Solutions Operative IQ

No, Of course – you haven’t. I don’t mean to belittle you; it’s due to the nature of the CP-DOS that you haven’t heard of it. No one has. Except for the select few government agencies who saw the true beauty, the true value the measure has to society. It really only involves a couple of buttons, a couple of marshmallows, and an excellent guide to measure the Machiavellian nature of the world’s preterm psychopaths. Enough with the abstractions, let’s get to it eh?
There are about 3,000,000 psychopaths in the United States. Psychopaths are your lawyers, parents, bankers; they’re everywhere, and the intelligent ones blend into society with little friction. Most of these people are either pacifistic or not intelligent enough to cause any real damage to our society. It’s the lottery winners of intelligence and the genetic and environmental contributors to violent psychopathy that we need to worry about. This toxic personality cocktail produces the Charlie Manson’s and Jeff Dahmer’s of this world. That’s where I come in.
I began developing the CP-DOS during my PhD dissertation, I studied predictors for psychopathy in early childhood. The logic is simple: if we can identify predictors of violent psychopathy, we can nip them in the bud, and have a safer society. I’ll spare you literature review and statistical analyses, and skip right to the discussion. The study was immensely successful, we found that 90% of our 7 year olds fitting our criteria for ‘at risk’ grew up to be violent and intelligent teenagers and adults. These are the ones who got away, and after my success, I vowed to never let it happen again.
The procedure is so painfully simple, I was almost surprised I got the level of significance I did. All we used was a bag of buttons and a carefully constructed observational structure masquerading as a game for children. There were 15 children in each classroom, and 15 buttons provided. We said each button was worth a marshmallow (calling it money helped them understand). We left them alone in the cafeteria for 10 minutes, and gave them one simple sentence: A button is worth one marshmallow. We videotaped and audio-bugged the room. A kid deemed ‘high risk’ gathered at least 12 buttons, scored high on our IQ test, and used violent and eloquently worded (for a 7-year-old) threats to gather the buttons.
In most classrooms, each child finished the 10 minutes with a button each. Simple, right? 15 buttons, 15 children, the math is simple (even by 7-year-old standards). It was the depraved little bastards we euphemistically referred to as “high risk” who grew up to skin lost animals and… worse. Science is weird like that, huh? Violent threats + intelligence + 12 or more marshmallows, and we have a little psychopathic sprout.
My to-be publication never made it past the peer review stage, I got a rejection letter for it having “potentially dangerous implications”. A month after my first sample of ‘at risk’ children turned 20, I was contacted by a member of the CIA. At this point I had given up on the CP-DOS, and had been teaching intro Psychology at a local community college. I was given an address and told to bring my notes on the measure.
I jumped at the opportunity to converse about my research (have you ever met a doctor of psychology?). I found myself sitting at a round kitchen table of a middle-class colonial with two badged men. They weren’t gigantic clean-cut men with black suits; instead I found myself opposite two average sized men wearing flannels and jeans. Outside of the briefcase and ID badge I requested to see, they looked overwhelmingly average, perhaps by design.
After we exchanged pleasantries, the shorter of the two agents passed me a manila folder with a 20-year-old’s face on the cover. For confidentiality sake, we’ll call this young adult “Ryan”. Believe me when I say, you’ll be thankful I’m keeping this brief. By the age of 20, Ryan was wanted for the rapes and murders of three women in his area, and those are only the reported ones. He’s been on the run for 6 months, and there are no leads to his whereabouts. 13 buttons.
Justin, 20, has been characterized as attractive, clever, and charismatic. Murdered his parents and girlfriend. 12 buttons.
Wade, 21, is antisocial, yet has been constantly hailed a musical prodigy, and piano was his trade. He traded his piano for the execution style killings of his high school bullies. 15 buttons.
Call me apathetic, call me cold, but most importantly, call me correct. I wasn’t bewildered by the results, in fact they made perfect sense. I had narrowed down the characteristic predictors of psychopathy, and operationalized them into a behavioral measure. The list went on, 8 more people, nominally tied to heinous crimes. It wasn’t perfect though, as science rarely is. On the list, there was one name that didn’t fit the bill. Kevin, 20, was in the midst of his public health degree, 3.98 GPA at an ivy league. He has plans to enroll in the Peace Corps, and improve the lives of those less fortunate than him. This fucker hasn’t had as much as a parking violation, let alone any relation to a violent crime. 14 goddamned buttons.
In most other circumstances, I would go down in history as one of the most influential psychologists of all time. These were not average circumstances. Due to Kevin’s existence, and the CIA’s hellbent rhetoric, I ended up trading my fame and mark in history, for anonymity and a pretty annual penny. The agents offered me a seven figure salary for my work and my silence, and my assistants and I would spend the next 10 years practicing my trade across the country. The stench of rectangular pizzas and chocolate milk burnt into my nasal passages, as I travelled elementary school to elementary school administering the CP-DOS. If anything, it was perfect preparation for parenthood. I have a low maintenance job, plenty of money, and all the knowledge in the world on how to raise a wonderful son. I named him Kevin.
I do this for a living, they knew I would catch onto them; I’ve kept close tabs on every ‘high risk’ child throughout the past 10 years. Sure enough, like clockwork, each one serendipitously disappearing weeks after the measure. It was genius really. I was the only one taking statistics on how many buttons each child would walk away with, and the categorization of an ‘at risk’ child was less than half of a percent. 99% of the time, each child would walk away with a button, a marshmallow, and their lives.
My silent inquisition of these prematurely psychopathic children was a blistering success. Over the past 10 years, there have been 54 mysterious disappearances of clever, intelligent children. A miniscule price our country has to pay in exchange for the murders of young women and parents. Abduction rates hardly increased, and violent crime rates impactfully decreased.
So why the hell am I telling you all of this? I need advice. Trust me when I say, the irony of a psychologist seeking advice isn’t lost on me. Call it karma, call it my payment to the 54 souls (10% of which were likely bound to be innocent) I robbed of their lives, but I find myself in a predicament. Should I run? Double down on my philosophy and let the system work its magic?
There I was, doing household chores after a long day in an elementary school 30 minutes from my house. It was Friday, and time for the house’s weekly deep clean and upkeep. I finally got to Kevin’s laundry, and in the back pocket of his worn blue-jeans, there they sat. 13 buttons.
EDIT: Hey Dr. Creepen, I wrote & posted this to Nosleep for a time last year, received ~500 upvotes, then it was removed for "Horrible, but not horror". I should say, Creepypod narrated this as well, but it was price-gated. I would love to hear your take on it!

