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Enregistrement W2949300649

Essays on Skills and Labour Market Outcomes of Immigrants and the Canadian Born

2019· dissertation· en· W2949300649 sur OpenAlexaboutno aff
Nguyen Tuan Khuong Truong

Notice bibliographique

RevueMacSphere (McMaster University) · 2019
Typedissertation
Langueen
DomaineSocial Sciences
ThématiqueLabor Movements and Unions
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésImmigrationLabour economicsDemographic economicsEconomicsPolitical science
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Inequalities in basic skills and labour market outcomes between immigrants (by admission category) and the Canadian-born, and the underrepresentation of women in the information and communication technology (ICT) sector, are examined using Statistics Canada’s 2012 Survey of Adult Skills, a product of the Organisation for Economic Cooperation and Development’s Programme for the International Assessment of Adult Competencies. Differences in basic ICT skills, and the rates of return to these skills in the Canadian labour market, between immigrants and Canadian non-immigrants, are the focus of the first chapter. Immigrants, especially men, are observed to be disproportionately employed in ICT industries and occupations. A measure of basic ICT skills is employed to document differences in skill levels and labour market earnings across immigration classes and categories of Canadians at birth. Adult immigrants, including those assessed by the points system, are found to have lower average ICT scores than Canadians at birth, although the rate of return to ICT skills is not statistically different between the two groups. Immigrants who arrived as children, and the Canadian-born children of immigrants, have similar outcomes to the children of Canadian-born parents. Chapter 2 explores differences in literacy and numeracy skills, and the economic returns to these skills, for immigrants to Canada in different admission classes and their Canadian-born counterparts. First, respondents are grouped into three broad categories – adult and young immigrants, and the Canadian-born. Then, these individuals are classified into nine population subgroups: adult economic immigrants, adult refugees, adult family reunification, other adult immigrants, adult temporary residents, young refugees, young non-refugee immigrants, and second- and third-generation Canadian-born individuals. The analysis suggests that both adult and young immigrants (those who arrived in Canada at age 13 or younger) do not perform as well on literacy and numeracy tests conducted in English or French as those born in Canada, although young immigrants have higher test scores than adult immigrants. Similar results are found for wages. Among immigrants, it is observed that economic immigrants tend to have the highest test scores and hourly wages, with refugees having the lowest. The wage returns to these basic skills are economically significant at the 25th, 50th, and 75th quantiles of log hourly wages and the Canadian labour market rewards immigrants and the Canadian-born equally for their literacy and numeracy skills. Chapter 3 explores why the proportion of women in Canada’s ICT sector is well below their percentages in other science, technology, engineering, and mathematics (STEM) fields. A measure of basic ICT skills is used to study the skills gap and differences in returns to these skills between men and women. After controlling for appropriate covariates, Canadian women on average score higher than their male counterparts in basic ICT skills. However, women with the same ICT test scores are less likely than men to be employed in ICT occupations. Hourly wages in ICT occupations are lower for women, but the earnings gap in these occupations is not higher than those in the general labour market. Given the current and projected shortages of ICT professionals, women represent a large, yet untapped, pool of talent for this sector.

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,740
Score d'incertitude au seuil0,985

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0160,000

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.

Tête enseignante Opus0,006
Tête enseignante GPT0,216
Écart entre enseignants0,210 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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