Genes, Brains, and Culture: Returning to a Darwinian Evolutionary Psychology
Bibliographic record
Abstract
Chisholm's central thesis is that the life histories of individual human beings (i.e., reproductive strategies, speeds of maturation, testosterone levels, mate seeking and risk-taking behaviors?even age at death) are contingent upon stability of parenting. For Chisholm, desirable social-behavior traits, which emphasize long-term and conscientiousness, emerge from a background of predictable attachments, whereas antisocial, impulsive, and self-destructive traits result from unpredictable experiences. As one who early applied r-K life-history theory to human differences (Rushton, 1985), I applaud Chisholm's attempt to understand the particulars of human behavior in terms of the big picture of the evolution of hominoid life cycles. Unfortunately, his book is weakened by its failure to examine the genetic side of the coin. Whether people provide stable environments for their children, or for themselves, and how they react to a variety of stresses and traumas, as well as other challenges and opportunities (even being wounded in combat; see True et al., 1993), is partly a function of the genes they inherit. Unfortunately, Chisholm is at a complete loss on how to unravel the nature-nurture conundrum, describing gene x environment interactions as conceptually vapid and relegating behavior genetic studies to a footnote (p. 71). His take-home message, that mind and morality are mainly a function of the family culture the child grows up in, is the conventional wisdom. Chisholm and I once debated behavioral genetics following his publication in Current Anthropology of an early version of his book (Chisholm, 1993, 1994; Rushton, 1994). It is disappointing that he has still not come to grips with this material. A clue to why is offered by a secondary theme of his book, that there exists an intense moral task of political planning in that governments have a duty to ensure that all people grow to be equally empathic and with equal opportunity to maximize future reproduction (pp. 237-238). Perhaps he believes his political agenda would be compromised by any admission that individual life outcomes are partly due to genetic differences. (He begins his Preface with S. J. Gould's favorite
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".