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Record W1946767119 · doi:10.22330/001c.89778

Human Life History Dimensions in Reproductive Strategies Are Intuitive Across Cultures

2015· article· en· W1946767119 on OpenAlexaff
Daniel J. Kruger, Maryanne L. Fisher, Charlotte De Backer, Igor Kardum, Martín Tetaz, Sigal Tifferet

Bibliographic record

VenueHuman Ethology · 2015
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsEvolutionary psychologyPsychologyLife history theoryLife historyMatingParental investmentSample (material)Social psychologyPsychological researchDevelopmental psychologyEcologyBiology

Abstract

fetched live from OpenAlex

Psychological research has been criticized for its extensive use of American university students to make broad claims about human psychology and behavior. Critics recommend a broader base of participants because there is substantial variability in experimental results across populations, and North American and Western European psychology pool participants may be outliers in comparison with the rest of the species. This challenge is especially pertinent for claims of species-universal evolved psychological architecture. One such claim has been made regarding recognition of human life history strategies. For example, previous research demonstrates that North American women and men can identify male and female characters with fast (high mating effort, low parental investment) and slow (low mating effort, high parental investment) life history strategies, make accurate predictions about their behavioral tendencies, and respond to them in ways that would facilitate participants’ own reproductive success. The current project validates the understanding of fundamental life history dimensions across a wide range of cultures, therefore supporting the idea that there is a universality in human’s ability to use, and perceive others’ use of, life history strategies. Results for each language sample replicated patterns from North American participants. Ratings for characters clustered into two dimensions, mating effort and parental investment. Items most central to the theoretical constructs had the highest factor loadings.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.184
GPT teacher head0.448
Teacher spread0.264 · 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 teacher head, not a consensus.

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

Citations15
Published2015
Admission routes1
Has abstractyes

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