Pumpkin Person rating: 9/10

Director: Ali Abbasi, Writer: Gabriel Sherman Budget: $16 million Box office: $12 million

I’ve been wanting to see this movie for a long time but apparently all the movie theatres feared law suits because the few theaters that would show it would only do so on weekday afternoons when I was working. This is not surprising given that a Trump spokesperson called the film “garbage” and “pure malicious defamation, should not see the light of day, and doesn’t even deserve a place in the straight-to-DVD section of a bargain bin at a soon-to-be-closed discount movie store. It belongs in a dumpster fire.”

According to Trump spokesperson Steven Cheung “We will be filing a lawsuit to address the blatantly false assertions from these pretend filmmakers…This garbage is pure fiction which sensationalizes lies that have been long debunked. As with the illegal Biden Trials, this is election interference by Hollywood elites, who know that President Trump will retake the White House and beat their candidate of choice because nothing they have done has worked.”

Finally I saw the film from the comfort of my home which I prefer anyway. The film depicts Trump’s life from the mid 1970s to the mid 1980s. It starts when the twenty-something Trump is at a private club with a young woman. He notes that across the room from them is one of the only two billionaires in America and explains that becoming a billionaire takes a certain gene.

Notorious closeted gay lawyer lawyer  Roy Cohn (played by Jeremy Strong from HBO’s must-see show Succession) invites the awkward young man (but not his date) to his table to eat with an Italian mobster and other power brokers. Cohn feels sorry for the goofy, oafish yet handsome young Trump, takes him under his wing and teaches him how to be a winner (though the subtext is Cohn has a crush on him) much to the jealousy of Cohn’s other blond young friend who seems to feel the even younger Trump is being groomed as his replacement.

Many of the techniques that caused Scott Adams types to view Trump as a political chess master, were, according to this film, actually taught to him by Roy Cohn who is portrayed as the evil genius mastermind behind Trump’s success. More evidence for Ashkenazi high IQ.

Among the rules Cohn taught his young apprentice:

• Attack, attack, attack; someone hits you; hit them back ten times harder
• Deny everything; admit nothing
• No matter how badly you’re beaten, always declare victory

But in the end there is no victory for Cohn who finds himself brutally discarded once Trump no longer needs him.

I thought the film was clever in not trying to tell Trump’s entire life story, but focusing on a specific period. His initial rise from the outsider from Queens to the King of New York. No one personifies that city during the 1980s quite like Trump, and the film is peppered with nostalgic tunes like The Pet shop Boys’ Always on My Mind and Baccara’s haunting Yes sir I can boogie to depict his ill-fated romance with first wife Ivana who is portrayed as stunningly beautiful in her youth.

But perhaps the true star of the film is the city of New York itself, with its massive skyscrapers, bright lights and all around vibrancy, seen from the panoramic view from high up in Trump tower.

For years HBDers have been citing twin studies to argue that IQ is up to 80% heritable. The logic seemed straightforward enough: Take pairs of identical twins separated at birth (or shortly there after) raise them in different homes, and then give them an IQ test. When this was done in the famous Minnesota Twin study, the correlation was 0.75, suggesting 75% of the variance in IQ is caused by genes. Taking the square root of the correlation suggests an astonishing 0.87 correlation between IQ and genes, and that 87% of the individual differences in American IQs are caused by genes.

Critics argue that the twins were not raised sufficiently apart to warrant such strong conclusions. Some like commenter RR argue that the very idea of inferring causation is absurd because genes and IQ interact. For example good genes cause good environments and bad genes cause bad environments so even if identical twins are perfectly separated into random environments at birth, the fact that they both have the same genes means they’ll both end up in similar environments by age 40, so does it really make sense to credit the genes for their IQ similarity when the genetic effect was mediated by environment?

My answer has always been “yes”, because even if environment were what directly caused someone to have a high or low IQ, it was their genes that made them smart or dumb enough to end up in a good or bad environment in the first place, relative to the one they started in, so genes were the ultimate cause of the IQ.

