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Record W2745335224 · doi:10.1073/pnas.1705910114

A model explaining the matrilateral bias in alloparental investment

2017· article· en· W2745335224 on OpenAlex
Gretchen Perry, Martin Daly

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.

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2017
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsMcMaster UniversityLakehead University
Fundersnot available
KeywordsReceiptRaising (metalworking)Investment (military)Parental investmentFoundation (evidence)PsychologySocial psychologyEconomicsBiologyPolitical scienceGeneticsOffspringPregnancyEngineering

Abstract

fetched live from OpenAlex

Maternal grandmothers invest more in childcare than paternal grandmothers. This bias is large where the expression of preferences is unconstrained by residential and lineage norms, and is detectable even where marriage removes women from their natal families. We maintain that the standard evolutionary explanation, paternity uncertainty, is incomplete, and present an expanded model incorporating effects of alloparents on the mother as well as on her children. Alloparenting lightens a mother's load and increases her residual nepotistic value: her expected fitness from later investments in personal reproduction and in her natal relatives. The mother's mother derives fitness from all such investments, whereas her mother-in-law gains only from further investment in children sired by her son, and thus has less incentive to assist the mother even if paternity is certain. This logic extends to kin other than grandmothers. We generate several hypotheses for future research.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.580

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.236
GPT teacher head0.420
Teacher spread0.184 · 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