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Record W2949300649

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

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

Bibliographic record

VenueMacSphere (McMaster University) · 2019
Typedissertation
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationLabour economicsDemographic economicsEconomicsPolitical science
DOInot available

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.740
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0160.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.216
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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