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Hunter-Gatherers and Human Evolution: New Light on Old Debates

2018· article· en· W2886024691 on OpenAlexaff
Richard B. Lee

Bibliographic record

VenueAnnual Review of Anthropology · 2018
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsArgument (complex analysis)AggressionCompetition (biology)EthnographySociologyHuman evolutionHunter-gathererAnthropologyHistoryArchaeologySocial psychologyEcologyPsychology

Abstract

fetched live from OpenAlex

One of the most persistent debates in anthropology and related disciplines has been over the relative weight of aggression and competition versus nonaggression and cooperation as drivers of human behavioral evolution. The literature on hunting and gathering societies—past and present—has played a prominent role in these debates. This review compares recent literature from both sides of the argument and evaluates how accurately various authors use or misuse the ethnographic and archaeological research on hunters and gatherers. Whereas some theories provide a very poor fit with the hunter-gatherer evidence, others build their arguments around a much fuller range of the available data. The latter make a convincing case for models of human evolution that place at their center cooperative breeding and child-rearing, as well as management of conflict, flexible land tenure, and balanced gender relations.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0030.005
Science and technology studies0.0040.028
Scholarly communication0.0090.014
Open science0.0020.004
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.026
GPT teacher head0.426
Teacher spread0.400 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations89
Published2018
Admission routes1
Has abstractyes

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