Razib Khan One-stop-shopping for all of my content

January 31, 2012

Secular liberals the tip of the Islamist spear

Filed under: Liberalism,Politics — Razib Khan @ 11:53 pm

I have long been on the record as a skeptic of the of the proposition that democratization in the Arab world will usher in liberalism. To a great extent I think that my skepticism has been vindicated, though these are early times yet. But looking at the events as they are playing out in Egypt and Tunisia reminds me of the rock-paper-scissors games.


Tunisia is arguably the best case for liberal democracy in the Arab world. It has a low fertility, a strong connection to the West via a Francophone elite, and has long banned practices such as polygyny. And unlike Egypt or Syria ethnic or religious conflict does not loom on the horizon. Tunisia is overwhelmingly Arab and overwhelming Sunni. Its Islamist party is genuinely more moderate than the Islamic Brotherhood in Egypt, and Salafists are not present in massive numbers in Tunisia. Nevertheless, it looks like Salafists have taken to beating up those whom they believe offend their sensibilities. In The New York Times article linked above there is the quote: “You lost your daddy, Ben Ali!” Ben Ali refers to the late authoritarian ruler of Tunisia. Islamists have been trying to dislodge these authoritarian rulers for decades; but it took the rising up of secular and affluent children of the middle and upper middle class to overthrow the regimes (with the collusion the military).

And yet once the authoritarian rulers are gone the Islamists seem to have the liberals by the throat. In Egypt they wiped the floor with them in democratic elections. In Tunisia the Salafists are not quite so powerful, and the more moderate Islamists have to take into the account the opinions of the large secular liberal urban population, but the latter are now subjected to violence by religious fundamentalists. Naturally the Islamists wish to legalize polygyny in Tunisia.

People will focus on Syria because of the violence. Egypt because of the size. But Tunisia is the really informative case. If Tunisia can’t make liberal democracy work, there’s little hope for other Arab nations. On the other hand, if hopes don’t unravel, then at least it’s a start.

January 30, 2012

Out of who knows where

In The New York Times, DNA Turning Human Story Into a Tell-All:

The tip of a girl’s 40,000-year-old pinky finger found in a cold Siberian cave, paired with faster and cheaper genetic sequencing technology, is helping scientists draw a surprisingly complex new picture of human origins.

The new view is fast supplanting the traditional idea that modern humans triumphantly marched out of Africa about 50,000 years ago, replacing all other types that had gone before.

Instead, the genetic analysis shows, modern humans encountered and bred with at least two groups of ancient humans in relatively recent times: the Neanderthals, who lived in Europe and Asia, dying out roughly 30,000 years ago, and a mysterious group known as the Denisovans, who lived in Asia and most likely vanished around the same time.

Their DNA lives on in us even though they are extinct. “In a sense, we are a hybrid species,” Chris Stringer, a paleoanthropologist who is the research leader in human origins at the Natural History Museum in London, said in an interview.

First, for reasons of novelty we are emphasizing the exotic tendrils of the human family tree. Even Chris Stringer, the modern paleontological father of “Out of Africa,” is claiming we’re hybrids! But let’s not forget that non-Africans are the product of a very rapid radiation out of the margins of the Afrotropic ecozone within the last ~50-100,000 years. I am not entirely sure that this is as true of Africans (recall how extremely basal Bushmen are to the rest of humanity; they seem to have diverge well before the “Out of Africa” pulse).


Second, the old model was way easier to write about, even if there were confusions like the idea that mtDNA Eve was our only female ancestor from 200,000 years ago in the past. The new paradigm leaves one with awkward and unhelpful turns of phrase. For example:

But Dr. Reich and his team have determined through the patterns of archaic DNA replications that a small number of half-Neanderthal, half-modern human hybrids walked the earth between 46,000 and 67,000 years ago, he said in an interview. The half-Denisovan, half-modern humans that contributed to our DNA were more recent.

How to make sense of this gibberish? I suspect that the author didn’t have a good idea how to translate a particular population genetic statistic, and its importance to assessing time since admixture, into plainer prose. I have no idea either!

In other news, i09 has an interesting interview up with Rebecca Cann and Mark Stoneking. These two were heavily involved in the mtDNA Eve controversies of the 1980s. Nice capstone to an era. Like Stringer, even they admit the likelihood of a necessity to modify the simple “Out of Africa” with replacement model.

Monogamous societies superior to polygamous societies

Filed under: Anthroplogy,Culture,Group Selection — Razib Khan @ 9:14 pm


The title is rather loud and non-objective.  But that seems to me to be the upshot of Henrich et al.’s The puzzle of monogamous marriage (open access). In the abstract they declare that “normative monogamy reduces crime rates, including rape, murder, assault, robbery and fraud, as well as decreasing personal abuses.” Seems superior to me. As a friend of mine once observed, “If polygamy is awesome, how come polygamous societies suck so much?” Case in point is Saudi Arabia. Everyone assumes that if it didn’t sit on a pile of hydrocarbons Saudi Arabia would be dirt poor and suck. As it is, it sucks, but with an oil subsidy. The founder of modern Saudi Arabia was a polygamist, as are many of his male descendants (out of ~2,000). The total number of children he fathered is unknown! (the major sons are accounted for, but if you look at the genealogies of these Arab noble families the number of daughters is always vague and flexible, because no one seems to have cared much)

 

So how did monogamy come to be so common? If you follow Henrich’s work you will not be surprised that he posits “cultural group selection.” That is, the advantage of monogamy can not be reduced just to the success of monogamous individuals within a society. On the contrary, males who enter into polygamous relationships likely have a higher fitness than monogamous males within a given culture. To get a sense of what they mean by group selection I recommend you read this review of the concept by David B. A major twist here though is that they are proposing that the selective process operates upon cultural, not genetic, variation (memes, not genes). Why does this matter? Because inter-cultural differences between two groups in competition can be very strong, and arise rather quickly, while inter-group genetic differences are usually weak due to the power of gene flow. To give an example of this, Christian societies in Northern Europe adopted normative monogamy, while pagans over the frontier did not (most marriages may have been monogamous, but elite males still entered into polygamous relationships). The cultural norm was partitioned (in theory) totally across the two groups, but there was almost no genetic difference.  This means that very modest selection pressures can still work on the level of groups for culture, where they would not be effective for biological differences between groups (because those differences are so small) in relation to individual selection (within group variation would remain large).

From what I gather much of the magic of gains of economic productivity and social cohesion, and therefore military prowess, of a given set of societies (e.g., Christian Europe) in this model can be attributed to the fact of the proportion of single males. By reducing the fraction constantly scrambling for status and power so that they could become polygamists in their own right the general level of conflict was reduced in these societies. Sill, the norm of monogamy worked against the interests of elite males in a relative individual sense. Yet still, one immediately recalls that elite males in normatively monogamy societies took mistresses and engaged in serial monogamy. Additionally, there is still a scramble for mates among males in monogamous societies, though for quality and not quantity. These qualifications weaken the thesis to me, though they do not eliminate its force in totality.