Use this paper as the go-to and link mine.
Racial and ethnic group differences in the heritability of intelligence: A systematic review and meta-analysis
https://filebin.net/nw5j2i9gzxwf98ms/1-s2.0-S0160289619301904-main.pdf?t=7ou2ybwl
Via meta-analysis, we examined whether the heritability of intelligence varies across racial or ethnic groups. Specifically, we tested a hypothesis predicting an interaction whereby those racial and ethnic groups living in relatively disadvantaged environments display lower heritability and higher environmentality. The reasoning behind this prediction is that people (or groups of people)raised in poor environments may not be able torealize their full genetic potentials. Our sample (k = 16) comprised 84,897 Whites, 37,160 Blacks, and 17,678 Hispanics residing in the United States. We found that White , Black, and Hispanic heritabilities were consistently moderate to high, and that these heritabilities did not differ across groups. At least in the United States, Race/ Ethnicity × Heritability interactions likely do not exist.
So much for racism causing the lower IQ.
We also found that genes accounted for about half of the IQ variance across groups, while shared and nonshared environmental effects explained the other half. Since the average age across samples was 15 (range of sample averages: 4 to 61; mean: 15; median: 12),
Yikes, someone said it. The age of the subjects explains the lowish heritability. Mid teens, not adults.
I've been seeing Tucker-Drob & Bates 2015 get cited a lot lately as some sort of definitive proof of lower heritability of iq among lower SES in the U.S. I wanted to write this post to provide a brief new review of the evidence and list an issue or two with T-D & B.
First and foremost, it's clear that the SR hypothesis has consistently failed to replicate in first world countries outside of the U.S. This was demonstrated in Tucker-Drob & Bates but this seems particularly very overt in the U.K. in particular. Not only was there no SR in the TEDS but there have been three very large studies using molecular genetic methods to demonstrate this:
Selzam et al. (2017) (N=127,000)

The genetic influence of EduYears GPS on educational achievement at age 16 and on g was not greater in high SES than in low-SES families, as would be predicted by the genotype–environment interaction hypothesis described earlier.

Ge et al. (2017) (N=34,491)

In our analysis, using SNP data, we observed no moderating effect of SES (as measured by the Townsend deprivation index) on the heritability of cognitive traits (including fluid intelligence), possibly due to the age range of participants in the UK Biobank (middle and old age) in contrast to many previous studies targeting childhood or early adulthood, and the cross-national differences in gene-by-SES interaction on intelligence as shown by a recent meta-analysis [34].

(This study did find some evidence of SR for EA, but not for UKBB shitty fluid iq test.)
Tahmabsi et al. (2017) (N=40,172)

We found that the additive genetic variation of IQ tagged by SNPs increases as socioeconomic status (SES) decreases, opposite the direction found by several twin studies conducted in the U.S. on adolescents, but consistent with several studies from Europe and Australia on adults.

