) is quite complex, we have not been able to derive an analytical expression for these equilibrium frequencies. However, it follows from the symmetry of the model that there is a stable symmetric equilibrium […] A more rigorous local stability analysis of the complete set of recursions supports the heuristic argument just given. Consider the set of i+1 difference equations where Δpj(j=0,1,…,i; see the Appendix) provides the dynamics of the behavioral traits at each stage. The cooperative equilibrium point […] is stable under the two distinct conditions …”

Someone ‘like me’ will not need to look up a lot of math-related stuff in order to understand the coverage in this book – the math is not that hard, it’s just that in some of the chapters there’s quite a lot of it. Then again if you’ve never seen a symmetry argument or people talking about deriving numerical solutions to troublesome analytical expressions (like the stuff above) before, and/or if you’ve never heard of eigenvalues or perhaps don’t have a good grasp of concepts like model equilibria or evolutionarily stable strategies, you’ll probably have some trouble along the way. One thing that ‘helps’ quite a bit in this context is that the math never seems superfluous; you get the clear impression that the authors did not add math in order to show how smart they are, but that they rather did it to promote and encourage a more systematic (…methodologically valid?) approach to this area of research. As they argue in the introduction:

“We think the way to make cultural explanations “hard” enough to enter into principled debates is to use Darwinian methods to analyze cultural evolution […] applying the evolutionary biologists’ concepts and methods to the study of culture […] Cultural evolution is rooted in the psychology of individuals, but it also creates population-level consequences. Keeping these two balls in the air is a job for mathematics; unaided reasoning is completely untrustworthy in such domains.”

I like their approach and I like the book so far. It has a lot of useful angles in terms of how to think about cultural stuff; variables, mechanisms, and tradeoffs.

I really liked the ‘Introduction’ chapter and before going any further I think I should a add a few (additional) remarks from that part of the book:

“People in culturally distinct groups behave differently mostly because they have acquired different beliefs, preferences, and skills, and these differences persist through time because the people of one generation acquire their beliefs and attitudes from those around them. To understand how cultures change, we set up an accounting system that describes how cultural variants are distributed in the population and how various processes, some psychological, others social and ecological, cause some variants to spread and others to decline. The processes that cause such cultural change arise in the everyday lives of individuals as people acquire and use cultural information. Some values are more appealing […] Some skills are easy to learn […] Some beliefs cause people to be more likely to be imitated […] We want to explain how these processes, repeated generation after generation, account for observed patterns of cultural variation.”

“Culture completely changes the way that human evolution works, but not because culture is learned. Rather, the capital fact is that human-style social learning creates a novel evolutionary trade-off. Social learning allows human populations to accumulate reservoirs of adaptive information over many generations, leading to the cumulative cultural evolution of highly adaptive behaviors and technology. Because this process is much faster than genetic evolution, it allows human populations to evolve (culturally) adaptions to local environments – kayaks in the arctic and blowguns in the Amazon […] To get the benefits of social learning, humans have to be credulous, for the most part accepting the ways that they observe in their society as sensible and proper, but such credulity opens human minds to the spread of maladaptive beliefs. The problem is one of information costs. The advantage of culture is that individuals don’t have to invent everything for themselves. We get adaptions like kayaks and blowguns on the cheap. The trouble is that a greed for such easy adaptive traditions easily leads to perpetuating maladaptions that somehow arise. Even though the capacities that give rise to culture and shape its content must be (or at least have been) adaptive on average, the behavior observed in any particular society at any particular time may reflect evolved maladaptions. Empirical evidence for the predicted maladaptions are not hard to find. […] The spread of such maladaptive ideas is a predictable by-product of cultural transmission.”

“Selection acting on culture is an ultimate cause of human behavior just like natural selection acting on genes. In several of the chapters in part III we argue that much cultural variation exists at the group level. Different human groups have different norms and values, and the cultural transmission of these traits can cause such differences to persist for long periods. The norms and values that predominate in a group plausibly affect the probability that the group is successful, whether it survives, and whether it expands.”

At the time the authors wrote the book they’d been working on this stuff for 30 years. The book is a collection of articles they’ve written over the years (not always together), so naturally some of the stuff – I don’t know how much as I have not looked for it – is available elsewhere; if you don’t want to read the entire book but would like to know a little more about the topic, you can probably find some of the stuff covered here in the book via google scholar; for example chapter 2 (‘Why Does Culture Increase Human Adaptability?’) in the book is as far as I can tell simply a reprint of this paper (pdf) – go have a look if you want to know what the book is like. Here’s chapter 10 (‘Why People Punish Defectors – Weak Conformist Transmission can Stabilize Costly Enforcement of Norms in Cooperative Dilemmas’ (pdf)). In the first case they put all the math in the back; as illustrated in the second link they don’t always do that. I’d rather link to those papers than cover them in detail here – go have a look if you’re curious.