In the end I am not convinced of this argument about group selection, though the survey of the empirical data on the deficiencies of societies which a higher frequency of polygamy was totally unsurprising.  I recall years ago reading of a Muslim male who wondered how women would get married if men did not marry more than once. He outlined how wars mean that there will always be a deficit of males! One is curious about the arrow of causality is here; is polygamy a response to a shortage of males, or do elite polygamist make sure that there is a shortage of males? (as is the case among Mormon polygamists in the SA)

Finally, I do not think one can discount the fact that despite the long term ultimate evolutionary logic, over shorter time periods other dynamics can take advantage of proximate mechanisms. For example, humans purportedly wish to maximize fitness via our preference for sexual intercourse. But in the modern world humans have decoupled sex and reproduction, and our fitness maximizing instincts are now countervailed by our conscious preference for smaller families. Greater economic production is not swallowed up by population growth, but rather greater individual affluence. This may not persist over the long term for evolutionary reasons, but it persists long enough that it is a phenomenon worth examining. Similarly, the tendencies which make males polygamous may exist in modern monogamous males, but be channeled in other directions. One could posit that perhaps males have a preference to accumulate status. In a pre-modern society even the wealthy usually did not have many material objects. Land, livestock, and women, were clear and hard-to-fake signalers to show what a big cock you had. Therefore, polygamy was a common cultural universal evoked out of the conditions at hand. Today there are many more options on the table. My point is that one could make a group selective argument for the demographic transition, but to my knowledge that is not particularly popular. Rather, we appeal to common sense understandings of human psychology and motivation, and how they have changed over the generations.

Addendum: When I say polygamy, I mean polygyny. I would say polygyny, but then readers get confused. Also, do not confuse social preference for polygyny with lack of female power. There are two modern models of polygynous societies, the African, and the Islamic. The Islamic attitude toward women shares much with the Hindu monogamist view, while in African societies women are much more independent economic actors, albeit within a patriarchal context. The authors note that this distinction is important, because it seems monogamy (e.g., Japan) is a better predictor of social capital than gender equality as such, despite the correlation.

Citation: Joseph Henrich, Robert Boyd, and Peter J. Richerson, The puzzle of monogamous marriage, Phil. Trans. R. Soc. B March 5, 2012 367 (1589) 657-669; doi:10.1098/rstb.2011.0290

Image credit: 1, 2, 3

Boycott Elsevier

Filed under: academia,Science and Society — Sean Carroll @ 8:56 am

While I have the blog open, let me throw in a quick two cents to support the Boycott Elsevier movement. As most working scientists know, Elsevier is a publishing company that controls many important journals, and uses their position to charge amazingly exorbitant prices to university libraries — and then makes the published papers very hard to access for anyone not at one of the universities. In physics their journals include Nuclear Physics, Physics Letters, and other biggies. It’s exactly the opposite of what should be the model, in which scientific papers are shared freely and openly.

So now an official boycott has been organized, and is gaining steam — if you’re a working scientist, feel free to add your signature. Many bloggers have chimed in, e.g. Cosma Shalizi and Scott Aaronson. Almost all scientists want their papers to be widely accessible — given all the readily available alternatives to Elsevier (including the new Physical Review X), all we need to do is self-organize a bit and we can make it happen.


Mind = Blown

Filed under: Entertainment,Music — Sean Carroll @ 8:37 am

Apologies that real work (to the extent that what I do can be called “work”) has gotten in the way of substantive blogging. But I cannot resist sharing the amazing things I learned this weekend — amazing to me, anyway, although it’s possible I’m the only one here who wasn’t clued in.

Thing the first is that Morgan Freeman, many years before he went through the wormhole, was a regular on The Electric Company, along with performers like Rita Moreno and Bill Cosby. (Via Quantum Diaries, of all places.) This was public television’s show from the 70′s that was meant for kids who had moved on from Sesame Street — I was more of a Zoom kid myself, but I must have seen Electric Company episodes with Freeman playing hip dude Easy Reader.

Thing the second is that Easy Reader’s theme song, sung in the clip above, is a dead ringer for Amy Winehouse’s “Rehab.” Flip back and forth between playing them if you don’t believe me. So much so, I am told, that DJ’s in clubs will sometimes mix the two tunes together. Not at the clubs I go to, I guess.


January 29, 2012

Most people don’t understand “heritability”

Filed under: Heritability,Quantitative Genetics — Razib Khan @ 1:08 pm

According to the reader survey 88 percent said they understood what heritability was. But only 34 percent understood the concept of additive genetic variance. For the purposes of this weblog it highlights that most people don’t understand heritability, but rather heritability. The former is the technical definition of heritability which I use on this weblog, the latter is heritability in the colloquial sense of a synonym for inheritance, biological and cultural. Almost everyone who understands the technical definition of heritability will know what heritability in the ‘narrow sense’ is, often just informally termed heritability itself. It is the proportion of phenotype variability that can be attributed to additive genetic variation. Those who understand additive genetic variance and heritability in the survey were 32 percent of readers. If you understand heritability in the technical manner you have to understand additive genetic variance. This sets the floor for the number who truly understand the concept in the way I use on this weblog (I suspect some people who were exceedingly modest who basically understand the concept for ‘government purposes’ put themselves in the ‘maybe’ category’). After nearly 10 years of blogging (the first year or so of which I myself wasn’t totally clear on the issue!) that’s actually a pretty impressive proportion. You take what you can get.

January 28, 2012

Socialized medicine + personal genomics = ?

Filed under: Genomics,Personal genomics — Razib Khan @ 7:02 pm

My own working assumption is that the demand side impulse toward mass adoption of human genomic technology in the USA is going to be dampened by fear of downside consequences, GINA notwithstanding. Rather, I assume that the more deregulated consumer environment in parts of Asia with very low fertility rates, as well as European states with more thorough socialized medical systems, will “punch above their weight” in this domain. It looks likes a genuine socialized medical system (i.e., the doctors are state employees), that of the UK, is preparing to step up to the plate, Genomic innovation will better target treatment in the NHS:

The independent cross-government advisory group was set up in response to the 2009 House of Lords report on genomic medicine. It draws on expertise from across Government and research institutes and makes six recommendations to Government:

The recommendations are:

• to develop a cross-cutting strategic document, to set out the direction on genomic technology adoption in the NHS;

• to develop a national central genomic data storage facility;

• that the NHS Commissioning Board should lead on developing genomic technology adoption;

• to work to develop a service delivery model for genomic technologies;

• that the NHS should continue to develop genomics education and training; and

• to raise public awareness of genomic technology and its benefits.

Many researchers believe that personal genomics will really not hit the biomedical sweet spot until you have on the order of a million people sequenced. But even then in the American system how to get a hold of all that information is going to be problematic, since it will likely be decentralized. In contrast in Britain tens of millions of people have one primary healthcare provider, their national government.

You can read the full report online (PDF). Like the “rise of China,” the “rise of genomics,” was one of those futurist predictions. Until now. It’s ridiculous to talk about the rise of something which has risen. Now it’s about maturity and ripening.

Population structure using haplotype data

The Pith: New software which gives you a more fine-grained understanding of relationships between populations and individuals.

According to the reader survey >50 percent of you don’t know how to interpret PCA or model-based (e.g., ADMIXTURE) genetic plots, so I am a little hesitant to point to this new paper in PLoS Genetics, Inference of Population Structure using Dense Haplotype Data, as it extends the results of those earlier methods. But it’s an important paper, and at some point I’ll starting using their software. The “big picture” is that earlier methods left “some information on the table.” That’s partly due to the fact that they were developed (or in the case of PCA leveraged, as it’s a very general technique) in an era where very dense marker data sets were not available (today we’re shifting to full genome sequences in many cases!). The information left on the table would be haplotype structure. Genetic variation in a concrete form manifests as sequences along a line, many of them physically connected. These correlations of nearby variant markers represent haplotypes of great interest, because they are excellent clues to admixture or divergence events across populations. In contrast the older methods, were looking at variation from marker to marker, each in turn independently, which collapses some of the important genomic structure that we can now inspect (in fact, linkage disequilibrium due to these correlations can distort some of the results in the older methods, so you want to “thin” your marker set).