But then I did a thought experiment: Imagine if in the future they develop really good gene editing technology and the richer your parents, the better the gene editing is. Now imagine if we did studies of identical twins raised apart in this society. We might find heritability drops to only 0% because when your identical twin is raised from birth in a much richer home, his adoptive parents can afford the best gene editing software money can buy, causing his intelligence to be twice yours.

Even if the IQ gaps between identical twins raised apart in such a society were 100% caused by genetic editing, twin studies would show them to be 100% caused by environment because the IQ correlation between identical twins raised apart in that society might be zero.

Even though it’s technically true that their environment caused their IQ differences since environment mediated access to gene editing, it would feel somehow wrong to say genes had no effect on their IQ, when literally 100% of the IQ differences were caused by gene editing.

So what I learned from this thought experiment is that heritability does not partition the variance into genes vs environment, but rather it partitions it into genes you were born with vs environment you were born with. Only in organisms that have very little ability to change their environment (like plants or to some degree people living in strict caste systems like 1940s India) , do twin studies capture the full spirit of heritability.

It’s pretty rare that Friday the 13th occurs in June (the birthday of Jason Voorhees) so it’s time to take a look at his sick and tragic life.

He’s an older Jewish man who was accused of rape after sexually inappropriate behavior.

She’s a young black woman who was accused of antisemtism after defending Palestinians in Gaza and indulging in conspiracy theories.

He was the King of movies. She is the Queen of new media.

Their unlikely friendship could itself have been one of the many great movies Weinstein produced. I’d call it, WHEN HARVEY MET CANDACE.

Using genetic data from Lee et al (2018), Davide Piffer has calculated polygenic scores for education/cognition for various populations around the World. Although these scores have very modest predictive power at the individual level, at the group level they correlate extremely well with IQ.

Below is a chart that reports these scores for 12 different “races” using two different polygenic scores (MTAG & PGS GWAS sig). In some cases the scores had to be inferred. For example the datasets did not have direct measures for Arctic people but because there was MTAG data on Mongolians and East Asians and because Mongolians are a hybrid of Arctic people and East Asians, their scores could be deduced.

The polygenic scores were converted to IQ equivalents by assigning the average European polygenic score an IQ of 99 (consistent with their psychometric scores) and assigning the average Bantu polygenic score an IQ of 80 (based on Richard Lynn’s 2006 estimate of how African Americans would average if they had no white admixture). From these two races, the IQs of all other races could be derived through linear extrapolation.

The most striking thing about the data is the clear correlation between genetic IQ and climate. All five of the top ranked races have light skin or lived in a cold climate during the ice age. Meanwhile the bottom four all have “Negroid” morphology, with the bottom three having never left sub-Saharan Africa. It is interesting that the bottom three never independently invented agriculture and the bottom two never made the neolithic transition at all, consistent with Richard Lynn’s theory that it was not until the last wurm glaciation about 20,000 years ago (which sub-Saharans did not endure) that humans became intelligent enough to take advantage of the wild grasses. By sadly killing everyone who was too dull to make fire, shelter and warm clothing, the last wurm glaciation probably raised North Eurasian IQ to near 90, and then only those with IQs of 93+ would make the leap to civilization. The exceptions are the Finns and the Arctic people who more or less reached triple digit IQ despite remaining essentially cavemen.

Population	Average polygenic MTAG Raw score calculated by Davide Piffer derived from Lee et al. (2018)	PGS (GWAS sig)	Genetic IQ derived from polygenic MTAG	Genetic IQ derived from PGS (GWAS sig)	Average of the one or two genetic IQs
Ashkenazi		50.038		106	106
East Asians	0.505	49.75	99	104	102
Finnish		49.456		101	101
Europeans	0.505	49.167	99	99	99
Arctic people	0.505 (estimated from the scores of Mongolians & East Asians)		99		99
Southeast Asians	0.501		93		93
South Asians & North Africans	0.501		93		93
Native Americans	0.494	48.6 (I subtracted 55% white & 15% black admixture since sample was Hispanic)	83	94	89
Papuans	0.498		89		89
Bantu	0.492	46.83(I subtracted 25% white admixture since sample was Black Americans)	80	80	80
pygmies	0.484		68		68
Bushmen	0.482		65		65

