The Epigenome and Nature/Nurture Reunification: A Challenge for Anthropology
Bibliographic record
Abstract
Recognition among molecular biologists of variables external to the body that can bring about hereditable changes in gene expression or cellular phenotypes has reignited nature/nurture discussion. These epigenetic findings may well set off a new round of somatic reductionism because research is confined largely to the molecular level. A brief review of the late nineteenth-century formulation of the nature/nurture concept is followed by a discussion of the positions taken by Boas and Kroeber on this matter. I then illustrate how current research into Alzheimer's disease uses a reductionistic approach, despite epigenetic findings in this field that make the shortcomings of reductionism clear. In order to transcend the somatic reductionism associated with epigenetics, drawing on concepts of local biologies and embedded bodies, anthropologists can carry out research in which epigenetic findings are contextualized in the specific historical, socio/political, and environmental realities of lived experience.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".