While the U.K. clearly shows no evidence of SR, what about the U.S.? While T-D & B's meta-analysis might seem convincing, there are some issues with it. There are some holes in it. The main being that effect-size clearly wasn't sample-size weighted as there was a seemingly large inverse relationship between sample-size and effect-size as noted by Emil. Grant et al. (2010) 3,203 twin-pairs and found no SR and Kirkpatrick, McGue, and Iacono (2015) had 2,494 pairs and found a very-weak SR with the biggest h2 difference being ~.05. These two studies made up slightly more than half of the full U.S. sample and found null effects. The other issue that this had was that it included a study on motor skills of infants and that has a near-zero correlation with adult iq. Moving on, let's take a look at some newer studies and ones that were missed:
Figlio et al. (2017)
This study seemingly crushed the dreams of fans of SR when it was first released. The sample size is huge (N=34,432; more than three times that of the T-D & B U.S. sample), it's in a state with a one of the highest gini coefficients of any U.S. state, and the sample is fairly racially diverse. Not only did SR fail to replicate, but the only effect-sizes to reach statistical significance are in the opposite direction. One potential flaw this study might have is that it had to infer zygosity from SS and OS sex comparisons. Fortunately, the commentary shows that the assumption holds just fine.
Turkheimer, Beam & Davis (2015)
This one is interesting, the sample size is only slightly larger than the original Winner's Curse and it's using data from the Louisville twin study. The Lousville twin study is one of the oldest and one with a lot of data. There was no SR here which is interesting; if this would have been analyzed in 2003 instead of the NCCP, then there wouldn't have been such a ruckus.
McGue et al. (2007)
SIBS adoption data was used here instead of the conventional method involving twins or kinship comparisons. In this study it was demonstrated that range-restriction of environments did not matter for adopted children and neither did family SES for iq. Those things only mattered for non-adopted children.
Beaver et al. (2014)
I'm only including this one because among the parental variables related to Viq examined was education. Interestingly enough, this was the same dataset that David Rowe originally used to demonstrate the SR. Maternal education didn't matter for Wave III iq or the MZ subsample. Some people might construe the fact that it mattered in Wave I as proof of some evidence of SR, but unrelated individuals reared-together grow more discordant as heritability of iq increases (Hunt (2011, page 227; Bouchard & McGue (2003)).
Nagoshi & Johnson (2005)
The sample-size is okayish (N=1,349) and it uses a decent measure of both g and SES. The SR failed to replicate here but there is one major issue with this study; it did not analyze the heritability of g but parent-child relationship. Interpret this one how you want.
Hart, Petrill, & Dush (2011)
Using biometric models in the CNLSY, the study here found no evidence that the heritability of a variety of cognitive abilites was any lower in the bottom 20% than the normal group. The sample-size here is fairly large and the sample itself is racially diverse and oversampling of lower SES individuals. Some people may not like it because of how it tested the SR, but I view this as a somewhat superior method as it sidesteps a lot of the complaints from people like Kevin about how SES is poorly operationalized in other studies etc. All of the measures of CA that they use seem to correlate with g at r>.7 (Zaboski II, Kranzler, & Gage (2018)).
Little, Haughbrook, & Hart 2018
As the previous study shows, RC is a robust correlate of g. Building on that point, this giant meta-analysis found that the heritability of RC was not modified by SES, Racial composition, or nationality. Very powerful evidence against SR here.
Woodley of Menie, Pallesen, & Sarraf (2018)
The first study to use PGS to test for SR in the U.S. as far as I know. While there was a SR effect here, the effect-size was meager (B=.02 on a log-scale). Some pointed out by the author's is that the cohort here was born in the 40's so the range of environments that we're dealing with may be a bit dated.
Overall, the SR effect in the U.S. seems very weak at best and probably non-existent for the most part.
There are two more important points pertaining to group differences that I would like to note before I end:

• Heritability of iq is not lower across racial groups in U.S. (Fuerst & Dalliard (2014); Mollon et al. (2018))
• There is a consistently replicated positive interaction between race gaps and SES. That is, even if there was a SR effect, it still mostly doesn't matter for the discussion of group differences as race gaps are the largest at higher SES levels.

Reliability: the overall consistency of a measure.
Common subtypes of reliability

• Inter-Rater Reliability: the consistency of scores on a measure provided by two separate raters (i.e., individuals scoring the measure) on the same set of results.
• Test-Retest Reliability: the consistency of scores on a measure across two different time points on the same set of results.
• Internal Consistency Reliability: the consistency between different items within a single assessment measure (usually reflected in the consistency of responses on items that are designed to be similar in content).

​
Validity: the overall accuracy of a measure (i.e.: “does this assessment actually measure what it is supposed to measure?”)
Common subtypes of validity

• Construct Validity: the extent to which operationalizations of a construct measure a construct as defined by a theory (e.g., how well does this test measure [the construct of] intelligence?).
• Content Validity: the extent to which a measure represents a specific area of content (e.g., “does this test of reading ability actually represent reading ability?”)
• Face Validity: the extent to which a measure appears to represent a construct. High/low face validity does not impact how “good” a measure is, but rather whether or not it is “deceptive” in what it is measuring. For example, a true-false item stating “I never lie” has high face validity on a measure designed to assess morality, but has low face validity on a measure designed to assess symptom validity.
• Criterion Validity: the extent to which a measure can be used to infer, predict, or estimate a specific criterion (i.e.: outcome). For example, “how well does IQ predict school performance?”

