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Record W2166120171 · doi:10.1111/1467-8721.01228

Autobiographical Memory and Conceptions of Self

2003· article· en· W2166120171 on OpenAlexaff
Michael G. Ross, Anne E. Wilson

Bibliographic record

VenueCurrent Directions in Psychological Science · 2003
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsWilfrid Laurier UniversityUniversity of Waterloo
Fundersnot available
KeywordsPsychologyFeelingPraiseAutobiographical memoryHarmSocial psychologySelfCognitive psychologyPsychology of selfSelf-enhancementRecall

Abstract

fetched live from OpenAlex

We examine links between self-assessment and autobiographical memory. People generally view themselves as improving over time, relative to their peers. We suggest that this sense of improvement is sometimes illusory, and motivated by the desire to enhance the current self. Our research focuses on people's subjective feeling of temporal distance between an earlier period and the present, a feeling that is only modestly associated with actual time. Research participants praise or criticize the same former self, depending on how far away it feels. An equally distant episode feels close or remote, depending on whether it has favorable or damaging implications for evaluations of the current self. The identical achievement boosts evaluations of the current self or has little impact, depending on how far away it feels. The same failure does or does not harm appraisals of the current self, depending on how far away it feels.

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)0.002
metaresearch head score (Gemma)0.014
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.004
Scholarly communication0.0040.005
Open science0.0010.002
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 head0.051
GPT teacher head0.422
Teacher spread0.371 · 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

Citations174
Published2003
Admission routes1
Has abstractyes

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