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Record W2253944897 · doi:10.1037/xlm0000230

Dissociating appraisals of accuracy and recollection in autobiographical remembering.

2016· article· en· W2253944897 on OpenAlexaff
Alan Scoboria, Lisa Pascal

Bibliographic record

VenueJournal of Experimental Psychology Learning Memory and Cognition · 2016
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsRecallAutobiographical memoryPsychologyCognitive psychologyPsycINFODissociation (chemistry)Developmental psychologyMEDLINE

Abstract

fetched live from OpenAlex

Recent studies of metamemory appraisals implicated in autobiographical remembering have established distinct roles for judgments of occurrence, recollection, and accuracy for past events. In studies involving everyday remembering, measures of recollection and accuracy correlate highly (>.85). Thus although their measures are structurally distinct, such high correspondence might suggest conceptual redundancy. This article examines whether recollection and accuracy dissociate when studying different types of autobiographical event representations. In Study 1, 278 participants described a believed memory, a nonbelieved memory, and a believed-not-remembered event and rated each on occurrence, recollection, accuracy, and related covariates. In Study 2, 876 individuals described and rated 1 of these events, as well as an event about which they were uncertain about their memory. Confirmatory structural equation modeling indicated that the measurement dissociation between occurrence, recollection and accuracy held across all types of events examined. Relative to believed memories, the relationship between recollection and belief in accuracy was meaningfully lower for the other event types. These findings support the claim that recollection and accuracy arise from distinct underlying mechanisms. (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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.226

Codex and Gemma teacher scores by category

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

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 head0.044
GPT teacher head0.363
Teacher spread0.319 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations15
Published2016
Admission routes1
Has abstractyes

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