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Record W2896284577 · doi:10.1371/journal.pone.0205830

Social modulation of object-directed but not image-directed actions

2018· article· en· W2896284577 on OpenAlexafffund
Jill A. Dosso, Alan Kingstone

Bibliographic record

VenuePLoS ONE · 2018
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaUniversity of British Columbia
KeywordsAffordanceCognitive psychologyStimulus (psychology)PsychologySocial cognitionCognitionComputer scienceCommunicationSocial psychologyNeuroscience

Abstract

fetched live from OpenAlex

There has recently been an increased research focus on the influence of social factors on human cognition, attention, and action. While this represents an important step towards an ecologically valid description of real-world behaviour, this work has primarily examined dyads interacting with virtual stimuli i.e. on-screen images of objects. Though differences between actions to images and real items are known, their relative sensitivity to social factors is largely unknown. We argue that because images and real items elicit different neural representations, patterns of attention, and hand actions, a direct comparison between the magnitude of social effects while interacting with images and real objects is demanded. We examined patterns of reaching as individuals performed a shape-matching game. Images and real objects were used as stimuli, and social context was manipulated via the proximity of an observer. We found that social context interacted with stimulus type to modulate behaviour. Specifically, there was a delay in reaching for distant objects when a participant was facing another individual but this social effect only occurred when the stimuli were real objects. Our data suggest that even when images and real objects are arranged to share the affordance of reachability, they differ in their sensitivity to social influences. Therefore, the measurement of social effects using on-screen stimuli may poorly predict the social effects of actions directed towards real objects. Accordingly, generalizations between these two domains should be treated with caution.

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 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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.823
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.120
GPT teacher head0.330
Teacher spread0.210 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations8
Published2018
Admission routes2
Has abstractyes

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