Note the PGS(Gwas sig) data is from Table 5 from the paper Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data. The MTAG raw data Piffer used is here:

Since commenter Mugabe keeps mentioning Bermuda as though this tiny island debunks over 100 years of HBD research, I thought it would be a good time to revisit the discussion Mugabe had on this topic with Lion of the Blogosphere. Original discussion can be found here. Note Mugabe is posting under the name “ron burgundy”:

In 2018, people taking DNA tests were measured on four proxies for IQ: education (n = 1.1 million), cognitive test, typically a super quick one ( n = 257,841), self-reported math ability (n = 564,698) and hardest math class completed (n= 430,445). Thousands of genetic variants (SNPs) were discovered and they implicated the brain and neuron to neuron communication (Lee et al., 2018). A total genetic score summarizing all four variables explained 7 to 10% of the variation in cognitive ability (implying a correlation of about 0.3), and 11 to 13% of the variation in education attainment (implying a correlation of 0.35) though that might be inflated by population stratification.

While none of the four phenotypes has a high g loading, you’d expect the total of all four (depending on how they were weighted) to have a reasonable g loading, so why the dismal correlation with genes? After all twin studies promised an adult heritability of 0.75, implying a genotype phenotype correlation of 0.87!

HBD deniers argue the twin studies gave inflated results because identical twins share prenatal effects and were not raised sufficiently apart. HBD proponents claim the twin studies are valid and the missing heritability is hiding in rare genetic variants not sampled by SNPs (single nucleotide polymorphisms).

While scientists are not yet able to predict an individual’s IQ from DNA with any useful certainty, they can predict the average IQ of a group from the average DNA of the group. That’s because error at the individual level cancels out at the group level. So while the above mentioned polygenic score (which Davide Piffer named EA3 PGS) correlates only 0.3 with IQ at the individual level, it correlates 0.985 at the ethnic group level (Piffer 2021).

Further, the correlation can not be dismissed as population stratification unless one believes that the same spurious correlations that hold within Whites (on which the polygenic scores were built) also hold between wildly different ethnic groups reared in the developed World. Of course with only seven data points, we can’t be overly confident in the strength of this correlation if expanded to a larger group of populations, but we can be 95% sure the correlation is at least 0.9.

In March 2024, Piffer and his colleague Emil O. W. Kirkegaard studied the EA3s of 2,625 “European-ish ancient genomes” and produced a most remarkable chart

Eyeballing the above chart, I estimated the EA3 PGSs of each of the historical eras. Unfortunately, I can’t simply apply the line of best fit from figure 9 shown above to these historical eras because Piffer calculates EA3s as Z scores relative to specific data set and thus are incomparable across datasets. Nonetheless, Piffer has confirmed that Upper Paleolithic Europeans have educ-cognitive scores similar to contemporary Africans (Piffer X account, June 6, 2024) On a scale where U.S. & British whites average 100, Europeans average 99 and it’s estimated Black Africans would average 80 if reared in the First World (Lynn 2006). If we thus equate the PGS of Upper Paleolithic Europeans to be equal to 80 and the PGS of contemporary Europeans (1 KG Eur) to 99, we get the following estimates of how each era would score in today’s environment:

Historical era (European-ish)	Estimated average EA3 PGS	Average expected IQ if reared in today’s First World (based on estimated line of best fit)
Upper Paleolithic	-1.6	80
Neolithic	-0.4	91
Copper Age	-0.5	90
Bronze Age	-0.3	92
Iron Age	+0.2	97
Imperial	+0.1	95
Medieval	+0.05	95
Contemporary Europeans (from the 1000 genome study)	+0.5	99

Of course minor fluctuations of a few IQ points here and there are to be expected given sampling errors and should not be over-interpreted. The big takeaway is that average European-ish genetic IQ has been relatively stable over the last few thousand years.

[Update 2025-03-20: An earlier version of this article incorrectly classified 1KG as an agent genome database when in fact it is contemporary]

[Update 2025-04-26: An earlier version of the article incorrectly estimated historical IQs from the line of best fit in figure 9, which can not be done because the historical PGS were calculated with respect to a different data set]