Temporary Foreign Workers and Former International Students as a Source of Permanent Immigration
Notice bibliographique
Résumé
We compare the economic outcomes of former Temporary Foreign Workers (TFWs) and former international students to immigrants who have no Canadian human capital at the time of landing. First, controlling for all possible variables that are adjustable under the current Canadian points system, we find that TFWs and students have better earning and employment outcomes, although by four years after landing, there is no difference between the employment outcomes of students or earnings of TFWs and workers with no pre-immigration Canadian human capital. Predicting the points that immigrants would obtain based on their observable human capital under the points system, each point increases earnings by around 2 percent and the probability of being employed by around half a percent. We also find that the predicted points of the respondent helps predict the earning and employment outcomes of the spouse. Next we examine the outcomes of immigrants based on entry class separately by gender. We find that both male and female Principal Applicants entering through the Skilled Worker program perform much better than immigrants entering through most of the other classes, although, for males, Principal Applicants entering under the Family Class are more likely to be employed at six months and two years after landing. Finally, restricting the sample to immigrants who were directly assessed based on economic criteria (Skilled Worker Principal Applicants), we discover that for males, immigrants who had previously worked in Canada as TFWs have much better outcomes in terms of entry earnings than immigrants who have no pre-Canadian experience at landing. Former international students experience an advantage in terms of hourly earnings, but much smaller than that experienced by TFWs, and students experience no earnings advantage in terms of weekly earnings. Overall, the evidence suggests that temporary foreign worker or student status does provide some signal of how well an immigrant will integrate economically.
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Comment cette classification a été obtenuedéplier
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 | 0,002 | 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 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».