The coverage in the book is really nice so far, and if the quality of the material does not drop later on I’ll certainly feel tempted to give it five stars.

April 14, 2014 Posted by | Anthropology, Books, culture, Evolutionary biology, Game theory | Leave a comment

Stuff

i. Contradictory Messages: A Content Analysis of Hollywood-Produced Romantic Comedy Feature Films.

“This study analyzed the romantic content of a sample of 40 romantic comedy films using a basic grounded theory methodology. Analyses revealed that such films appear to depict romantic relationships as having qualities of both new and long-term relationships; that is, to be both novel and exciting, yet emotionally significant and meaningful. Furthermore, relationships were shown to have both highly idealistic and undesirable qualities but, for any problems or transgressions experienced to have no real negative long-term impact on relationship functioning. The potential for viewer interpretations is discussed and the need for future research highlighted. […]

Of the 107 [romantic] gestures coded, male characters performed 90, they gave 35 of 37 gifts, performed 14 of 17 favors, and took more steps to initiate relationships (63 of 84). Such a proportion of effort could lead to the distinguishing of gender roles, identifying the man’s role to ‘‘take the lead’’ when it comes to relationships. A further implication could be female adolescent viewers’ forming of somewhat idealized relationship expectations. With films depicting male characters as frequently performing exaggeratedly romantic gestures […], female adolescents may be led to believe that such behaviors are the norm. Furthermore, by preferring to focus on behaviors between couples such as the aforementioned, it is possible that such films may make these gestures more salient to adolescents as an indication of the extent of partners’ feelings for them and the quality of the relationship itself over factors such as communication and trust.

Although there were 61 coded instances of ‘‘open about feelings and intentions,’’ there were only 4 incidents coded pertaining to trust, with 3 of these demonstrating a character’s lack of trust in their partner. […] The lack of depiction of trust becomes particularly notable when looking at the number of incidents of ‘‘deception’’ coded. There were 82 such incidents, occurring across all 40 films, ranging from white lies so as to spare partners’ feelings, to more serious acts of deception such as ulterior motives and direct lying for personal gains. These far outweighed characters confessing their lies and deceptive acts to their partners (9), with lies being discovered by partners typically by chance or indeed not at all. […]

Another category to emerge at this stage of coding that may have the potential to influence viewer perceptions was ‘‘being single.’’ Although this was one of the smaller categories, each coded incident (15) was consistently negative. Individuals who were single were depicted as either lonely and miserable […], frustrated […], or made to feel insecure […]. Two films […] even suggested that being single might interfere with career progression. Such a consistently negative representation of being single could, therefore, have the potential to negatively influence viewers’ feelings toward being single themselves. […]

It should be further noted that of the incidents of affection coded, a vast minority occurred between married couples. Married couples were typically portrayed as either unhappy with their spouse […], or were implied as happy but did little to reflect this […]. Of the depictions of affection between married couples that were coded, many were interspersed with episodes of arguing […], and most were limited to gestures such as brief kisses or standing with an arm around one other. Such a representation of marriage may leave adolescent viewers to see marriage and romance as disparate entities and with affection between married couples as an exception instead of the norm. […]

What is interesting to note about the behaviors comprising this category [‘relationship issues’], however, is that, irrespective of seriousness, there appeared to be no real consequences for characters’ transgressions in their relationships. […] Such depictions do not accurately reflect the actual emotions individuals typically experience in response to acts of deception and betrayal in their relationships, which can involve feelings of hurt, anger, resentment, and relational devaluation (Fitness, 2001). As a result, with characters’ negative behaviors either going undiscovered or having no long-lasting impact on their relationships, adolescent viewers may underestimate the consequences their behaviors can have on their own relationships.”

ii. The burden of knowledge and the ‘death of the renaissance man’: Is  innovation getting harder? by Benjamin Jones.

