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Record W3036245928 · doi:10.1002/acp.3713

Defending or relinquishing belief in occurrence for remembered events that are challenged: A social‐cognitive model

2020· article· en· W3036245928 on OpenAlexaff
Alan Scoboria, Linda A. Henkel

Bibliographic record

VenueApplied Cognitive Psychology · 2020
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsCognitive dissonanceIntrapersonal communicationPsychologyInterpersonal communicationRecallSelf-justificationCognitionSocial psychologyCognitive psychologyEvent (particle physics)Self-perception theoryAutobiographical memory

Abstract

fetched live from OpenAlex

Summary We describe a social‐cognitive model explaining processing of cognitive dissonance resulting from being told by someone that a vividly remembered event did not actually occur. The model proposes that receiving challenges to one's recollection of events results in both intrapersonal and interpersonal cognitive dissonance. Rememberers process intrapersonal dissonance by weighing features of memory representations against the qualities of the feedback, and they process interpersonal elements by weighing the potential costs of agreeing or disagreeing with the challenger within the social dynamics of the relationship. To resolve the dissonance, people will either maintain or reduce belief in occurrence for the event, and will agree or disagree with the challenger. We explore factors that can influence dissonance and how they impact the rememberers' beliefs in occurrence of the event and their interaction with challengers in terms of defending or relinquishing their memory, and we discuss preliminary data confirming some of these factors.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.463
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.353
GPT teacher head0.418
Teacher spread0.065 · 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

Citations19
Published2020
Admission routes1
Has abstractyes

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