Let me make this concrete for you. On 23andMe you can see where your friends shake out on a PCA plot using the HGDP data set as a reference. What this means is that the HGDP data set is used to generate independent dimensions of genetic variation. As is the usual case in these analyses the largest dimension separates Africans from everyone else, and the second largest dimension separates Asians from Europeans and Africans. 23andMe customers are then projected upon this variation, so you can get a sense where you are positioned in the clusters. To the left is a zoom in on the section for Central/South Asians. You can see that one of my friends, highlighted with a green color, falls almost perfectly in the Uygur cluster. According to ancestry estimates my friend is 50 percent Asian and 50 percent European. The “representative” Uygur in the 23andMe chromosome painting gives about the same results. But these are total genome estimates. The historical nature of my friend’s admixture and that of the Uygur woman is very different, as one can see in the below figure.

 

My friend is to the right, and the Uygur woman is to the left. Why the big difference? My friend has an East Asian parent an a European parent. The Uygur woman is the product of a marriage between Uygurs, a population which is due to admixture betwen East Asians and Europeans one to two thousand years ago. Recombination has broken apart the perfect linkage between European and East Asian regions among the Uygurs. Obviously this isn’t the case with my friend, as recombination has had no time to generate alternative sequences of ancestry. This is critical information which genome-wide estimates displayed on PCA or ADMIXTURE will miss out on.

As for this particular paper and method, I want to point you to figure 5. The darker/bluish colors indicate higher conancestry estimates, and yellower colors lower ones. Red is in the middle. The diagonal tends to be blue/red because that represents populations’ correlations with themselves, which one would expect to be high. You can’t really read the labels, but  I wanted to highlight the Italian and Sardinian blocks. Explanation below.

You can see an ADMIXTURE plot underneath the heat-map. What’s going on? Sardinians exhibit the hallmarks of an isolated population with smaller effective population which has undergone more genetic drift than Italians over the same amount of time. This is naturally one reason that they “break out” rather quickly in ADMIXTURE and PCA. You see this in South Asia with the Kalash, who often emerge as their own cluster rather quickly, and separate out in a PCA as well. This is simply a function of their isolation and lower effective population size. Most of the people who use ADMIXTURE and PCA know this, but those reading these plots do not. Without that knowledge one can make incorrect inferences. The methods outlined here in the paper allow one to visually observe immediately these trends, while keeping in place broader wold-wide correlations across populations in mind. This is a big step forward not only in data analysis, but result visualization.

If you are more interested in this topic, the first author has a comparison of the various tools up. Both Dienekes and Eurogenes are using the new software. Get the software at PaintMyChromosomes.com!

Citation: Lawson DJ, Hellenthal G, Myers S, Falush D (2012) Inference of Population Structure using Dense Haplotype Data. PLoS Genet 8(1): e1002453. doi:10.1371/journal.pgen.1002453

Social conservatives have a lower I.Q.? (probably)

Filed under: conservative,Culture,I.Q.,Intelligence,Liberalism,Politics — Razib Khan @ 1:29 pm

In light of my previous posts on GRE scores and educational interests (by the way, Education Realist points out that the low GRE verbal scores are only marginally affected by international students) I was amused to see this write-up at LiveScience, Low IQ & Conservative Beliefs Linked to Prejudice. Naturally over at Jezebel there is a respectful treatment of this research. This is rather like the fact that people who would otherwise be skeptical of the predictive power of I.Q. tests become convinced of their precision of measurement when it comes to assessing whether a criminal facing the death penalty is mentally retarded or not! (also see this thread over at DailyKos). You can see some of the conservative response too.

The paper itself is Bright Minds and Dark Attitudes: Lower Cognitive Ability Predicts Greater Prejudice Through Right-Wing Ideology and Low Intergroup Contact:

Despite their important implications for interpersonal behaviors and relations, cognitive abilities have been largely ignored as explanations of prejudice. We proposed and tested mediation models in which lower cognitive ability predicts greater prejudice, an effect mediated through the endorsement of right-wing ideologies (social conservatism, right-wing authoritarianism) and low levels of contact with out-groups. In an analysis of two large-scale, nationally representative United Kingdom data sets (N = 15,874), we found that lower general intelligence (g) in childhood predicts greater racism in adulthood, and this effect was largely mediated via conservative ideology. A secondary analysis of a U.S. data set confirmed a predictive effect of poor abstract-reasoning skills on antihomosexual prejudice, a relation partially mediated by both authoritarianism and low levels of intergroup contact. All analyses controlled for education and socioeconomic status. Our results suggest that cognitive abilities play a critical, albeit underappreciated, role in prejudice. Consequently, we recommend a heightened focus on cognitive ability in research on prejudice and a better integration of cognitive ability into prejudice models.

I emphasized sections that I assume will answer some immediate questions, as not everyone has access to Psychological Science. Yes, they used different types of intelligence tests; verbal and spatial. Yes, they corrected for socioeconomic background. Their replication was in the UK and USA. Importantly, they focused on a few characteristics, attitudes toward homosexuals and race. It doesn’t seem like they explored an enormous range of opinions. And as noted in the paper they were looking at the social dimension of political ideology.

There is plenty of work on cognitive styles and political orientation. Recently it is moral foundations from Jon Haidt. Earlier you had George Lakoff’s models. Neither of these focused on general intelligence, the raw CPU power of the mind. Rather they surveyed moral intuition and personality profiles (for example, there is some evidence that those with a greater bias toward “openness” are more socially liberal).

Looking at the General Social Survey I too have found at a correlation between higher intelligence and social liberalism. On the other hand a good objection to this is that my estimator of intelligence, WORDSUM, was verbal, and liberals and conservatives may exhibit different cognitive profiles. This study takes that into account, adding spatial I.Q. tests to the mix.

It is important to emphasize that the authors do not posit an independent direct causal connection between low I.Q. and more reactionary attitudes towards race and homosexuality. Rather, they start out with a model where low cognitive ability people are drawn (or remain in) to conservative orientation, and this is further correlated with these specific racial and sexual attitudes. Like almost all psychology you can’t get the causation airtight (if you are a hardcore Humean you could probably say this for everything), but the correlation is suggestive in light of political and psychological models. The problem is the second. As Jonathan Haidth has articulated most recently most academic political scientists and psychologists have strongly social liberal views, and so they consciously or unconsciously tend to caricature and misrepresent the views of half their study population (notice that the authors assume that these socially conservative positions are ‘Dark Attitudes’; most people today would agree, but shouldn’t intellectuals avoid this sort of thing?). So though I have some confidence in the correlations, I’m a lot more skeptical of the explanatory models (though I don’t reject them out of had). There are so many models sitting around that how you chose models can be shaped by bias rather easily.

First, let’s hit the results.

The table above represents the results for the British cohorts and race, and the diagram to the left illustrates the outcome for the American sample and homosexuality. The primary point is that as per their hypothesis the effect of lower cognitive ability on prejudice toward other races and homosexuality is mediated more or less through ideology. Coarsely, stupid people aren’t racist, stupid people are more likely to be socially conservative, and more socially conservative people are more likely to be racist. How these join together though is something one can subject to more critical examination. The authors allude to this when they note that there is a finding that those who know people of other races tend to be less prejudiced, with the inference being that contact makes one less racist. But this is not an established causality. Rather, it could be that people with less prejudiced tendencies put themselves into situations where they are likely to meet other races. This tendency could be correlated with higher I.Q. through a mediation of a “cosmopolitanism index.” Who knows? There are many stories one could tell.

