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Record W801712705 · doi:10.1037/xhp0000090

Confirmation bias in visual search.

2015· article· en· W801712705 on OpenAlexaff
Jason Rajsic, Daryl E. Wilson, Jay Pratt

Bibliographic record

VenueJournal of Experimental Psychology Human Perception & Performance · 2015
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsQueen's UniversityUniversity of Toronto
Fundersnot available
KeywordsSelection (genetic algorithm)Matching (statistics)PsycINFOVisual searchCognitionComputer scienceCognitive psychologyConfirmation biasSelection biasCognitive biasPsychologyInformation retrievalArtificial intelligenceSocial psychologyMEDLINENeuroscienceMathematics

Abstract

fetched live from OpenAlex

In a series of experiments, we investigated the ubiquity of confirmation bias in cognition by measuring whether visual selection is prioritized for information that would confirm a proposition about a visual display. We show that attention is preferentially deployed to stimuli matching a target template, even when alternate strategies would reduce the number of searches necessary. We argue that this effect is an involuntary consequence of goal-directed processing, and show that it can be reduced when ample time is provided to prepare for search. These results support the notion that capacity-limited cognitive processes contribute to the biased selection of information that characterizes confirmation bias. (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.

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)0.003
metaresearch head score (Gemma)0.030
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 score0.004
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.452
GPT teacher head0.511
Teacher spread0.060 · 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

Citations53
Published2015
Admission routes1
Has abstractyes

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