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Record W2159510617 · doi:10.1037/a0031138

Failures to replicate hyper-retrieval-induced forgetting in arithmetic memory.

2013· article· en· W2159510617 on OpenAlexafffund
Anna J. Maslany, Jamie I. D. Campbell

Bibliographic record

VenueCanadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale · 2013
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsForgettingRetrieval-induced forgettingMultiplication (music)ReplicateReplication (statistics)ArithmeticComputer sciencePsychologyMathematicsCognitive psychologyStatisticsCombinatorics

Abstract

fetched live from OpenAlex

Campbell and Phenix (2009) observed retrieval-induced forgetting (slower response time) for simple addition facts (e.g., 3 + 4) immediately following 40 retrieval-practice blocks of their multiplication counterparts (3 × 4 = ?). A subsequent single retrieval of the previously unpracticed multiplication problems, however, produced an retrieval-induced forgetting (RIF) effect about twice as large for their addition counterparts. Thus, a single retrieval of a multiplication fact appeared to produce much larger RIF of the addition counterpart than did many multiplication retrieval-practice trials. In several subsequent similar studies, however, we failed to observe this hyper-RIF effect. Here, we attempted an exact replication of the Campbell and Phenix experiment, but found no evidence of hyper-RIF. We conclude that the hyper-RIF effect reported by Campbell and Phenix is an elusive phenomenon; consequently, it cannot at this time be considered an important result in the RIF literature.

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 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)0.001
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 score0.038
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.070
GPT teacher head0.331
Teacher spread0.261 · 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 teacher head, not a consensus.

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

Citations7
Published2013
Admission routes2
Has abstractyes

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