A Comparative Assessment of Non-tenure Stream Faculty Members’ Perceived Organizational Support and Organizational Commitment at Two Canadian Universities
Notice bibliographique
Résumé
This study explored the employee-organizational relationship of non-tenure stream faculty teaching at two research-intensive Canadian universities through an examination of faculty members’ perceived organizational support, organizational commitment, and organizational exchange relationship. Through a survey of 146 non-tenure stream faculty teaching at two institutions in the 2013-14 academic year, the study examined their composition, characteristics, career aspirations, and views about working as a non-tenure stream teacher at their institution, from a comparative perspective. Five research questions were addressed. The closed- and open-ended survey question results were analyzed and presented for both the pooled and individual institutional samples. The measures of perceived organizational support, organizational commitment, and organizational exchange relationship were analyzed and scale reliability results are reported. Key findings include: one third of study participants are teaching in a non-stream position because they could not find a tenure stream position; three quarters of participants had other employment (whether it was full-time or part-time, at or external to the university); participants feel emotionally attached to their institution (affective commitment) and believe that their institution supports them and values their work (perceived organizational support); part-time non-tenure stream faculty were less ‘emotionally attached’ than were full-time non-tenure stream faculty; full-time non-tenure stream faculty associate greater ‘costs’ to leaving their institution of employment (continuance commitment) than part-time non-tenure stream faculty; over four fifths of participants were satisfied working at their institution and would recommend the institution as a good place to work; participants identified job security and stability, a greater respect, sense of belonging, recognition, being undervalued, and better compensation and career related issues, as concerns; working with students, learners, colleagues, and teaching were what participants liked best about working at their university.
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 | 0,003 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,005 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 ».