Career Choice, Barriers, and Prospects of Asian American Social Workers
Notice bibliographique
Résumé
The current study explored factors influencing career choices of Asian American social workers and assessed if their personal characteristics and career-related experiences affected their perceived glass ceiling, perception of ethnic discrimination, and perception of career prospects. A total of 208 Asian American social work administrators, supervisors, practitioners and graduate social work students participated in a comprehensive online survey. Participants provided basic demographic and career-related information and completed a set of measures to explore their reasons of choosing social work as their career, and their career perceptions and prospects. Correlation analyses and multiple regression analyses were used to identify predictors of their perception of ethnic discrimination, perceived glass ceiling, and perception of career prospects. The findings showed that altruistic reasons were very important to extremely important in their choice of social work as their career. Social work idealism was found to associate positively with both altruistic reasons and professional concerns of choosing social work. There was a significant relationship between participant’s immigration status and family influence on their career choice. Those who were not born in the U.S. were more likely to be influenced by their family in their career choice than those who were born in in the U.S. Those whose parents were not born in the U.S. were more likely to be influenced by their family expectations on their career choice than either of their parents was born in the U.S. Perceptions of organizational fairness was found to be a strong predictor of perceived glass ceiling, perception of ethnic discrimination, and perception of career prospects. Implications of the findings for social work education and future research were discussed.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».