I do want to emphasize though that this is a coarse measure of ‘conservatism.’ In the early to mid aughts Paul Wolfowitz was a hated figure on the American political Left because of his critical role in buttressing the intellectual armamentarium favoring the invasion of Iraq. But it is well known that Wolfowitz was and is a social liberal, like a subset of neoconservatives who focus on foreign policy. On the above measure Wolfowitz, who has undergraduate degrees in mathematics and chemistry from Cornell and a graduate degree in political science from University of Chicago, would come out as a high I.Q. social liberal. Is that right? As far as it goes it is right, but on some level the results would be misleading in the more complex terrain of coalitional politics. A substantial number of Americans shake out as social conservatives and fiscal moderates/liberals. And yet this faction is totally unrepresented in modern politics. In contrast, their inverse, libertarians, do have some representation, albeit a marginalized one. Why? Because the latter position has modest high I.Q./elite support, while the former position has far less. If you changed the question to attitudes toward global free trade there would be a correlation between lower I.Q. and the ‘more liberal’ (at last in American politics) position.

This qualification also dovetails with the broader point about styles of cognitive thinking, and reliance on traditional norms as opposed to think a priori. Ironically it makes intuitive sense that higher I.Q. people would be less reliant on intuition, impulse, and collective wisdom. But there are limits to this. For example, see the reaction to the proposition of sex between consenting adults who happen to be siblings on an atheism forum (assume they use birth control). But some moral philosophers posit that this is not harmful or immoral, and should be socially accepted. It’s an interesting illustration of the boundary condition of the power of disgust and emotion, as only the hyper-rational feel comfortable even entertaining the moral legitimacy of this proposition. More relevantly, educated liberals also make use of ‘stereotypes’ constantly. It’s just that those stereotypes are of conservatives. I know this because almost all my friends are educated liberals, and they often forget that I’m a conservative. So I hear a lot about conservatives are this and that without qualification, to great merriment and laughter (also, conservatives are genuinely evil and malevolent apparently!). The tendency toward generalization doesn’t bother me in an of itself, rather, I’m focused on whether the proposition is true. But the hypocrisy gets tiresome sometimes, as people will fluidly switch from a cognitive style which accepts generalization to one which rejects it. A stereotype is often a generalization whose robustness you don’t want to accept. Negative generalities need context when they’re unpalatable, but no qualification is necessary when their truth is congenial. Sometimes this veers into moderately politically incorrect territory. I was once an observer on a conversation between liberal white academics who were mulling over the unfortunate reality that their Asian American students were far more likely to cheat to obtain better grades. I suspect that this is actually true for various reasons. But I also suspect that these academics forgot that I was privy to the conversation, and wouldn’t have aired this truth in a more racially diverse social context.

More broadly what is the takeaway from this sort of research? Should we conclude that because the more intelligent tend to be socially liberal that socially liberal propositions are true? I think one should be skeptical of this position. There are two immediate rejoinders. First, politics is a matter of values. The reliance of reason vs. emotion, individual ratiocination vs. historical or social wisdom, may vary. But that does not speak to the truth of any given value judgement, as those judgments are embedded in a system of norms, as well as individual self-interest (e.g., the higher I.Q. tendency to favorable attitudes toward free trade may have less to do with an understanding of comparative advantage, than an implicit understanding that globalization favors them as opposed to less intelligent lower classes). Second, the moral arc of history is not always unidirectional. The ‘progressive’ position is sometimes reversed. In Better for All the World there is a broad history of the rise of a consensus among economic and intellectual elites about the wisdom of coercive eugenics as an instrument of progressive social engineering in the late 19th century. Religious conservatives, whether evangelical Protestant or Roman Catholic, were two of the greatest bulwarks against this force for progress. Arguably these two elements were more efficacious in resisting the spread of eugenics legislation than the Left critics, judging by the outcomes Southern Europe and the American South, as opposed to the more ‘forward thinking’ nation-states of Northern Europe and the American North. This fact is unknown to most of my friends and acquaintances, judging by repeated assumptions that any utilization of personal genomics for eugenic purposes will occur first in politically conservative jurisdictions.

With all these qualifications, I believe this sort of research is essential and insightful. We need to understand the patterns of cognitive variation, whether it be intelligence or personality, which may result in differences of opinion. At the end of the day no opinions may change, but one may be able to construct a crisper argument when taking into account the genuine roots of one’s political opponents viewpoints, rather than your own ill-informed caricature.

Addendum: I did not address the issue of revealed vs. avowed preferences and attitudes. But I think that this difference will not change the sign of correlation. For example, for various reasons I assume that the gap between white liberals and white conservatives when it comes to race is smaller in terms of the preference revealed in their choices, rather than the survey responses they give, but I don’t think it reverses the rank order of the correlation.

Citation: Bright Minds and Dark Attitudes: Lower Cognitive Ability Predicts Greater Prejudice Through Right-Wing Ideology and Low Intergroup Contact, Psychol Sci. 2012 Jan 5.

Sikhs being dumbasses

Filed under: Uncategorized — Razib Khan @ 12:34 am

Jay Leno & NBC Sued Over Mitt Romney Joke:

Dr. Randeep Dhillon of Bakersfield filed the suit today in Los Angeles Superior Court. On behalf of himself and Bol Punjabi All Regions Community Organization, the suit charges that the broadcast was libelous on its face and exposed Sikhs and their religion to hatred, contempt and ridicule because it portrayed the holiest place in the Sikh religion as a vacation resort owned by a non-Sikh. The suit charges that Leno’s use of the photo of the temple was intentional, deliberately false and “hurt the sentiments of all Sikh people in addition to those of the plaintiff.” The suit seeks general, special and punitive damages as well as court costs. It appears that video of the segment in question has been removed from NBC’s website.

Remember, this is the same religion which prompted believers to riot in England to shut down a play which they considered blasphemous. A disproportionate number of migrants in the Indian Diaspora are Punjabi Sikhs for what it’s worth. They’ve committed multiple acts of terrorism in Canada.

January 27, 2012

Friday Fluff, 01/27/2012

Filed under: Blog,Friday Fluff,Katz — Razib Khan @ 4:32 pm

They’re bbbaaaccckkkk!

Out of Africa and out of Siberia

The latest edition of The American Journal of Human Genetics has two papers using “old fashioned” uniparental markers to trace human migration out of Africa and Siberia respectively. I say old fashioned because the peak novelty of these techniques was around 10 years ago, before dense autosomal SNP marker analyses, let alone whole genome sequencing. But mtDNA, passed down the maternal line, and Y chromosomes, passed from father to son, are still useful. Prosaically they’re useful because the data sets are now so large for these sets of markers after nearly 20 years of surveying populations. More technically because these two regions of the genome do not recombine they lend themselves to excellent representation as a tree phylogeny. Finally, mtDNA in particular is particularly amenable to estimates via molecular clock methodologies (it has a region with a higher mutational rate, so you can sample a larger range of variation over a given number of base pairs; you can use STRs, which mutate rapidly, for Y chromosomes, but there seems to be a lot of controversy in dating).

The papers are The Arabian Cradle: Mitochondrial Relicts of the First Steps along the Southern Route out of Africa and Mitochondrial DNA and Y Chromosome Variation Provides Evidence for a Recent Common Ancestry between Native Americans and Indigenous Altaians. Dienekes has already commented on the first paper. I am not going to take a detailed position on either, but I have to add that we need to be very careful of extrapolating from maternal or paternal lineages, and, assuming that population turn over is low enough that we can make phylogeographic inferences about the past from the present. For example, if you look at mtDNA South Asians as a whole strongly cluster with East Asians and not Europeans, while if you look at Y chromosomes you see the reverse. The whole genome gives a more mixed picture. Additionally, ancient DNA analyses in Northern Eurasia are showing strong discontinuities between past and present populations. So coalescence back to last common ancestor between two different lineages in two different regions may actually be due to diversity in a common source population more recently, which entered into demographic expansion and replaced other groups.

