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Record W3130845397 · doi:10.1177/0301006621991320

Color Judgments of #The Dress and #The Jacket in a Sample of Different Cultures

2021· article· en· W3130845397 on OpenAlexaff
Yayoi Kawasaki, J. Reid, Kazuhiro Ikeda, Bodil S. A. Karlsson

Bibliographic record

VenuePerception · 2021
Typearticle
Languageen
FieldPsychology
TopicColor perception and design
Canadian institutionsWestern University
Fundersnot available
KeywordsPerceptionPsychologyWhite (mutation)ChinaSocial psychologySample (material)GeographyBiology

Abstract

fetched live from OpenAlex

Two viral photographs, #The Dress and #The Jacket, have received recent attention in research on perception as the colors in these photos are ambiguous. In the current study, we examined perception of these photographs across three different cultural samples: Sweden (Western culture), China (Eastern culture), and India (between Western and Eastern cultures). Participants also answered questions about gender, age, morningness, and previous experience of the photographs. Analyses revealed that only age was a significant predictor for the perception of The Dress, as older people were more likely to perceive the colors as blue and black than white and gold. In contrast, multiple factors predicted perception of The Jacket, including age, previous experience, and country. Consistent with some previous research, this suggests that the perception of The Jacket is a different phenomenon from perception of The Dress and is influenced by additional factors, most notably culture.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.029
GPT teacher head0.325
Teacher spread0.297 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2021
Admission routes1
Has abstractyes

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