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Record W2062650493 · doi:10.1080/01494929.2010.543038

Impact of Self-Descriptions and Photographs on Mediated Dating Interest

2010· article· en· W2062650493 on OpenAlex
Jan de Vries

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

VenueMarriage & Family Review · 2010
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsTrinity College
Fundersnot available
KeywordsPreferenceContrast (vision)PsychologyComputer scienceStatisticsArtificial intelligence

Abstract

fetched live from OpenAlex

This simulated dating experiment addresses the relative impact of photographs and self-descriptions on dating interest in White students in Los Angeles (n = 223). A previous study demonstrated that self-descriptions had little impact on dating success. This was attributed to obstacles in inspection and processing time, primacy effects, information overload, interference, mental discomfort, and low variability in descriptions. The present study controlled for these factors. Results show that for men the self-descriptions were half as important as the photographs, whereas for women the impact of the descriptions was equal to the photographs. This article includes a discussion of the contrast between findings in research on mating preference and actual dating studies, and the implications of its findings for dating and the dating industry.

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 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 score0.419
Threshold uncertainty score0.995

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.069
GPT teacher head0.386
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