Work-Ready Graduates: The Role of Co-op Programs in Labour Market Success
Notice bibliographique
Résumé
Adapting to the labour market after post-secondary education and finding a job that matches graduates’ skills, while providing a good standard of living, can be a daunting challenge for new graduates.This Commentary investigates whether work-integrated learning (specifically co-op programs) results in higher incomes or other benefits after graduation.It provides an analysis of National Graduate Survey (2013) data to determine (i) the returns to participation in co-op for different fields of study at both the college and university levels, (ii) differential outcomes based on individual characteristics, and (iii) the effects associated with non-monetary success in the labor market. Estimates suggest that co-op programs have significant benefits for participants in the form of eased transition to the labor market and higher incomes after graduation and that they may play a role in overcoming wage gaps associated with bias toward individual characteristics (race, gender, immigration status). Overall, participating in co-op generally appears to be beneficial for graduates’ incomes – three years after graduation co-op participants have incomes about $2, 000 to $4, 000 higher than non-participants. At the college level, participating in co-op does not necessarily lead to higher incomes after graduation across all fields of study.There are, however, significant benefits to participating in co-op at the college level in science and engineering programs. Aggregate results, however, do not capture underlying and important differences in the effects associated with participating in co-op programs that depend on individuals’ characteristics and chosen fields of study. The estimated effect of participating in co-op programs differs for women, visible minorities and immigrants, relative to Canadian men. For visible minority and immigrant university graduates, participation in co-op programs is associated with similar incomes to white-male co-op participants. Female co-op program participants that graduated from university received wages similar to male peers that did not participate. Immigrants, women and visible minority individuals that participated in co-op were more likely to be employed full time than non-participants with similar characteristics.Women, unfortunately, tend to receive lower benefits than men from participating in co-op programs in terms of income, getting a first job related to their field of study, or securing a permanent position. Together, these results highlight that co-op programs and work-integrated learning more generally might have a role in reducing wage and employment gaps traditionally associated with bias toward individual characteristics. Government policymakers and educational institutions should continue their support for expanding the programs so they are accessible to more students. At present, co-op programs in arts, education and social science do not appear to be as beneficial as the programs in STEM subjects. While co-ops are generally beneficial, the differences between fields of study suggests a need for caution in assuming that expanding co-op programs to more individuals or new areas would have the same benefits for new graduates as do current co-op programs. This highlights a need to carefully monitor the results of participating in co-op for students both during school and after graduation to continuously improve and adapt the programs to maximize benefits for individual fields of study.
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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 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».