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Record W1488202384 · doi:10.1108/09513551211244124

Swimming against the current

2012· article· en· W1488202384 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Public Sector Management · 2012
Typearticle
Languageen
FieldPsychology
TopicHuman Resource Development and Performance Evaluation
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsTrainerPublic sectorTransfer of trainingTraining (meteorology)Public relationsOriginalityReturn on investmentBusinessValue (mathematics)Investment (military)Training and developmentQualitative researchMarketingPsychologyPolitical scienceManagementSociologyEconomicsPolitics

Abstract

fetched live from OpenAlex

Purpose This paper aims to examine the personal and organisational factors that affected public sector managers' participation in leadership training programmes and their ability to transfer learning to their workplace. Design/methodology/approach In‐depth interviews were conducted with five Canadian and five Northern Irish managers who participated in one‐day leadership training programmes. Findings The uncertain environment throughout the public sector was the greatest inhibitor to training participation and transfer. However, other training characteristics and training design features were also noted (e.g. motivation, trainer influence). Practical implications Public sector organisations must take concrete steps to address current environmental challenges to fully benefit from leadership training programmes. The paper highlights pre‐, during, and post‐training strategies that can be implemented. Originality/value The findings illustrate that leaders in both public sector jurisdictions face similar issues and these have been exacerbated by the current turbulent climate. The authors suggest that to maximise return on training investment the public sector must create an environment supportive of training participation and transfer and suggest recommendations to help organisations in the future. These findings were facilitated by the use of qualitative training evaluation methods, not traditionally used in training transfer research.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.902
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.094
GPT teacher head0.372
Teacher spread0.277 · 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