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Record W2886487377 · doi:10.1073/pnas.1808418115

Invariances in the architecture of pride across small-scale societies

2018· article· en· W2886487377 on OpenAlexaff
Daniel Sznycer, Dimitris Xygalatas, Sarah Alami, Xiao-Fen An, K.I. Ananyeva, Shintaro Fukushima, Hidefumi Hitokoto, А.Н. Харитонов, Jeremy Koster, Charity N. Onyishi, Ike E. Onyishi, Pedro Romero, Kosuke Takemura, Jin-Ying Zhuang, Leda Cosmides, John Tooby

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2018
Typearticle
Languageen
FieldPsychology
TopicEmotions and Moral Behavior
Canadian institutionsUniversité de Montréal
FundersJohn Templeton Foundation
KeywordsPrideScale (ratio)ArchitectureAction (physics)Subsistence agricultureAdaptation (eye)DeferenceValuation (finance)SociologyEcologySocial psychologyGeographyPsychologyEconomicsPolitical scienceLawBiologyCartographyAgriculture

Abstract

fetched live from OpenAlex

Significance It has been proposed that one key function of pride is to guide behavior in ways that would increase others’ valuation of the individual. To incline choice, the pride system must compute for a potential action an anticipated pride intensity that tracks the magnitude of the approval or deference that the action would generate among local audiences. Data from industrial mass societies support this expectation. However, it is presently not known whether those data reflect cultural evolutionary processes or a panhuman adaptation. Experiments conducted in 10 traditional small-scale societies with widely varying cultures and subsistence modes replicate the pattern observed in mass societies. This suggests that pride is a universal system that is part of our species’ cooperative biology.

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)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.003
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.092
GPT teacher head0.386
Teacher spread0.294 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations97
Published2018
Admission routes1
Has abstractyes

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