​
\**Please note that reliability DOES NOT necessitate validity - your measure can have high reliability but low validity. Conversely, validity DOES necessitate reliability - if a test has high validity it will always have high reliability.**\**

I've been seeing Tucker-Drob & Bates 2015 get cited a lot lately as some sort of definitive proof of lower heritability of iq among lower SES in the U.S. I wanted to write this post to provide a brief new review of the evidence and list an issue or two with T-D & B.
First and foremost, it's clear that the SR hypothesis has consistently failed to replicate in first world countries outside of the U.S. This was demonstrated in Tucker-Drob & Bates but this seems particularly very overt in the U.K. in particular. Not only was there no SR in the TEDS but there have been three very large studies using molecular genetic methods to demonstrate this:
Selzam et al. (2017) (N=127,000)

The genetic influence of EduYears GPS on educational achievement at age 16 and on g was not greater in high SES than in low-SES families, as would be predicted by the genotype–environment interaction hypothesis described earlier.

Ge et al. (2017) (N=34,491)

In our analysis, using SNP data, we observed no moderating effect of SES (as measured by the Townsend deprivation index) on the heritability of cognitive traits (including fluid intelligence), possibly due to the age range of participants in the UK Biobank (middle and old age) in contrast to many previous studies targeting childhood or early adulthood, and the cross-national differences in gene-by-SES interaction on intelligence as shown by a recent meta-analysis [34].

(This study did find some evidence of SR for EA, but not for UKBB shitty fluid iq test.)
Tahmabsi et al. (2017) (N=40,172)

We found that the additive genetic variation of IQ tagged by SNPs increases as socioeconomic status (SES) decreases, opposite the direction found by several twin studies conducted in the U.S. on adolescents, but consistent with several studies from Europe and Australia on adults.

While the U.K. clearly shows no evidence of SR, what about the U.S.? While T-D & B's meta-analysis might seem convincing, there are some issues with it. There are some holes in it. The main being that effect-size clearly wasn't sample-size weighted as there was a seemingly large inverse relationship between sample-size and effect-size as noted by Emil. Grant et al. (2010) 3,203 twin-pairs and found no SR and Kirkpatrick, McGue, and Iacono (2015) had 2,494 pairs and found a very-weak SR with the biggest h² difference being ~.05. These two studies made up slightly more than half of the full U.S. sample and found null effects. The other issue that this had was that it included a study on motor skills of infants and that has a near-zero correlation with adult iq. Moving on, let's take a look at some newer studies and ones that were missed:
Figlio et al. (2017)
This study seemingly crushed the dreams of fans of SR when it was first released. The sample size is huge (N=34,432; more than three times that of the T-D & B U.S. sample), it's in a state with a one of the highest gini coefficients of any U.S. state, and the sample is fairly racially diverse. Not only did SR fail to replicate, but the only effect-sizes to reach statistical significance are in the opposite direction. One potential flaw this study might have is that it had to infer zygosity from SS and OS sex comparisons. Fortunately, the commentary shows that the assumption holds just fine.
Turkheimer, Beam & Davis (2015)
This one is interesting, the sample size is only slightly larger than the original Winner's Curse and it's using data from the Louisville twin study. The Lousville twin study is one of the oldest and one with a lot of data. There was no SR here which is interesting; if this would have been analyzed in 2003 instead of the NCCP, then there wouldn't have been such a ruckus.
McGue et al. (2007)
SIBS adoption data was used here instead of the conventional method involving twins or kinship comparisons. In this study it was demonstrated that range-restriction of environments did not matter for adopted children and neither did family SES for iq. Those things only mattered for non-adopted children.
Beaver et al. (2014)
I'm only including this one because among the parental variables related to Viq examined was education. Interestingly enough, this was the same dataset that David Rowe originally used to demonstrate the SR. Maternal education didn't matter for Wave III iq or the MZ subsample. Some people might construe the fact that it mattered in Wave I as proof of some evidence of SR, but unrelated individuals reared-together grow more discordant as heritability of iq increases (Hunt (2011, page 227; Bouchard & McGue (2003)).
Nagoshi & Johnson (2005)
The sample-size is okayish (N=1,349) and it uses a decent measure of both g and SES. The SR failed to replicate here but there is one major issue with this study; it did not analyze the heritability of g but parent-child relationship. Interpret this one how you want.
Hart, Petrill, & Dush (2011)
Using biometric models in the CNLSY, the study here found no evidence that the heritability of a variety of cognitive abilites was any lower in the bottom 20% than the normal group. The sample-size here is fairly large and the sample itself is racially diverse and oversampling of lower SES individuals. Some people may not like it because of how it tested the SR, but I view this as a somewhat superior method as it sidesteps a lot of the complaints from people like Kevin about how SES is poorly operationalized in other studies etc. All of the measures of CA that they use seem to correlate with g at r>.7 (Zaboski II, Kranzler, & Gage (2018)).
Little, Haughbrook, & Hart 2018
As the previous study shows, RC is a robust correlate of g. Building on that point, this giant meta-analysis found that the heritability of RC was not modified by SES, Racial composition, or nationality. Very powerful evidence against SR here.
Woodley of Menie, Pallesen, & Sarraf (2018)
The first study to use PGS to test for SR in the U.S. as far as I know. While there was a SR effect here, the effect-size was meager (B=.02 on a log-scale). Some pointed out by the author's is that the cohort here was born in the 40's so the range of environments that we're dealing with may be a bit dated.
Overall, the SR effect in the U.S. seems very weak at best and probably non-existent for the most part.
There are two more important points pertaining to group differences that I would like to note before I end:

