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Record W3115598276 · doi:10.1002/acp.3781

Does generation benefit learning for narrative and expository texts? A direct replication attempt

2020· article· en· W3115598276 on OpenAlexaff
Julia Schindler, Tobias Richter, Raymond A. Mar

Bibliographic record

VenueApplied Cognitive Psychology · 2020
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsYork University
FundersDeutsche Forschungsgemeinschaft
KeywordsGermanPsychologyReplication (statistics)Task (project management)CognitionCognitive psychologyNarrativeReplicateCognitive scienceLinguisticsNatural language processingComputer science

Abstract

fetched live from OpenAlex

Abstract Generated information is better recognized and recalled than information that is read. This so‐called generation effect has been replicated several times for different types of material, including texts. Perhaps the most influential demonstration was by McDaniel et al. (1986, Journal of Memory and Language , 25 , 645–656; henceforth MEDC). This group tested whether the generation effect occurs only if the generation task stimulates cognitive processes not already stimulated by the text. Numerous studies, however, report difficulties replicating this text by generation‐task interaction, which suggests that the effect might only be found under conditions closer to the original method of MEDC. To test this assumption, we will closely replicate MEDC's Experiment 2 in German and English‐speaking samples. Replicating the effect would suggest that it can be reproduced, at least under limited conditions, which will provide the necessary foundation for future investigations into the boundary conditions of this effect, with an eye towards its utility in applied contexts.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.060
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.068
GPT teacher head0.340
Teacher spread0.272 · 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.

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

Citations0
Published2020
Admission routes1
Has abstractyes

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