MétaCan
Menu
Back to cohort
Record W2801632303 · doi:10.1177/1474704918769417

Displaying Red and Black on a First Date: A Field Study Using the “First Dates” Television Series

2018· article· en· W2801632303 on OpenAlex

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

VenueEvolutionary Psychology · 2018
Typearticle
Languageen
FieldPsychology
TopicColor perception and design
Canadian institutionsTrent University
Fundersnot available
KeywordsClothingAttractivenessContext (archaeology)Television seriesPsychologyAdvertisingGeographySociologyMedia studies

Abstract

fetched live from OpenAlex

Previous research has shown that displaying the color red can increase attractiveness. As a result, women display red more often when expecting to meet more attractive men in a laboratory context. Here, we carried out a field study by analyzing 546 daters from the "First Dates" television series. Each participant was filmed in a pre-date interview and during a real first date, allowing direct comparison of the clothing worn by each person in these two contexts. Analysis of ratings of the amount of red displayed showed that both men and women wore more red clothing during their dates. This pattern was even stronger for black clothing, while the amount of blue clothing did not differ across the two contexts. Our results provide the first real-world demonstration that people display more red and black clothing when meeting a possible mate for the first time, perhaps seeking to increase their attractiveness and/or reveal their intentions to potential partners.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.063
GPT teacher head0.380
Teacher spread0.317 · 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