• Heritability of iq is not lower across racial groups in U.S. (Fuerst & Dalliard (2014); Mollon et al. (2018))
  
• There is a consistently replicated positive interaction between race gaps and SES. That is, even if there was a SR effect, it still mostly doesn't matter for the discussion of group differences as race gaps are the largest at higher SES levels.
  

Robert Sapolsky on heritability: https://youtu.be/RG5fN6KrDJE?t=40m
Browsing the discussion about the latest podcast has been very interesting and I want to thank Sam and this community for coming together for discussion. I see this issue as an enormous social pendulum swinging from one extreme to the other. At one endpoint, people see genetics as having no bearing on social, economic, political, and psychological outcomes. On the other, people see genetics as being deterministic.
I suspect nearly everyone here would wisely call both of these extremes foolish in light of the scientific evidence.
Rather, we are interested in how much variation in a trait (say, IQ) can be explained by genetics. Techniques: adoption studies, marker studies, and twin studies. But there are some problems!
The problems:

• Babies in adoption and twin studies share a prenatal environment (there is also the issue of choinic or non-chorionic twins) Environment begins in utero.
  
• Some fuzzy phenotypes are not easily detected (IQ) some are easily detected (PKU, sickle cell). I can run a blood test to detect sickle cell. An IQ test is an operationalization of what researchers think intelligence is. IQ is a difficult thing for everyone to agree on (not just because it's a socially difficult concept).
  
• The genes that are antecedents of IQ are likely 100s of different genes in dozens of gene networks all working together in various ways. Unfortunately the specific genes of IQ are unknown. We have very little knowledge about specific genes that contribute to IQ
  

Most of these studies measure heritability. Heritability definition: estimates how much variation in a phenotypic trait in a population is due to genetic variation among individuals in that population.
There are two examples that you need to understand in order to grasp heritability:

1. Number of finger has nearly 0 percent heritability. While our genes program for how many fingers we have, variability is largely accounted for by whether we've had any industrial accidents (lost a finger due to environment).
   
2. Whether or not you wear earrings in 1950s America is nearly 100% heritable. Variability in earring wearing in 1950s was entirely accounted for by which gender you are (wearing earrings due to genetics).
   

Problems with heritability:

• Even though humans live in vastly different types of environments, behavioral genetic research often artificially inflates "heritability" by controlling environmental context.
  
• Often the answer for what does gene X have to do with IQ, the answer will be "it depends". Gene function is often not consistent across environmental variations. Gene profile A that leads to high IQ in environment 1, may not give you an edge in environment 2. In fact, sometimes gene-environment interactions actual flip the phenotype of a gene profile in different environments. Genes can have non-intuitive interactions with the environment. This is all to say, phenotypes are often not consistent even with the same genotype.
  

Heritability doesn't taken any of this into account.
As a final example: Let’s look at PKU. PKU is a genetic disease that was once said to be 100% heritable because every child with the genetic profile developed the disease. Now, heritability is much lower. Why? Because people now know that children with PKU should avoid phenylalanine. Heritability was inflated because our ignorance of the environmental conditions that result in the phenotype.
TL;DR quote from Sapolsky himself: “There is no such thing as a genetic influence outside the context of an environmental interaction”.
To put a cap on my contribution to the IQ conversation: Heritability of IQ is not the same as generalizable knowledge about genetic contribution to IQ.

The relevant article was recently published, although the entire thing is behind a subscription wall, so the authors published a summary (much more detailed than a traditional "abstract") here. The whole thing is worth reading, and it isn't very long.
Some highlights:

In this article, we suggest that one largely overlooked cause of failure is a lack of political diversity. We review evidence suggesting that political diversity and dissent would improve the reliability and validity of social psychological science…
We focus on conservatives as an underrepresented group because the data on the prevalence in psychology of different ideological groups is best for the liberal-conservative contrast – and the departure from the proportion of liberals and conservatives in the U.S. population is so dramatic.
The lack of diversity causes problems for the scientific process primarily in areas related to the political concerns of the Left – areas such as race, gender, stereotyping, environmentalism, power, and inequality – as well as in areas where conservatives themselves are studied, such as in moral and political psychology.

