Who benefits from firm-sponsored training?
Notice bibliographique
Résumé
ProsWorkers undertaking firm-sponsored training improve their skills and receive higher wages as a result.Firm-sponsored training increases productivity, as measured by sales or value added per worker.Innovation performance also improves in firms that invest in training.Larger firms and firms investing in physical capital (IT) and/or organizational capital provide more training due to the benefits of complementarities.There is evidence that returns are higher in firms that invest in both training and in physical and organizational capital. eLeVAtoR PitCHWorkers participating in firm-sponsored training receive higher wages as a result.But given that firms pay the majority of costs for training, shouldn't they also benefit?Empirical evidence shows that this is in fact the case.Firm-sponsored training leads to higher productivity levels and increased innovation, both of which benefit the firm.Training can also be complementary to, and enhance, other types of firm investment, particularly in physical capital, such as information and communication technology (ICT), and in organizational capital, such as the implementation of high-performance workplace practices. AUtHoR's MAin MessAGeFirm-sponsored training is an investment in which both workers and firms can share the benefits.Workers benefit through higher wages and increased skills.Firms benefit through increased innovation and a higher productivity of labor.There is also evidence that firm-sponsored training complements other types of investment in the firm.Policymakers need to consider the importance of firm-sponsored training as a key driver of productivity growth.Policy should also be directed toward reducing barriers to training that may result from a lack of information or access to credit, particularly in smaller firms. ConsSome workers, particularly older workers and less-educated workers, receive less firm-sponsored training.Smaller firms tend to favor informal training and provide less training overall than larger firms.There is little data on the cost of training, which makes it difficult to measure the return-oninvestment of training for firms.There is a lack of research on the effects of training on some important measures of firm performance and workers' well-being. Who benefits from firm-sponsored training?Firm-sponsored training benefits both workers and firms through higher wages, increased productivity and innovation
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,023 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».