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Record W4300690090 · doi:10.1002/wcs.1621

Autobiographical memory and the self: A transition theory perspective

2022· article· en· W4300690090 on OpenAlexafffund
Norman Brown

Bibliographic record

VenueWiley Interdisciplinary Reviews Cognitive Science · 2022
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAutobiographical memoryPerspective (graphical)Transition (genetics)Event (particle physics)Cognitive psychologyRepresentation (politics)PsychologyRelation (database)Self representationCognitive scienceEpisodic memoryEpistemologyComputer scienceCognitionArtificial intelligencePhilosophyRecall

Abstract

fetched live from OpenAlex

In contrast to much theoretical work on the topic, Transition Theory (Brown, 2016, 2021) attempts to account for important aspects of autobiographical memory in a way that emphasizes the structure of experience, rather than the relation between personal-event memories and the Self. This article provides the rationale for adopting this minimalist stance. Here it is argued that: (a) an all-inclusive notion of the Self is of little utility to the study of autobiographical memory because virtually all sentient goal-directed activities can be seen as reflecting the Self, hence, adopting this view provides no bias for predicting event memorability; (b) although some event memories are clearly Self-relevant (e.g., life-story events, turning points, self-defining memories), most are not; (c) the formation of and access to Self-knowledge typically does not depend on the availability of specific autobiographical memories; rather, (d) Self-knowledge is generally derived from massive amounts of readily forgotten role-relevant experience. This article is categorized under: Philosophy > Representation Philosophy > Knowledge and Belief Psychology > Memory.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.011
Scholarly communication0.0030.006
Open science0.0010.002
Research integrity0.0010.002
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 head0.021
GPT teacher head0.352
Teacher spread0.331 · 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 designTheoretical or conceptual
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

Citations11
Published2022
Admission routes2
Has abstractyes

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Same venueWiley Interdisciplinary Reviews Cognitive ScienceSame topicIdentity, Memory, and TherapyFrench-language works237,207