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Record W2890290588 · doi:10.1126/sciadv.aat2201

The origins of human prosociality: Cultural group selection in the workplace and the laboratory

2018· article· en· W2890290588 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueScience Advances · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicExperimental Behavioral Economics Studies
Canadian institutionsUniversity of British ColumbiaCanadian Institute for Advanced Research
FundersSocial Sciences and Humanities Research Council of CanadaInstitut Universitaire de FranceCanadian Institute for Advanced Research
KeywordsSelection (genetic algorithm)Group (periodic table)Competition (biology)Group selectionPsychologySocial psychologyBiologyEcologyChemistryComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Human prosociality toward nonkin is ubiquitous and almost unique in the animal kingdom. It remains poorly understood, although a proliferation of theories has arisen to explain it. We present evidence from survey data and laboratory treatment of experimental subjects that is consistent with a set of theories based on group-level selection of cultural norms favoring prosociality. In particular, increases in competition increase trust levels of individuals who (i) work in firms facing more competition, (ii) live in states where competition increases, (iii) move to more competitive industries, and (iv) are placed into groups facing higher competition in a laboratory experiment. The findings provide support for cultural group selection as a contributor to human prosociality.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.702
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.013
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.383
Teacher spread0.359 · 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