It's refreshing to see a group of maverick academics admit that, in effect, many of the studies of the sharpest interest between left and right (and which, of course, are the most salient for the issues discussed at PPD) are at risk of being inherently biased in favor of the orthodox left. This is something that has been intuitive to any of who are both not members of the orthodox left and who have spent some time around the humanities/social sciences academy, but it is nevertheless refreshing to see a small group of academics admit to this, and have the balls both to do that and to study how and why that is the case.
More:

Before the 1990s, academic psychology only LEANED left. Liberals and Democrats outnumbered Conservatives and Republican by 4 to 1 or less. But as the “greatest generation” retired in the 1990s and was replaced by baby boomers, the ratio skyrocketed to something more like 12 to 1. In just 20 years. Few psychologists realize just how quickly or completely the field has become a political monoculture. This graph took us by surprise too.
Might a shared moral-historical narrative [the “liberal progress” narrative described by sociologist Christian Smith] in a politically homogeneous field undermine the self-correction processes on which good science depends? We think so, and present three risk points— three ways in which political homogeneity can threaten the validity of social psychological science
3.1. Risk point 1: Liberal values and assumptions can become embedded into theory and method The embedding of values occurs when value statements or ideological claims are wrongly treated as objective truth, and observed deviation from that truth is treated as error.
[Example:] Son Hing, Bobocel, Zanna, and McBride (2007) found that: 1) people high in social dominance orientation (SDO) were more likely to make unethical decisions, 2) people high in right-wing authoritarianism (RWA) were more likely to go along with the unethical decisions of leaders, and 3) dyads with high SDO leaders and high RWA followers made more unethical decisions than dyads with alternative arrangements (e.g., low SDO—low RWA dyads). Yet consider the decisions they defined as unethical: not formally taking a female colleague’s side in her sexual harassment complaint against her subordinate (given little information about the case), and a worker placing the well-being of his or her company above unspecified harms to the environment attributed to the company’s operations. Liberal values of feminism and environmentalism were embedded directly into the operationalization of ethics, even to the extent that participants were expected to endorse those values in vignettes that lacked the information one would need to make a considered judgment. The appearance of certain words that imply pernicious motives (e.g., deny, legitimize, rationalize, justify, defend, trivialize) may be particularly indicative of research tainted by embedded values.
3.2. Risk point 2: Researchers may concentrate on topics that validate the liberal progress narrative and avoid topics that contest that narrative.
Since the enlightenment, scientists have thought of themselves as spreading light and pushing back the darkness. The metaphor is apt, but in a politically homogeneous field, a larger-than-optimal number of scientists shine their flashlights on ideologically important regions of the terrain. Doing so leaves many areas unexplored. Even worse, some areas become walled off, and inquisitive researchers risk ostracism if they venture in.
3.3. Risk point 3: Negative attitudes regarding conservatives can produce a psychological science that mischaracterizes their traits and attributes

These seem clear enough, to anyone who doesn't toe the orthodox progressive line. Yet, the question remains -- why is the situation this way? Haidt and colleagues looked into this as well:

1. Why are there so few non-liberals in social psychology? the evidence does not point to a single answer. To understand why conservatives are so vastly underrepresented in social psychology, we consider five explanations

5.1. Differences in ability [Are conservatives simply less intelligent than liberals, and less able to obtain PhDs and faculty positions?] The evidence does not support this view… [published studies are mixed. Part of the complexity is that…] Social conservatism correlates with lower cognitive ability test scores, but economic conservatism correlates with higher scores (Iyer, Koleva, Graham, Ditto, & Haidt, 2012; Kemmelmeier 2008). [Libertarians are the political group with the highest IQ, yet they are underrepresented in the social sciences other than economics]
5.2. The effects of education on political ideology Many may view education as “enlightening” and believe that an enlightened view comports with liberal politics. There is little evidence that education causes students to become more liberal.
5.3. Differences in interest Might liberals simply find a career in social psychology (or the academy more broadly) more appealing? Yes, for several reasons.
5.4. Hostile climate Might self-selection be amplified by an accurate perception among conservative students that they are not welcome in the social psychology community?
Evidence of hostile climate is not just anecdotal. Inbar and Lammers (2012) asked members of the SPSP discussion list: “Do you feel that there is a hostile climate towards your political beliefs in your field?” Of 17 conservatives, 14 (82%) responded “yes” (i.e., a response at or above the midpoint of the scale, where the midpoint was labeled “somewhat” and the top point “very much”), with half of those responding “very much.” In contrast, only 18 of 266 liberals (7%) responded “yes”, with only two of those responding “very much.” Interestingly, 18 of 25 moderates (72%) responded “yes,” with one responding “very much.” This surprising result suggests that the hostile climate may adversely affect not only conservatives, but anyone who is not liberal or whose values do not align with the liberal progress narrative.
5.5. Discrimination The literature on political prejudice demonstrates that strongly identified partisans show little compunction about expressing their overt hostility toward the other side (e.g., Chambers et al., 2013; Crawford & Pilanski, 2013; Haidt, 2012). Partisans routinely believe that their hostility towards opposing groups is justified because of the threat posed to their values by dissimilar others (see Brandt et al., 2014, for a review). Social psychologists are unlikely to be immune to such psychological processes. Indeed, ample evidence using multiple methods demonstrates that social psychologists do in fact act in discriminatory ways toward non-liberal colleagues and their research.
Conservative graduate students and assistant professors are behaving rationally when they keep their political identities hidden, and when they avoid voicing the dissenting opinions that could be of such great benefit to the field. Moderate and libertarian students may be suffering the same fate.