If you need the papers, email me. Some of you know the alphabet soup of haplogroups better than I do. Below are two figures which I think give the top line results.

January 26, 2012

1 migrant needed to prevent genetic divergence

Filed under: 1 migrant rule,Conservative Genetics,Population genetics — Razib Khan @ 2:09 am

In the survey below I asked if you knew about how many migrants per generation were needed to prevent divergence between populations. About ~80 percent of you stated you did not know the answer. That was not totally surprising to me. The reason I asked is that the result is moderately obscure, but also rather surprisingly simple and fruitful. The rule of thumb is that 1 migrant per generation is needed to prevent divergence.*

It doesn’t tell you much in and of itself of course. But if you think about it you can inject that fact into all sorts of other population genetic phenomena. For example, to have selection across two populations which is not reducible to selection within those populations (i.e., inter-demic selection) you need group-level genetic differences. These differences can be measured by the Fst statistic. In short the value of Fst tells you the proportion of variation which can be attributed to between-group differences (e.g., Fst across human races is ~0.15). For natural selection to have any adaptive effect you also need heritable variation. If you have lots of heritable variation selection can be weaker, while if you have little heritable variation selection has to be very strong (see response to selection). Fst is a rough gauge of heritable variation when you are evaluating group level differences. An Fst of 1.0 would imply that the groups are nearly perfectly distinct at the loci of interest, while an Fst of 0.0 would imply that the groups are not genetically distinct at all. With no distinction selection would have no efficacy in terms of driving adaptation. All this is a long way to saying that the 1 migrant rule is one reason that evolutionary biologists take a skeptical position in relation to group selection. It tends to quickly erase the variation which group selection depends upon.

 

To make it concrete here is the equation which you use to generate the equilibrium F statistic:

In this formula N = the population size, and m = the proportion of migrants within the population within a given generation. Nm then works out to be the number of migrants in any given generation. So 1 migrant per generation would mean for 1,000 individuals m = 0.001. For 100, the m = 0.01. To see the power of a given number of migrants per generation on long term Fst, the measure of between population difference, I’ve plotted some computed results below (Fst y-axis, Nm on the x-axis).

 

This should make intuitive sense. If there is no migration (gene flow) between populations then over the long term they become perfectly distinct. As you increase migration naturally that is going to homogenize differences between populations. But I suspect the question you may still have is how is it that only a few individuals are necessary in even large populations to prevent differentiation?

Here the intuition is simple. In a neutral scenario between-population differences emerge as gene frequencies change over time. The generation to generation change is inversely proportional to population. This is simply the sample variance or transmission noise. The expected deviation is going to be proportional to 1/N, where N is the population (2N for diploid). As N gets rather large you converge upon zero. So as the population gets very large there is less and less divergence which may occur in one given generation. In contrast you have a lot of generation to generation variation, and rapid change in frequency, in a small population. So why only 1 migrant? In a large population 1 migrant does not effect much change, but much change is not necessary. In a small population it has much more impact, but the generation to generation change is also much bigger. These two dynamics work at cross purposes so that the number of migrants needed remains relatively insensitive to population size.

* This is the result derived from population genetics, some ecological geneticists have made the case that you may actually need 10 migrants, 1 being the lower boundary.

Image credit: Wikipedia

January 25, 2012

Born to conform

Filed under: Culture,Evolution,Group Selection — Razib Khan @ 11:52 am

There is a new paper in Nature, Social networks and cooperation in hunter-gatherers, which is very interesting. As Joe Henrich observes in his view piece the panel of figure 2 (see left) is probably the most important section.

The study focuses on the Hadza, a hunter-gatherer population of Tanzania. Their language seems to be an isolate, though there have been suggestions of a connection to Khoisan. Additionally the genetic evidences tells us that like the Bushmen and Pygmies the Hadza do descend from populations which are basal to other human lineages, and were likely resident in their homeland before the arrival of farmers. And it is critical to also note that the Hadza are probably uninterrupted hunter-gatherers in terms of the history of their lifestyle, as agriculture likely arrived in Tanzania on the order of two thousand years ago, and their genetic distinctiveness indicates a separation from groups like Bantus far deeper in time. When it comes to Paleolithic model populations the Hadza are relatively “uncontaminated.”

So how does 2a matter? It shows a sharp discontinuity in cooperation across Hadza camps, all things controlled. There have been debates about the level of analysis necessary to explain human cooperation, with reductionists focused on the individual, arguing that dynamics such as kin selection and reciprocal altruism can explain the complexity we see around us simply through extension (e.g., universalist religious ideologies and philosophies usually appeal to fictive kinship or the golden rule). These data instead given some support to models which posit that group-level cultural dynamics must also be taken into account. Remember though that these more complicated systems don’t deny the importance of kin selection and reciprocal altruism; they only posit that there are other forces which can’t easily be reduced to these two.

The peculiarity of figure 2a illustrates the difference between transmission of culture, memes, and biology, genes. The Hadza are a small population, and genetically rather homogeneous in relation to their neighbors (to my knowledge they don’t exhibit much population substructure). It is difficult for between group variance to develop between human populations with adjacent residence patterns because even small amounts of migration rapidly equilibrate gene frequencies. This is why biologists have traditionally been skeptical of selection across groups. If the two entities are nearly clonal (because the groups do not differ much) then evolution by natural selection can not operate across the groups (remember, being clonal at the scale of the group does not mean there isn’t variation within groups, so selection still operates, just at a “lower” scale). But human culture is very different. Novel groups with their own distinctive cues can emerge very rapidly, and generate horizontal networks of affinity. Sometimes, as with accents, it is rather difficult for outsiders to a group to mimic and deceive because of a biologically “critical period” of enculturation (this might also be the role that radical body modification plays in a functional sense; it’s a difficult-to-fake identity marker, often irreversible).

That’s the theory. The main problem with these group-level models is that there’s always a lot of talk (theory), but a lot less empirical data. Hopefully that will change. The paper used a lot of experimental methods, and these are probably the way to go. Obviously you can’t put people in life or death situations, but you can at least discern general and specific patterns cross-culturally. And are these canned “games” any less valid than surveys to the WEIRD set?

Citation: Social networks and cooperation in hunter-gatherers, doi:10.1038/nature10736

Image credit: Wikipedia

Classicists are smart!

Filed under: Data Analysis,GRE,Intelligence,Social Science — Razib Khan @ 4:15 am

The post below on teachers elicited some strange responses. Its ultimate aim was to show that teachers are not as dull as the average education major may imply to you. Instead many people were highly offended at the idea that physical education teachers may not be the sharpest tools in the shed due to their weak standardized test scores. On average. It turns out that the idea of average, and the reality of variation, is so novel that unless you elaborate in exquisite detail all the common sense qualifications, people feel the need to emphasize exceptions to the rule. For example, over at Fark:

Apparently what had happened was this: He played college football. He majored in math, minored in education. When he went to go get a job, he took it as a math teacher. When the football coach retired/quit, he took over. When funding for an advance computer class was offered, he said he could teach it after he got the certs – he easily got them within a month.

So the anecdote here is a math teacher who also coached. Obviously the primary issue happens to be physical education teachers who become math teachers! (it happened to me, and it happened to other readers apparently) In the course of double checking the previous post I found some more interesting GRE numbers. You remember the post where I analyzed and reported on GRE scores by intended graduate school concentration? It was a very popular post (for example, philosophy departments like it because it highlights that people who want to study philosophy have very strong GRE scores).

