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Record W2948836041

Time Estimation During Mutual Eye Gaze

2017· article· en· W2948836041 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

VenueStudent Research Proceedings · 2017
Typearticle
Languageen
FieldPsychology
TopicPsychological and Temporal Perspectives Research
Canadian institutionsMacEwan University
Fundersnot available
KeywordsGazeEye contactPerceptionPsychologyFace (sociological concept)Eye trackingCognitive psychologyEye movementSocial psychologyCommunicationComputer visionComputer scienceNeuroscienceSociology
DOInot available

Abstract

fetched live from OpenAlex

Eye contact requires attention both when we send and receive gaze signals. Previous research suggests that when one is attending to something their perception of time is altered, such that time passes by more slowly while watching a pot boil. The disruption of time perception has been shown to happen during face-to-face eye contact but has also been observed (albeit to a lesser extent) if one person is looking at another or being looked at by another [Jarick et al., 2016]. Here, we aimed to tease apart whether eye contact is more attention-capturing when we are sending signals during mutual gaze or receiving the gaze signal, or both. This will be investigated by having pairs of participants (sitting side-by-side) make subjective time estimates of 40, 60, and 80 seconds during the participation of four gaze trials: looking away from one another (baseline), looking at the profile of their partner, being looked at by their partner and making eye contact. If attention is equally attributed to sending and receiving signals, we predict that the degree to which time estimation is disrupted during the profile and looked at trials will sum to the disruption found during eye contact trials. Alternatively, if attention is captured more by sending or receiving gaze signals, then we should see time estimation more disrupted in either the profile or looked at trials. This research will allow us to further understand how attention is allocated during face-to-face eye contact in the wild. Discipline: Psychology Faculty Mentor: Dr. Michelle Jarick

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.398
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.009

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 head0.208
GPT teacher head0.555
Teacher spread0.347 · 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