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True Photographs and False Memories

2004· article· en· W2138953586 on OpenAlexaff
D. Stephen Lindsay, Lisa Hagen, J. Don Read, Kimberley A. Wade, Maryanne Garry

Bibliographic record

VenuePsychological Science · 2004
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPsychologyFalse memoryCognitive psychologyRecall

Abstract

fetched live from OpenAlex

Some trauma-memory-oriented psychotherapists advise clients to review old family photo albums to cue suspected "repressed" memories of childhood sexual abuse. Old photos might cue long-forgotten memories, but when combined with other suggestive influences they might also contribute to false memories. We asked 45 undergraduates to work at remembering three school-related childhood events (two true events provided by parents and one pseudoevent). By random assignment, 23 subjects were also given their school classes' group photos from the years of the to-be-recalled events as memory cues. As predicted, the rate of false-memory reports was dramatically higher in the photo condition than in the no-photo condition. Indeed, the rate of false-memory reports in the photo condition was substantially higher than the rate in any previously published study.

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)0.005
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.057
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.064
GPT teacher head0.364
Teacher spread0.300 · 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 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

Citations261
Published2004
Admission routes1
Has abstractyes

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