Behavioral Data, Cultural Group Selection, and Genetics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Kasser et al. pose an important and often unaddressed question: how do different institutional forms, or economic systems, shape the ideas, values, beliefs, motivations, and practices of their members or participants.(also see Bowles, 1998). While I applaud their efforts in opening up this line, I offer two concerns. First, Kasser et al. neglected two large-scale comparative projects that directly test their principle hypotheses and arrive at quite different conclusions. Second, much of their evidence involves relationships among variables drawn from samples within one ACC populations, yet their hypotheses seem to demand comparisons among populations with differing exposure to ACC institutions. This may have resulted in faulty causal inferences. The authors hypothesize that ACC institutions, collectively forming the capitalist economic system, favor the transmission of cultural representations that promotes self-interest, competition, and materialism, while suppressing the acquisition of representations related to altruism, fairness, cooperation and numerous aspects of psychological well-being. In my view, the proper test of such hypotheses would involve a systematic comparative study, preferably using behavioral measures of self-interest, fairness, etc., from popula-tions with differing degrees of exposure to ACC institutions. It happens that my colleagues and I, over the last decade, have run two such projects, deploying behavioral experiments among 15 diverse populations drawn from some of the remotest corners of
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it