As it happens the table which I reported on is relatively coarse. ETS has a much more fine-grained set of results. Want to know how aspiring geneticists stack up against aspiring ecologists? Look no further! There are a lot of disciplines. I wanted to focus on the ones of interest to me, and I limited them to cases where the N was 100 or greater (though many of these have N’s in the thousands).

You’re going to have to click the image to make out where the different disciplines are. But wait! First I need to tell you what I did. I looked at the average verbal and mathematical score for each discipline. Then I converted them to standard deviation units away from the mean. This is useful because there’s an unfortunate compression and inflation on the mathematical scores. Disciplines which are stronger in math are going to have a greater average because the math averages are higher all around. You can see that I divided the chart into quadrants. There are no great surprises. People who want to pursue a doctorate in physical education are in the bottom left quadrant. Sorry. As in my previous post physicists, economists, and philosophers do rather well. But there were some surprises at the more detailed scale. Historians of science, and those graduate students who wish to pursue classics or classical languages are very bright. Budding historians of science have a relatively balanced intellectual profile, and the strongest writing scores of any group except for philosophers. I think I know why: many of these individuals have a science background, but later became interested in history. They are by nature relatively broad generalists. I have no idea why people drawn to traditionally classical fields are bright, but I wonder if it is because these are not “sexy” domains, to the point where you have to have a proactive interest in the intellectual enterprise.

I also wanted to compare aggregate smarts to intellectual balance. In the plot to the right on the x-axis you have the combined value of math and verbal scores in standard deviation units. A negative value indicates lower values combined, and a positive value higher. Obviously though you can have a case where two disciplines have the same average, but the individual scores differ a lot. So I wanted to compare that with the difference between the two scores. You can see then in the plot that disciplines like classics are much more verbal, while engineering is more mathematical. Physical scientists tend to be more balanced and brighter than engineers. Interestingly linguists have a different profile than other social scientists, and cognitive psych people don’t cluster with others in their broader field. Economists are rather like duller physicists. Which makes sense since many economists are washed out or bored physicists. And political science and international relations people don’t stack up very well against the economists. Perhaps this is the source of the problem whereby economists think they’re smarter than they are? Some humility might be instilled if economics was always put in the same building as physics.

In regards to my own field of interest, the biological sciences, not too many surprises. As you should expect biologists are not as smart as physicists or chemists, but there seems to be two clusters, with a quant and verbal bias. This somewhat surprised me. I didn’t expect ecology to be more verbal than genetics! And much respect to the neuroscience people, they’re definitely the smartest biologists in this data set (unless you count biophysicists!). I think that points to the fact that neuroscience is sucking up a lot of talent right now.

The main caution I would offer is that converting to standard deviation units probably means that I underweighted the mathematical fields in their aptitudes, because such a large fraction max out at a perfect 800. That means you can’t get the full range of the distribution and impose an artificial ceiling. In any case, the raw data in the table below. SDU = standard deviation units.

 

Field V-mean M-mean V-SDU M-SDU Average-SDU Difference-SDU
Anatomy 443 568 -0.16 -0.11 -0.13 -0.05
Biochemistry 486 669 0.20 0.56 0.38 -0.36
Biology 477 606 0.13 0.15 0.14 -0.02
Biophysics 523 727 0.51 0.95 0.73 -0.43
Botany 513 626 0.43 0.28 0.35 0.15
Cell & Mol Bio 497 658 0.29 0.49 0.39 -0.20
Ecology 535 638 0.61 0.36 0.49 0.26
Develop Bio 490 623 0.24 0.26 0.25 -0.02
Entomology 505 606 0.36 0.15 0.25 0.22
Genetics 496 651 0.29 0.44 0.36 -0.16
Marine Biology 499 611 0.31 0.18 0.24 0.13
Microbiology 482 615 0.17 0.21 0.19 -0.04
Neuroscience 533 665 0.60 0.54 0.57 0.06
Nutrition 432 542 -0.25 -0.28 -0.27 0.03
Pathology 468 594 0.05 0.07 0.06 -0.02
Pharmacology 429 634 -0.28 0.33 0.03 -0.61
Physiology 464 606 0.02 0.15 0.08 -0.13
Toxicology 465 610 0.03 0.17 0.10 -0.15
Zoology 505 609 0.36 0.17 0.26 0.20
Other Biology 473 626 0.09 0.28 0.19 -0.19
Chemistry, Gen 483 681 0.18 0.64 0.41 -0.47
Chemistry, Analytical 464 652 0.02 0.45 0.23 -0.43
Chemistry, Inorganic 502 690 0.34 0.70 0.52 -0.37
Chemistry, Organic 490 683 0.24 0.66 0.45 -0.42
Chemistry, Pharm 429 647 -0.28 0.42 0.07 -0.69
Chemistry, Physical 513 708 0.43 0.82 0.62 -0.39
Chemistry, Other 477 659 0.13 0.50 0.31 -0.37
Computer Programming 407 681 -0.46 0.64 0.09 -1.10
Computer Science 453 702 -0.08 0.78 0.35 -0.86
Information Science 446 621 -0.13 0.25 0.06 -0.38
Atmospheric Science 490 673 0.24 0.59 0.41 -0.35
Environ Science 493 615 0.26 0.21 0.23 0.06
Geochemistry 514 657 0.44 0.48 0.46 -0.05
Geology 495 625 0.28 0.27 0.27 0.01
Geophysics 487 676 0.21 0.61 0.41 -0.40
Paleontology 531 621 0.58 0.25 0.41 0.33
Meteology 470 663 0.07 0.52 0.30 -0.46
Epidemiology 485 610 0.19 0.17 0.18 0.02
Immunology 492 662 0.25 0.52 0.38 -0.26
Nursing 452 531 -0.08 -0.35 -0.22 0.27
Actuarial Science 460 726 -0.02 0.94 0.46 -0.96
Applied Math 487 730 0.21 0.97 0.59 -0.76
Mathematics 523 740 0.51 1.03 0.77 -0.52
Probability & Stats 486 728 0.20 0.95 0.58 -0.75
Math, Other 474 715 0.10 0.87 0.48 -0.77
Astronomy 525 706 0.53 0.81 0.67 -0.28
Astrophysics 540 727 0.66 0.95 0.80 -0.29
Atomic Physics 522 739 0.50 1.03 0.77 -0.52
Nuclear Physicsl 506 715 0.37 0.87 0.62 -0.50
Optics 495 729 0.28 0.96 0.62 -0.68
Physics 540 743 0.66 1.05 0.85 -0.40
Planetary Science 545 694 0.70 0.73 0.71 -0.03
Solid State Physics 514 743 0.44 1.05 0.74 -0.62
Physics, Other 519 723 0.48 0.92 0.70 -0.44
Chemical Engineering 490 729 0.24 0.96 0.60 -0.72
Civil Engineering 456 705 -0.05 0.80 0.38 -0.85
Computer Engineering 465 716 0.03 0.87 0.45 -0.85
Electrical Engineering 465 722 0.03 0.91 0.47 -0.89
Industrial Engineering 426 699 -0.30 0.76 0.23 -1.06
Operations Research 483 743 0.18 1.05 0.61 -0.88
Materials Science 509 728 0.39 0.95 0.67 -0.56
Mechanical Engineering 471 721 0.08 0.91 0.49 -0.83
Aerospace Engineering 498 725 0.30 0.93 0.62 -0.63
Biomedical Engineering 504 717 0.35 0.88 0.62 -0.53
Nuclear Engineering 500 720 0.32 0.90 0.61 -0.58
Petroleum Engineering 414 676 -0.40 0.61 0.10 -1.01
Anthropology 532 562 0.59 -0.15 0.22 0.73
Economics 508 707 0.39 0.81 0.60 -0.43
International Relations 531 588 0.58 0.03 0.30 0.55
Political Science 523 574 0.51 -0.07 0.22 0.58
Clinical Psychology 484 554 0.18 -0.20 -0.01 0.38
Cognitive Psychology 532 627 0.59 0.28 0.44 0.30
Community Psychology 441 493 -0.18 -0.60 -0.39 0.43
Counseling Psychology 444 500 -0.15 -0.56 -0.35 0.41
Developmental Psychology 476 563 0.12 -0.14 -0.01 0.26
Psychology 476 546 0.12 -0.25 -0.07 0.37
Quantitative Psychology 515 629 0.45 0.30 0.37 0.15
Social Psychology 518 594 0.47 0.07 0.27 0.40
Sociology 490 541 0.24 -0.28 -0.02 0.52
Criminal Justice/Criminology 418 477 -0.37 -0.71 -0.54 0.34
Art history 536 549 0.62 -0.23 0.20 0.85
Music History 536 596 0.62 0.08 0.35 0.54
Drama 514 541 0.44 -0.28 0.08 0.72
Music History 490 559 0.24 -0.17 0.03 0.40
Creative Writing 553 540 0.76 -0.29 0.24 1.06
Classical Language 619 633 1.32 0.32 0.82 0.99
Russian 584 611 1.03 0.18 0.60 0.85
American History 533 541 0.60 -0.28 0.16 0.88
European History 554 555 0.77 -0.19 0.29 0.97
History of Science 596 661 1.13 0.51 0.82 0.62
Philosophy 591 630 1.08 0.30 0.69 0.78
Classics 609 616 1.24 0.21 0.72 1.02
Comp Lit 591 588 1.08 0.03 0.56 1.06
Linguistics 566 630 0.87 0.30 0.59 0.57
Elementary Education 438 520 -0.20 -0.42 -0.31 0.22
Early Childhood Education 420 497 -0.35 -0.58 -0.46 0.22
Secondary Education 484 576 0.18 -0.05 0.07 0.24
Special Education 424 497 -0.32 -0.58 -0.45 0.26
Physical Education 389 487 -0.61 -0.64 -0.63 0.03
Finance 466 721 0.03 0.91 0.47 -0.87
Business Adminstraiton 434 570 -0.24 -0.09 -0.16 -0.14
Communication 458 517 -0.03 -0.44 -0.24 0.41
Theology 537 583 0.63 -0.01 0.31 0.64
Social Work 428 463 -0.29 -0.80 -0.54 0.52

