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Record W4386244294 · doi:10.1167/jov.23.9.5780

Viewing images with closed eyes diminishes implied social presence

2023· article· en· W4386244294 on OpenAlexaff
Oliver Jacobs, Farid Pazhoohi, Alan Kingstone

Bibliographic record

VenueJournal of Vision · 2023
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAttractivenessEyes openGazePsychologyProsocial behaviorCognitive psychologySocial psychologyPsychoanalysis

Abstract

fetched live from OpenAlex

People perceive the minds of others in depicted faces. For example, "being watched" by photographic eyes can enhance prosocial behaviour. We sought to test whether this effect of implied social presence is greater for open eyes than closed eyes. Using a series of counterbalancing and photoshopped paintings, 48 participants viewed 40 images: original eyes open, photoshopped eyes closed, original eyes closed, and photoshopped eyes open. Participants viewed these images for 10 seconds each while their eyes were monitored by an SMI tracker; and then they rated the attractiveness of the model. We discovered that people spent more time dwelling on bodies than faces when the model's eyes were closed in comparison with when their eyes were open. No differences were found in overt ratings of attraction or between the self-reported gender of participants. These results demonstrate that there is greater objectifying gaze when nude models have their eyes closed suggesting that implied social presence of depicted minds declines when the eyes are closed.

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)0.000
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.049
GPT teacher head0.399
Teacher spread0.349 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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