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Record W4253493584 · doi:10.1108/09670730810911341

Training takes root when the boss has been, too

2008· article· en· W4253493584 on OpenAlexaboutno aff

Bibliographic record

VenueHuman Resource Management International Digest · 2008
Typearticle
Languageen
FieldPsychology
TopicHuman Resource Development and Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsBossOriginalityTraining (meteorology)Value (mathematics)ManagementSoft skillsTransfer of trainingPsychologyPublic relationsPlan (archaeology)Root (linguistics)BusinessOperations managementKnowledge managementSociologySocial psychologyPolitical scienceComputer scienceEngineeringEconomicsCognitive psychology

Abstract

fetched live from OpenAlex

Purpose This paper seeks to understand what contributes to the transfer back to the workplace of soft‐skill leadership training. Design/methodology/approach The study draws on information from a study carried out at Vancouver Island Health Authority, Canada. Findings The paper reveals that the greatest inhibitor to transfer appears to be the fear of breaking cultural norms and the most important remedy, the number of other managers who receive the training. In particular, having one's boss take the same training is strongly associated with post‐training utilization. Practical implications The paper points to the need to plan for the rapid diffusion of training, and for cultural‐change processes to run in parallel with leadership‐development courses. Originality/value The paper shows that some people are motivated to transfer their training back to the workplace because the organization has “invested” in them.

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)0.003
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.003
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0190.003

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 head0.167
GPT teacher head0.339
Teacher spread0.172 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2008
Admission routes1
Has abstractyes

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