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Data_Sheet_3_Assortative mate preferences for height across short-term and long-term relationship contexts in a cross-cultural sample.DOCX

2022· dataset· en· W6927510791 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2022
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInfections and bacterial resistance
Canadian institutionsnot available
Fundersnot available
KeywordsAssortative matingMate choiceContext (archaeology)Sexual selectionPreferenceSample (material)Similarity (geometry)Mating

Abstract

fetched live from OpenAlex

<p>Height preferences reflecting positive assortative mating for height—wherein an individual’s own height positively predicts the preferred height of their mate—have been observed in several distinct human populations and are thought to increase reproductive fitness. However, the extent to which assortative preferences for height differ strategically for short-term versus long-term relationship partners, as they do for numerous other indices of mate quality, remains unclear. We explore this possibility in a large representative sample of over 500 men and women aged 15–77 from Canada, Cuba, Norway and the United States. Participants’ own heights were measured, and they indicated their height preferences for a long-term and short-term mate using graphic stimuli containing metric indices. Replicating the “male-taller norm,” participants on average preferred taller-than-average male mates, and shorter-than-average female mates. Positive assortative preferences for height were observed across sexes and samples, however the strength of these height preferences varied with relationship context for men, and not for women. Taller men preferred relatively shorter women for short-term relationships than for long-term relationships, indicating stronger assortative preferences for height in a long-term context. These results provide preliminary evidence that, in addition to mate preferences for other physical traits related to mate quality such as masculinity in the body, face, and voice, assortative preferences for height do vary as a function of expected relationship length, but this was surprisingly only observed in preferences for female height.</p>

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)0.000
metaresearch head score (Gemma)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.231
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0320.000

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 head0.053
GPT teacher head0.370
Teacher spread0.316 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2022
Admission routes1
Has abstractyes

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