What is the relevance of this to PPD?
That should be clear.
Why on Earth should those of us who dissent from the liberal/progressive orthodoxy on these issues that we discuss here at PPD (which are in the scope of what the researchers here found to be most subject to the kinds of biases they address) defer to peer-reviewed papers coming from an academy that systemically discriminates against alternative points of view and which, in many ways, acts as an echo chamber of liberal progressive orthodoxy? This is, in fact, the main reason I have never laid a lot of stock in peer-reviewed social science research -- it is hopelessly biased, due to the overwhelming biases of the people conducting it. Thankfully, there are a few academics of the left who see the problems in having their side be hegemonic in the academy, such that this research is taking place. But until some kind of balance is restored, substantial skepticism understates the proper approach to be taken to research being done in these "politically and socially sensitive" areas. Something to keep in mind when citing, or responding to a cite, of this or that peer-reviewed social science "study".

Dear glitching noise,
Maybe this isn't such a good idea. But here goes.
I'm sorry I was petty, hostile, and difficult to you when we were working together. I made things unpleasant and personal and I shouldn't have.
Despite our differences, I am glad I was able to learn from you. I think you may be insecure about your IQ, perhaps not. But I don't think you should be. IQ is a poorly operationalized measure to begin with. But because of that, I have to say something. I have met and worked with a lot of scientists from a lot of disciplines. You are, quite literally, one of the most brilliant people I have ever worked with. You know psychology, neurology, and even physics to a level most can never hope to rise to. You are the best psychologist I have ever worked with. Period. No one understands the brain and its relation to behavior like you do. You are an inspiration to me. I am honored to have worked with you - you are a true master of your craft. I hope one day I can be even a fraction of the scientist that you are.

IANAE, so excuse any errors, and the general mess. I collected some resources over time out of personal interest (call it the a-word, if you will). All of them carry many methodological qualifications, and remain contestable in details, unfortunately. There are no hard answers here, just bits and pieces of developing frameworks, that at least help to think about such issues, and maybe someone will find this useful, or notice that I got something wrong.
TLDR: We're not at the end of history, and shouldn't fall to status quo bias. Everything boils down to what Destiny keeps saying, that we should work on what we can change.
IQ and personality traits are malleable, e.g. by nurture, therapy (1, 2, 3, 4). We know of no deterministic genetic mechanisms that would preclude this.
Historical development and well-being of various populations is nowadays argued to be determined by:

1. Geography. This is the "Guns, Germs and Steel" argument that I guess we already know at this point.
   
2. Quality of inclusive political and economic institutions – among these e.g. stable rule of law, property rights, equal access to education and opportunity. This view is spearheaded and popularized by Daron Acemoğlu, and at the very least I recommend reading any summary of his "Why Nations Fail", which gives a good framework for this topic. This research line seems solid, even if "institutions" are not very precisely defined. (1, 2, 3, 4, 5). The killer argument from this angle are comparisons of how the exact same real world populations have thrived or withered under different institutions, like in North and South Korea, border areas of USA/Mexico, or East and West Germany. In particular, long term extractive regimes – the slave-owning colonial ones, for example, give way for a vicious cycle of infighting and poverty, that continue even after a superficial political change. This ties into the second point:
   
3. Social capital (culture, values, including social trust, and also potentially genetics) is argued to matter apart from institutions and geography. A couple of papers argue that such things constitute "deep roots" of development, and can be difficult to change, even over many generations. But it can and does change, I'll come back to this later. While many studies here are very good efforts, culture and institutions remain obviously really hard to disentangle, so be wary of people dismissing either one. I have some reservations here about trust being operationalized by literally one question in a self-report measure, and tendency to consider only national-level institutions, which causes omitted variable bias by overlooking informal institutions in weak nation-states. (1, 2, 3, 4, 5, 6, 7). Now, while some of studies in this approach employ genetic distance to differentiate populations, all authors I've read are very skeptical of actual genetic explanations of development. Rather, they see high plausibility of barriers hypothesis. More similar, neighboring populations have higher, not lower differences: suggesting that it's not genetics, but language and cultural barriers, and other historical antagonisms, that drive the effect. (particularly relevant examples: 1, 2). Some quotes from the Easterly paper:
   

While it is possible that intergenerationally transmitted traits have direct effects on productivity and economic performance (for example, if some parents transmit a stronger work ethic to their children), another possibility is that human traits also act to hinder development through a barrier effect: more closely related societies are more likely to learn from each other and adopt each other's innovations.

