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Record W1979041654 · doi:10.1080/00221300109598912

Effects of Free and Forced Retrieval Instructions on False Recall and Recognition

2001· article· en· W1979041654 on OpenAlex
Stuart J. McKelvie

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of General Psychology · 2001
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsBishop's University
Fundersnot available
KeywordsRecallFree recallRecall testTwo-alternative forced choicePsychologyTest (biology)Artificial intelligenceComputer scienceCognitive psychologyNatural language processing

Abstract

fetched live from OpenAlex

One hundred undergraduates heard 6 lists of 14 words that were each associated with 1 of 6 central concepts not on the lists (the DRMRS procedure). The participants were instructed to recall as many words as possible (free retrieval) or to fill all 14 spaces (forced retrieval) and were subsequently given a recognition test. False recall and recognition of the critical central concepts were higher with forced than with free retrieval instructions, but correct recall and recognition were not affected. Confidence was lower for false than for correct recall and recognition. Confidence was also lower with forced than with free retrieval instructions for false recall but not for false recognition. The DRMRS procedure easily elicited false memories, but confidence judgments helped more in detecting them in recall than in recognition. Theoretical and applied implications are discussed.

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.

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 score0.096
Threshold uncertainty score0.161

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 head0.053
GPT teacher head0.328
Teacher spread0.275 · 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