“This paper investigates, theoretically and empirically, a possibly fundamental aspect of technological progress. If knowledge accumulates as technology progresses, then successive generations of innovators may face an increasing educational burden. Innovators can compensate in their education by seeking narrower expertise, but narrowing expertise will reduce their individual capacities, with implications for the organization of innovative activity – a greater reliance on teamwork – and negative implications for growth. I develop a formal model of this “knowledge burden mechanism” and derive six testable predictions for innovators. Over time, educational attainment will rise while increased specialization and teamwork follow from a sufficiently rapid increase in the burden of knowledge. In cross-section, the model predicts that specialization and teamwork will be greater in deeper areas of knowledge while, surprisingly, educational attainment will not vary across fields. I test these six predictions using a micro-data set of individual inventors and find evidence consistent with each prediction. The model thus provides a parsimonious explanation for a range of empirical patterns of inventive activity. Upward trends in academic collaboration and lengthening doctorates, which have been noted in other research, can also be explained by the model, as can much-debated trends relating productivity growth and patent output to aggregate inventive effort. The knowledge burden mechanism suggests that the nature of innovation is changing, with negative implications for long-run economic growth.”

iii. The Basic Laws of Human Stupidity.

iv. Beyond Guns and God, Understanding the Complexities of the White Working Class in America. I haven’t read it and I don’t think I will, but I thought I should put the link up anyway. The link has a lot of data.

v. Some Danish church membership numbers. The site is in Danish but google translate is your friend and there isn’t much text anyway. Where I live almost 5 out of 6 people are members of the church. Over the last 20 years the national membership rate has dropped by ~0,5 percentage points/year. 4 out of 5 Danes are members of the national church, in 1990 it was 9 out of 10. Approximately 90% of the people who die are members, whereas ‘only’ approximately 70% of children being born get baptized. Children of non-Western immigrants make up less than 10% of all births (9,1% from 2006-2010) – so even though population replacement may be part of the story, there’s likely other stuff going on as well.

vi. Intelligence: Knowns and Unknowns. I may blog this in more detail later, for now I’ll just post the link.

vii. Theodore Dalrymple visited North Korea in 1989. The notes here about his visit to Department Store Number 1 are worth reading.

October 11, 2012 Posted by | culture, Data, Demographics, IQ, Papers, Psychology, Religion | Leave a comment

The National Museum of Denmark

(click to view in a higher resolution)

I went there today. “The National Museum is Denmark’s largest museum of cultural history” – and sadly, because of travel arrangements and real life stuff that came up, I had but 4 hours to spend there. Which is far from enough.

Given that I spent 4 hours there I naturally liked it a lot, it wasn’t that I couldn’t find the exit (there are signs in both Danish and English). It’s a great museum. If you don’t live in Denmark but happen one day to be in Copenhagen for some reason or another, consider wasting a full day here (or you can combine it with a visit to Glyptoteket – they are located very close to each other).

I took a lot of pictures along the way (250+), I’ve posted quite a few more of them below the fold (click the link with the Danish text: ‘læs mere’ to see the rest).

Continue reading

August 23, 2011 Posted by | Anthropology, Archaeology, culture, Personal, Random stuff | Leave a comment

Witchcraft in the 21st century

“By some estimates, about 40 percent of the cases in the Central African court system are witchcraft prosecutions. (Drug offenses in the U.S., by contrast, account for just 12 percent of arrests.) In Mbaiki — where Pygmies, who are known for bewitching each other, make up about a tenth of the population — witchcraft prosecutions exceed 50 percent of the case load, meaning that most alleged criminals there are suspected of doing things that Westerners generally regard as impossible.”

[…]

““The problem is that in a witchcraft case, there is usually no evidence,” said Bartolomé Goroth, a lawyer in Bangui, who recently defended (unsuccessfully) a coven of Pygmies who had been accused of murder-by-witchcraft in Mbaiki. Goroth said the trials generally ended with an admission of guilt by an accused witch in exchange for a modest sentence. I asked how one determined guilt in cases where the alleged witches denied the charges. “The judge will look at them and see if they act like witches,” Goroth said, specifying that “acting like a witch” entailed behaving “strangely” or “nervously” in court. His principal advice to clients, he said, was to act normally and refrain from casting any spells in the courtroom.”

Here’s the link, via MR.

May 27, 2010 Posted by | Africa, culture | Leave a comment

Why culture matters…

Jewkes and her colleagues interviewed a representative sample of 1,738 men in South Africa’s Eastern Cape and KwaZulu-Natal provinces.

Of those surveyed, 28% said they had raped a woman or girl, and 3% said they had raped a man or boy. Almost half who said they had carried out a rape admitted they had done so more than once, with 73% saying they had carried out their first assault before the age of 20.

The study, which had British funding, also found that men who are physically violent towards women are twice as likely to be HIV-positive. They are also more likely to pay for sex and to not use condoms.

Any woman raped by a man over the age of 25 has a one in four chance of her attacker being HIV-positive.

Here’s the link, via MR.

Stuff like this is also one of the reasons why I’m not an anarchist. I’m not inviting to a long discussion here, I’m just saying that things like these certainly do not in my mind disprove that Hobbes had a point.

June 18, 2009 Posted by | Africa, culture | Leave a comment