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Record W2626976220 · doi:10.1037/cep0000117

Staring reality in the face: A comparison of social attention across laboratory and real world measures suggests little common ground.

2017· article· en· W2626976220 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCanadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsMcGill University
FundersSocial Sciences and Humanities Research CouncilNatural Sciences and Engineering Research Council of Canada
KeywordsCovertPsychologyOperationalizationPsycINFOCognitive psychologyGazeTask (project management)Social psychologyEcological validitySocial cognitionStaringContext (archaeology)Joint attentionCognitionDevelopmental psychologyCommunication

Abstract

fetched live from OpenAlex

The ability to attend to someone else's gaze is thought to represent one of the essential building blocks of the human sociocognitive system. This behavior, termed social attention, has traditionally been assessed using laboratory procedures in which participants' response time and/or accuracy performance indexes attentional function. Recently, a parallel body of emerging research has started to examine social attention during real life social interactions using naturalistic and observational methodologies. The main goal of the present work was to begin connecting these two lines of inquiry. To do so, here we operationalized, indexed, and measured the engagement and shifting components of social attention using covert and overt measures. These measures were obtained during an unconstrained real-world social interaction and during a typical laboratory social cuing task. Our results indicated reliable and overall similar indices of social attention engagement and shifting within each task. However, these measures did not relate across the two tasks. We discuss these results as potentially reflecting the differences in social attention mechanisms, the specificity of the cuing task's measurement, as well as possible general dissimilarities with respect to context, task goals, and/or social presence. (PsycINFO Database Record

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.464
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.241
GPT teacher head0.462
Teacher spread0.221 · 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