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Record W4287578766 · doi:10.1037/bul0000360

The enactment effect: A systematic review and meta-analysis of behavioral, neuroimaging, and patient studies.

2022· review· en· W4287578766 on OpenAlexafffund
Brady R. T. Roberts, Colin M. MacLeod, Myra A. Fernandes

Bibliographic record

VenuePsychological Bulletin · 2022
Typereview
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPsychologyNeuroimagingCognitive psychologyMeta-analysisAction (physics)Reading (process)Functional neuroimagingTask (project management)CognitionNeuroscienceMedicineLinguistics

Abstract

fetched live from OpenAlex

= 1.23. Further meta-analyses revealed that variations in study design and comparison task reliably influence the size of the enactment effect, whereas four other experiment factors-test format, learning instruction type, retention interval, and the presence of objects during encoding-likely do not influence the effect. Neuroimaging studies demonstrated enactment-related activation to be prevalent in the motor cortex and inferior parietal lobule. Patient studies indicated that, regardless of whether impairments of memory (e.g., Alzheimer's) or of motor capability (e.g., Parkinson's) were present, patients were able to benefit from enactment. The findings of this systematic review and meta-analysis highlight two components accounting for the memory benefit from enactment: a primary mental contribution relating to planning the action and a secondary physical contribution of the action itself. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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)0.013
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.028
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0090.019
Bibliometrics0.0060.006
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
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 head0.270
GPT teacher head0.472
Teacher spread0.202 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations35
Published2022
Admission routes2
Has abstractyes

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