January 24, 2012

Unsolicited Advice XIII: How to Craft a Well-Argued Proposal

Filed under: Advice,proposals,unsolicited advice — Julianne Dalcanton @ 11:55 pm

In almost any project, the path between “a good idea” and the “final exciting result” contained a proposal. It may have been a proposal to obtain access to scarce resources (like telescopes or accelerator beams), or it may be have been a proposal to obtain other more prosaic resources (i.e., money, to pay for the needed personnel and supplies). Whatever the nature of the proposal, however, I guarantee that the competition was ridiculously stiff, and that the odds of having any given proposal accepted were quite low (for reference, in most astronomy contexts, over-subscription rates tend to be factors of 5-10). These unfavorable odds can be incredibly demoralizing. They also can have profoundly negative impacts on a talented scientist’s career, if the odds never manage to tip in their favor.

Given the inspiration of the looming Hubble Space Telescope deadline, I thought I would share some of my “big picture” views on crafting successful proposals, expanding significantly on the more succinct advice given in an earlier post. While I’ve developed these opinions based on my experience in astronomy, I suspect they’d apply to many other fields, both within and beyond science. So here goes…

A Proposal is a Highly Structured Rigorous Argument

In its most abstract form, a proposal is a piece of persuasive writing that lays out a convincing case that the proposed research is:

  1. important
  2. feasible
  3. efficient

By “important”, I mean that the project must rise above the level of “good to do”, and instead be seen as “must be done”, even by people who don’t work in the field. By “feasible”, I mean that there must be a clear path to a definitive scientific result. By “efficient”, I mean that the particular approach you’ve taken is the optimal one for reaching the important goals you’re targeting (i.e. aim for “Studying X provides the cleanest test of Important Science Y” and avoid building a proposal to study X when studying Z is clearly a more direct approach to Important Science Y — even if you worked on X for your thesis.)

You should lay out your arguments for Every. Single. One. of these cases before you write a single word of latex. Why? Because proposals live or die not on the beauty of your prose, but on the structure of your argument. If the reviewer does not believe that you’ve made the case for importance, feasibility, and efficiency, you’re done.

Here’s how I do this. Although I’m sure it will seem remedial to many of you, and reveal me as the anal geek that I am, I start a stupid ASCII file with two sections:

  1. Selling Points
  2. Potential Weaknesses to Shore Up

I then start filling out each with short bullet points listing every possible argument for or against what I’m proposing.

The selling points should be fairly easy, since you’re likely to write proposals for things you are inclined to think are awesome. Do, however, avoid the pitfall of conflating “important to me” with “important to Science”. Just because you would really like to know more about some property of something you’re interested in, doesn’t mean that other people will naturally share your enthusiasm. Keep your eye on the big picture.

The “Potential Weaknesses” section can be a bit trickier, since you need to channel your inner crabby reviewer. Think of every nit-picky, outside the box criticism one could throw at your idea, and every area where a reviewer could get confused. (As an example, here’s a list of some of the self-criticisms I came up with for an HST proposal for NIR observations of nearby galaxies a few years back: “What about AO from the ground?” “Why this many targets — how many do you actually need?” “What about dust (i.e. is 1 NIR filter OK)?” “Are the models really in need of improvement?” “How can we claim to do galaxy science while simultaneously arguing that the models aren’t yet up to it?” “Are the results confused depending on fraction of O-rich vs C-rich AGB?” etc).

In short, the “Selling Points” section is about demonstrating “importance”, and the “Potential Weaknesses” section is about assessing “feasibility” and “efficiency”.

After you’ve got an initial list, you have to step back, evaluate, and edit.

  • Go through the selling points and prioritize. Decide what the “main message” of your proposal is, based on which bullet points speak most effectively to the larger importance of what you’re proposing. If your ideas are strong, you’ll usually find that several of the most compelling bullet points will group together and can be ordered to tell a single story. You’ll also find that some of the bullet points will not naturally fit within that narrative. Identify this subset of arguments that are “nice, but not compelling”. You’ll want to be sure to minimize these in the proposal, to avoid their distracting from a more central idea. I speak from experience when I say that you really do not want to confuse the reviewers about what your proposal is about (i.e. It’s better to have something like “Dark Matter! Dark Matter! Dark Matter! and by the way it also tells you something about planets, frogs, and quark stars” rather than “Dark Matter! Planets! Frogs! Quark Stars!”, since the latter leads to complaints from the reviewers that while they believed your dark matter ideas, you had not fully fleshed out a compelling case for the frog science.)
  • For each entry in the “Potential Weakness” section, write down any brief ideas about addressing those concerns (something like “Make figure showing evolution of models with time” “Check number of stars expected and compare to sizes of Galactic samples”, etc). You don’t have to come up with definitive answers, but you should lay out a road map for what you need to do to make your experiment look feasible and efficient.

At this point, I sometimes make a third section and list a few figures that seem like they support the key scientific ideas, or that shore up some of the obvious weaknesses.

