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Record W2042445563 · doi:10.1080/713755917

On the Cognitive Basis of Observational Learning: Development of Mechanisms for the Detection and Correction of Errors

2000· article· en· W2042445563 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

VenueThe Quarterly Journal of Experimental Psychology Section A · 2000
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsObserver (physics)Systematic errorCognitionTask (project management)Cognitive psychologyPsychologyObservational studyMotor skillError detection and correctionComputer scienceMotor learningObservational learningArtificial intelligenceMachine learningDevelopmental psychologyStatisticsAlgorithmMathematicsMathematics educationNeuroscienceEngineering

Abstract

fetched live from OpenAlex

It has been proposed that observation of a model practising a motor skill results in the observer developing mechanisms for the detection and correction of errors that are similar to those acquired during physical practice. Results of a first experiment indicated that prior observation of a model permitted participants to estimate their errors as efficiently as those who had physically practised the task. Similarly, results of a second experiment indicated that observation of a model receiving biased knowledge of results during practice resulted in similarly biased reference and error detection/correction mechanisms for the observers and for the models. These results suggest that observation engages one in cognitive processes similar to those occurring during physical practice.

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)0.000
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 score0.047
Threshold uncertainty score0.177

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.069
GPT teacher head0.328
Teacher spread0.260 · 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