Participation in Corporate University Training: Its Effect on Individual Job Performance
Bibliographic record
Abstract
Abstract This study investigates the effect of corporate university training on employees' job performance. The popularity of this strategic training approach has grown considerably in both North America and Europe over the last decade; however, no scientific research known by the authors has evaluated the effectiveness of corporate university training on work‐related outcomes. Using a data set of 1,484 employee observations from a Canadian financial institution's computerized personnel files, results from a regression analysis reveal that participation in corporate university training had a relatively small effect on individual job performance after controlling for pre‐training job performance as well as job and individual characteristics. Furthermore, this finding indicates a positive linear relationship between the number of corporate university training courses completed and job performance. Results also show a significant interactive effect of corporate university training and pre‐training job performance on post‐training individual job performance. We discuss theoretical and practical implications as well as limitations and suggestions for future research. Résumé La recherche qui suit est une enquête sur l'impact de la formation de l'université d'entreprise sur la performance des employés. Au cours de la dernière décennie, cette approche stratégique du développement des compétences a connu un succès remarquable en Amérique du Nord et en Europe. Pourtant, à notre connaissance, aucune recherche scientifique n'en évalue l'efficacité sur les indicateurs de la performance au travail. En appliquant l'analyse de régression à 1 484 observations d'employés provenant d'un fichier informatique d'une grande institution bancaire canadienne, l'étude révèle que par rapport à la performance pré‐formation et aux caractéristiques individuelles, la participation à un programme d'université d'entreprise a un impact relativement faible sur la performance individuelle. Les résultats indiquent également qu'il existe une relation linéaire positive entre le nombre de cours complétés avec succès et la performance individuelle. Par ailleurs, l'université d'entreprise et la performance pré‐formation ont un effet interactif remarquable sur la performance individuelle post‐formation. Pour finir, Varticle examine les implications théoriques et pratiques de l'étude, passe en revue ses limites avant de proposer des pistes de recherche future.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".