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Record W2108779329 · doi:10.1177/0265407514529068

Brides and young couples

2014· article· en· W2108779329 on OpenAlexaff
Ivanka Prichard, Janet Polivy, Véronique Provencher, C. Peter Herman, Marika Tiggemann, Kathleen Cloutier

Bibliographic record

VenueJournal of Social and Personal Relationships · 2014
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsUniversité LavalUniversity of Toronto
Fundersnot available
KeywordsAssortative matingPhysical attractivenessPsychologyRomanceSimilarity (geometry)AttractivenessMate choiceSocial psychologyDevelopmental psychologyMatingSexual selectionSelection (genetic algorithm)ZoologyBiology

Abstract

fetched live from OpenAlex

Mate selection seems to be based to some extent on appearance and physique. Assortative mating suggests that romantic partners select each other based on their similarity in important characteristics. Two studies examined the similarity in physiques of members of romantic couples. Study 1 found that the physical measurements of brides-to-be were positively correlated with those of their fiancés, although the brides were lighter and shorter than their partners. The exception was that brides who lost weight before their wedding initially had body mass indexes (BMIs) very similar to their partners. Study 2 also found similarity in weight and BMI between university couple partners. Partners’ ratings of the participants’ physical attractiveness were higher than participants’ own self-ratings, particularly for females. Romantic couples were thus similar in physique and share the same (inaccurate) view of their partners’ height and weight. These findings support assortative mating and highlight the importance of weight in the partner selection process.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.082
GPT teacher head0.342
Teacher spread0.261 · 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

Citations8
Published2014
Admission routes1
Has abstractyes

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