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Record W2127631587 · doi:10.1111/ijtd.12029

Is transfer of training related to firm performance?

2014· article· en· W2127631587 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 · 2014
Typearticle
Languageen
FieldPsychology
TopicHuman Resource Development and Performance Evaluation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTransfer of trainingTraining (meteorology)Training and developmentTechnology transferJob performanceKnowledge managementBusinessPsychologyComputer scienceManagementSocial psychologyJob satisfaction

Abstract

fetched live from OpenAlex

The purpose of this study was to bridge the gap between micro‐training research on the transfer of training and macro‐training research on training and firm performance by testing the relationship between transfer of training and firm performance. Training and development professionals completed a survey about the training methods used in their organization (on‐the‐job, classroom, computer‐based), the transfer of training, and their firm's performance. The results indicated that transfer of training was positively related to firm performance and mediated the relationship between training methods and firm performance. The results also suggest that among the three training methods, on‐the‐job training was the most strongly related to transfer of training and firm performance. These results highlight the importance of transfer of training for firm performance and suggest that meaningful organizational outcomes can be obtained by implementing training programs and strategies to facilitate and improve the transfer of training.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.701
Threshold uncertainty score1.000

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)0.0010.000

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 head0.083
GPT teacher head0.348
Teacher spread0.265 · 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