Determinants of Immigrants' Decisions to Remain in Canada
Notice bibliographique
Résumé
In recent years, Canada's immigration landscape has become complex and politically sensitive. Public discourse has increasingly portrayed immigrants as contributors to the housing and job shortage. In response, the Canadian government reduced the number of work permits and permanent residence invitations, focusing on attracting highly educated, English-proficient professionals with recognized work experience. These candidates are selected with the expectation that they will quickly integrate and effectively contribute to the economy. However, the reality for many newcomers is far more complicated. Despite meeting the selection criteria, skilled immigrants often encounter structural barriers, such as complex licensing processes, lack of Canadian credential recognition, and the persistent requirement for “Canadian experience.” These challenges prevent many from continuing their professional careers. In other words, immigrants arrive with the belief that their skills and qualifications are valuable but often find themselves undervalued and under-utilized. Meanwhile, the host society may view immigrants not as contributors powering social programs, but as burdens on an already strained system. Although considerable research has been done on the challenges immigrants face, relatively little is known about the immigrants’ motivations for choosing Canada in the first place and what might lead individuals to stay, despite not being able to work in the career they trained for in their country of origin. To improve retention and integration, it is essential to examine where mismatches between expectations and realities occur, how these disconnects influence long-term settlement decisions, what can be done to close the gap between immigration selection criteria and immigrant outcomes, and eventually, how Canada can send a clearer and realistic message to future newcomers and develop effective policies and supports to ensure their long-term success and contribution. Specifically, we want to examine: 1. What are the initial goals and expectations of immigrants coming to Canada, and how do these compare with their actual experiences after settling? 2. Does the degree of alignment between expectations and lived experience influence the intention/desire to stay in Canada long-term? 3. Are individuals higher in self-efficacy more likely to want to remain in Canada, and is an alignment between expectations and experience less determinant of their intention to remain?
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 | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,009 | 0,002 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 ».