Now that you have this silly little ASCII file (which you shouldn’t spend more than a day on, if that), send it to your collaborators. Get their feedback about what they think the strongest selling points are, what their additional concerns are, and what arguments they would use to shore up weaknesses. Expand the file accordingly, so you have a record of everything that you think needs to go into the proposal. You’ll probably find that it’s a huge time savings to get this to your collaborators in this form, before you have a 10 page latex file with embedded figures. If you do the latter, your collaborator will likely come back and say “You know, I think the reviewers are going to be way more interested in frogs”, at which point you have to chuck out weeks of work. With this method, you get feedback quickly (since they have to skim a very short list of bullet points), and you don’t have a lot of sunk costs if you decide to overhaul the arguement.

At this point you’ll have a document that summarizes your rhetorical argument. Your case will be laid out so that you can easily evaluate it on its scientific merits. So, before you dive into writing, you need to step back and decide if you’ve actually constructed a strong case. Sometimes, it will become obvious that there are too many weaknesses to address, and that it’s going to be an uphill battle to convince anyone that this needs to be done. If that’s the case DON’T WRITE THE PROPOSAL! I have probably a half dozen of these ASCII files where I spent half a day deciding that I didn’t, in fact, have a compelling project, and I’d be better off investing my time elsewhere. That’s OK! The exercise of structuring your argument first is designed to be fast, so you don’t sink much time in before you decide whether to continue or not.

Once you (and your collaborators) are convinced that you do in fact have a strong case, you need to start building the actual text. I frequently will estimate the number of paragraphs I expect to have for my scientific justification (usually 2.5-3 per page), and then make an enumerated list showing how the argument will flow through the paragraphs. This exercise helps to keep the text following the structure of the argument, so that it builds to make the main points. It also helps me to figure out when I’m trying to cram too much information in.

If you’ve gone through all of the above, you’ll find that the proposal will almost write itself. You will have cleanly separated “generating text” from “generating a compelling project”, such that you know exactly what you want to convey, and what the text needs to accomplish. Generating lovely English sentences at this point is much easier.


When Eve met Creb

The excellent site io9 has a piece up today which is a fascinating indicator of the nature of popular science publications as a lagging indicator. It is a re-post of a piece published last April, How Mitochondrial Eve connected all humanity and rewrote human evolution. In it you have an encapsulation of a particular period in our understanding of human natural history through evolutionary genetics. Notice for example the focus on maternally transmitted lineages, mtDNA and Y chromosomes. And the citations on genealogy date to the middle aughts. The science is mostly correct as far as it goes in the details (or at least it is defensible, last I checked there was still debate as to the validity of the molecular clocks used for Y chromosomal lineages), but it misses the big picture of how we’ve reframed our understanding of the human past over the last few years. The distance between 2011 and 2009 is far greater in this sense than between 2009 and 1999 (or even 2009 and 1989!). The io9 piece is a reflection of the era before the paradigmatic rupture.

We are no longer talking just about African mtDNA Eve and her husband Y chromosomal Adam. I’m going to consciously avoid the term “revolutionize,” because the broad outlines of the old story certainly hold. Rather, as we are wont to do it seems that we became a bit too bold with some of our brush strokes, and elided fascinating and subtle elements of the landscape on the margins. There were Crebs, and other assorted Oogas and Boogas. And the painting is not completed yet. As such we can’t really draw any conclusions as to “what it all means,” aside from the fact that it’s fascinating.

Addendum: Someone in the comments observes in relation to a depiction of Eve in the story that “She’s awfully pale for an East African.” This is true on the merits, but the logic is kind of dumb. Why exactly do we think that people ~150,000 years ago looked anything like modern East Africans? It is very likely that Europeans ~35,000 years ago did not look like Daryl Hannah.

Survey on genetics knowledge

Filed under: Blog,Survey — Razib Khan @ 2:23 am

A regular issue that comes up on this weblog is that many of my posts are difficult to understand. I am aware of this. Unfortunately a problem is that there is a wide variation in fluency in genetics knowledge among the readership. To get a better sense I have created a survey with 60+ questions. It may seem like a lot, but the questions go fast because there are only three answers to each, and you should immediately know how to respond. I will likely use these responses to guide me in future “refresher” posts and the like. The questions range from relatively simple to moderately abstruse. That’s by design. Thanks.

Note: The survey will not show up in the RSS, so please click through!

Create your free online surveys with SurveyMonkey, the world’s leading questionnaire tool.

January 23, 2012

Personal genomics and adoption

Filed under: Genealogy,Genetics,Genomics,Personal genomics — Razib Khan @ 9:23 pm

With DNA Testing, Suddenly They Are Family:

Several companies provide tests that can confirm whether adoptees are related to individuals they already know. Others cast a wider net by plugging DNA results into databases that contain tens of thousands of genetic samples, provided mostly by people searching for their ancestral roots. The tests detect genetic markers that reveal whether people share a common ancestor or relative.

Some experts on adoption and genetics have criticized ancestry and genealogy testing companies, saying they are, at times, connecting people whose genetic links are tenuous — in effect stretching the definition of a relative. Nevertheless, the growing popularity of the tests, combined with social media sites that connect people day to day, has given some adoptees a sense of family that feels tangible, intimate and immediate.

 

I think that these tenuous connections and slivers of information are better than nothing. This isn’t rocket science. And naturally many adopted people also could care less. This is a deeply personal issue, and the valence is going to be private. I suspect that those of us who aren’t adopted, and take for granted knowledge of our own family background have a hard time imagining the value which even a 3rd or 4th cousin could give someone.

Additionally, though finding very close relatives is not that common (first cousins, let alone first order relatives), knowledge of more distant relations can still help you triangulate aspects of family history if you begin with nothing. To give a personal example I know someone whose paternal grandparents were immigrants from Germany. The maternal side is much more mixed, and some of the genealogical records hit dead-ends in the mid 19th century in the USA. It turns out that one of the individuals that this person is closest to on 23andMe is an African American (both maternal and paternal lineages are clearly African). What does this mean? The lead hasn’t been followed up, but combining family histories might be very informative in this case.

Ahmadiyya chill free speech in the UK

Filed under: Uncategorized — Razib Khan @ 2:38 am

Readers of this weblog will appreciate the tragic irony. Muhammad cartoon row leads to resignation:

The society at University College London (UCL) published an image on its Facebook page showing “Jesus and Mo” having a drink at a bar.

Ahmadiyya Youth Association is continuing with its protest against the image, saying it has wider implications.

Adam Walker, the association’s national spokesperson, said the two student groups had worked well together in the past and said the offence was unnecessary.

The principle is more important than who is being attacked – this time it is Muslims and Christians but in the future it could be atheists themselves”

Adam Walker
Ahmadiyya Muslim Youth Association spokesman
“The principle is more important than who is being attacked – this time it is Muslims and Christians but in the future it could be atheists themselves.

“There is no need to print these things other than to cause offence and history has told us that these things cause offence.”

He added: “I wouldn’t say we’re specifically pursuing UCL atheist society, it’s more about the broader principle.”

The Ahmadiyya, slandered across the Muslim world to an extent that would make Ismailis seem like Sunnis to Salafis, are enforcing Islamic norms about public decorum in relation to religion in the Western world! The irony? Many non-Ahmadiyya Muslims find the sect offensive and insensitive by its very nature (though I’m sure a lot of the offense is due to uncritical acceptance of slanders against the Ahmadiyya).

A huge issue I notice with Muslims and South Asians (non-Muslims) is the inability to distinguish between hurt and insensitivity to the corporate religious/communal abstract identity, and hurt and insensitivity directed toward the concrete identity. In other words, if you sketch out a primitive drawing of Muhammad being sodomized by a dromedary camel, you attack the corporate identity, and since there is no distinction between the collective and individual identity the hurt and pain redounds to the individual.

Older Posts »

Powered by WordPress