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Understanding frame‐of‐reference training success: a social learning theory perspective

2007· article· en· W2047677807 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

VenueInternational Journal of Training and Development · 2007
Typearticle
Languageen
FieldPsychology
TopicHuman Resource Development and Performance Evaluation
Canadian institutionsUniversity of CalgaryWilfrid Laurier University
Fundersnot available
KeywordsPerspective (graphical)Training (meteorology)Control (management)Relational frame theoryFrame (networking)Protocol (science)PsychologyApplied psychologyLearning theoryComputer scienceArtificial intelligenceCognitive psychologyMedicine

Abstract

fetched live from OpenAlex

Employing the social learning theory (SLT) perspective on training, we analysed the effects of alternative frame‐of‐reference (FOR) training protocols on various criteria of training effectiveness. Undergraduate participants ( N = 65) were randomly assigned to one of four FOR training conditions and a control condition. Training effectiveness was determined via trainee reactions, learning and rating accuracy. The results partially supported the study hypotheses: compared to the control group, the more comprehensive FOR training conditions evidenced: (1) significantly higher rating accuracy; (2) significantly higher levels of learning; and (3) more favorable reactions to the training. The discussion focuses on the implications of the results for protocol development when designing FOR training programs.

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)0.003
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score0.507

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.296
GPT teacher head0.415
Teacher spread0.119 · 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