Building multi-target commitment through work-integrated learning : The roles of proactive socialization behaviours and organizational socialization domains
Bibliographic record
Abstract
Cette recherche teste la relation entre les comportements proactifs de socialisation de 2905 nouveaux-entrants et deux conséquences – les domaines de socialisation et l’implication multi- cibles – dans le contexte particulier de contrats courts en formation-emploi. Les résultats basés sur des régressions multiples soutiennent les relations directes entre les comportements de socialisation et deux domaines de socialisation et l’implication multi-cibles. De plus, les domaines de socialisation médiatisent la relation entre comportements de socialisation et implication envers l’équipe et le travail. Les résultats indiquent que même sous contrats courts, les individus se socialisent dans plusieurs domaines et développent de multiples chemins pour tisser des liens avec des cibles organisationnelles. Des recommandations pour de futures recherches et pour les praticiens sont avancées.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".