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Record W2011120998 · doi:10.1080/09658210344000161

False memory across languages: Implicit associative response vs fuzzy trace views

2004· article· en· W2011120998 on OpenAlex

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

VenueMemory · 2004
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFalse memoryPsychologyTRACE (psycholinguistics)Associative propertyCognitive psychologySemantic memoryWord (group theory)Test (biology)LinguisticsCognitionRecall

Abstract

fetched live from OpenAlex

We investigated false recognition across languages using the Deese-Roediger-McDermott (DRM) paradigm. A group of English-French bilinguals studied lists of converging associates, some lists in English and some in French, and then performed a recognition test containing studied list items and nonstudied critical lures whose language matched or mismatched the language at study. Participants were instructed to answer old only if the test cue was in the same language as the studied word. The results yielded a robust false memory rate both within-language and across-languages. The effect of the study-test language shift was much larger for list items than for critical lures. This finding suggests that memory representations for critical lures contain primarily semantic gist traces and little surface information, and hence is more consistent with the fuzzy trace view than with the implicit associative response view. In sum, the study demonstrates the existence of false memory across languages, and provides information about the memory traces underlying veridical and illusory recognition.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.016
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.045
GPT teacher head0.350
Teacher spread0.305 · 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