Essay Review: Criticism: Fair and Foul, Mostly Foul
Bibliographic record
Abstract
Noble Savages: My Life among Two Dangerous Tribes—The Yanomamö and the Anthropologists by Napoleon A. Chagnon Darkness’s Descent on the American Anthropological Association—A Cautionary Tale by Alice Dreger The Controversy Surrounding The Man Who Would Be Queen: A Case History of the Politics of Science, Identity, and Sex in the Internet Age by Alice D. Dreger Anomalists know that being criticized goes with their territory, and that at times it is less substantive and more personally derogatory. But the same thing can be said about many controversies within mainstream disciplines. One instance concerns the anthropologist Napoleon Chagnon, who had studied isolated tribes in the Amazon, the Yanomamö, for about a quarter of a century when he came to national attention through being charged with major malfeasance, including responsibility for a measles epidemic fatal to many natives. The charges came in an article by Patrick Tierney (2000), soon followed and augmented by Tierney’s book-length disquisition (2001). The media coverage and reports of investigations by the American Anthropological Association left the clear impression that Chagnon had behaved badly and unprofessionally. Certainly that had been my own recollection, and a book review (Povinelli 2013) of Chagnon’s recent memoir, Noble Savages, did nothing to change that impression. However, this book review seemed so mean-spirited, and its accusations were so broad-brush and non-specific, that I resolved to read the memoir and try to make up my own mind.
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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 | 0.007 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.015 | 0.009 |
| Insufficient payload (model declined to judge) | 0.038 | 0.028 |
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".