For instance, historically rooted differences may generate mistrust, miscommunication, and even racial or ethnic bias and discrimination, hindering interactions between populations that could result in a quicker diffusion of productivity-enhancing innovations from the technological frontier to the rest of the world.

the magnitude of the effect of genetic distance is maximal in 1870, in the wake of the Industrial Revolution. The effect then declines steadily from the peak of 16% in 1870 to 7:8% in 2005

Evidence on the long-term persistence of pernicious cultural traits is provided by Nico Voigtlander and Hans Joachim Voth (2011), who use data on anti-Semitism in Germany and Önd continuity at the local level over six centuries: anti-Semitic pogroms during the Black Death in 1348-50 are a strong and robust predictor of violence against Jews in the 1920s and of the vote share of the Nazi Party.

That leaves a large fraction of variation to be explained by other factors and forces, suggesting that many societies can escape the straightjacket of history. (...) Cultures and societies are persistent but dynamic, and can change over time, as stressed in a famous quote attributed to Senator Daniel Patrick Moynihan: "The central conservative truth is that it is culture, not politics, that determines the success of a society. The central liberal truth is that politics can change a culture and save it from itself."

When Japan got the Industrial Revolution, it became a cultural beachhead. South Korea followed, and then industrialization and modernization spread across several societies in East Asia. North Korea, in contrast, is a sad example that very bad policies and institutions can kill growth and development in a society irrespectively of any long-term historical and cultural variables

One potential way forward appears to be brain circulation, which in contrast to the fears of a "brain drain" seems to be mostly beneficial for the migrants, and countries of origin's growth (1, 2), democratization (1, 2, 3, 4, 5), institution quality and international relations (1, 2, 3), and cultures (1, 2).
Another way forward is evidence-based schooling and human capital investments, including desegregation. These can have strong positive returns and externalities. (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, etc.) Early ed is especially promising. (1, 2, 3, 4, 5, 6).
Human capital externalities obviously include lower crime rates, better health, etc. (1, 2, 3, 4). Even without completing primary or any other education level, participation in it is good. (1)
People can also benefit from various sensibly designed interventions, like regulations, redistribution and Piguovian taxes. It decreases poverty, crime, and improves health. (1, 2, 3, 4, 5, 6, 7).
Do postcolonial states have capacity for full convergence? Will globalization bring them economically and culturally all the way to the developed world? Historically we're only just past the peak great divergence. Many parts of Eastern Europe, Asia, South America managed to converge really well. Among success stories in Africa, e.g. Mauritius, Seychelles, Botswana and South Africa present large promise. All this happens against odds, despite toxic historical background, massive AIDS and malaria epidemics, and weak states. Good resources that visualize the road up are, as always:

• https://africaindata.org (ourworldindata side project).
• https://gapminder.org

As seen above, formal institutions haven't yet spread into many Third World peripheries, and there is plenty of room for future improvements.
Can foreign aid help? Maybe – there were many disappointing results, and among others, Easterly heavily campaigns against dumb foreign aid. Some things work nonetheless, especially marginal, evidence-based things like malaria nets. General point is, it's probably harder to "export" prosperity and democracy, than to import and export people. (It's particularly hard to "export democracy" by way of war.)
Well designed, temporary affirmative action may occasionally be helpful, with drawbacks overshadowed by gains. (1, 2, 3, 4).
OTOH: poverty can be a vicious circle, that people won't escape alone. (1, 2, and a nice /neoliberal writeup).
Such discussions sometimes go into philosophy and economics of libertarianism, a.k.a. freedom of choice and "personal responsibility". Jeffrey Friedman penned a good (long) insider criticism of this angle, if anyone's interested. Tl;dr: Neither is the libertarian ethics irrefutable, nor the ancap economics.
Bonus meme: "The bosom of America is open to receive not only the opulent & respectable Stranger, but the oppressed & persecuted of all Nations & Religions; whom we shall wellcome to a participation of all our rights & previleges, if by decency & propriety of conduct they appear to merit the enjoyment." –G. Washington

Let's say in social, psychological (emotional, IQ, pathologies, etc.), neurological (brain pattern), physiological (general health problems, tumors, etc..), or economic terms. What is the cost of someone who has had to repress their sexuality for any amount of time?
Also are there any good studies on operationalizing and quantifying and clearly demonstrating said cost of sexual repression?