MétaCan
Menu
Back to cohort
Record W2095027235 · doi:10.1037/a0016795

Seeing meaning in action: A bidirectional link between visual perspective and action identification level.

2009· article· en· W2095027235 on OpenAlexaff
Lisa K. Libby, Eric M. Shaeffer, Richard P. Eibach

Bibliographic record

VenueJournal of Experimental Psychology General · 2009
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAction (physics)Perspective (graphical)PerceptionIdentification (biology)Meaning (existential)PsychologyCognitionCognitive psychologyInterpretation (philosophy)Dimension (graph theory)Relation (database)Social psychologyCognitive scienceComputer scienceArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

Actions do not have inherent meaning but rather can be interpreted in many ways. The interpretation a person adopts has important effects on a range of higher order cognitive processes. One dimension on which interpretations can vary is the extent to which actions are identified abstractly--in relation to broader goals, personal characteristics, or consequences--versus concretely, in terms of component processes. The present research investigated how visual perspective (own 1st-person vs. observer's 3rd-person) in action imagery is related to action identification level. A series of experiments measured and manipulated visual perspective in mental and photographic images to test the connection with action identification level. Results revealed a bidirectional causal relationship linking 3rd-person images and abstract action identifications. These findings highlight the functional role of visual imagery and have implications for understanding how perspective is involved in action perception at the social, cognitive, and neural levels.

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)0.010
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.161
GPT teacher head0.479
Teacher spread0.317 · 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

Citations142
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Experimental Psychology GeneralSame topicAction Observation and SynchronizationFrench-language works237,207