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Record W2754554347 · doi:10.20381/ruor-20904

The Impact of Immigrant Language Skills on Canadian Wages

2017· dissertation· en· W2754554347 on OpenAlexaboutno aff
Seda Gunduz

Bibliographic record

VenueuO Research (University of Ottawa) · 2017
Typedissertation
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationDemographic economicsLabour economicsGeographyEconomicsArchaeology

Abstract

fetched live from OpenAlex

This thesis consists of three chapters investigating the impact of immigrant language skills on Canadian wages. The first chapter, “Linguistic diversity among Canadian immigrants: 1981-2006”, describes the changes in linguistic diversity among Canadian immigrants, as measured by a preferred linguistic distance measure, the Levenshtein Distance (LD) Index, and documents socio-demographic characteristics of recent immigrants as well as their labour market performance based on their language capital at the time of entry. The LD is an approximation of immigrants’ language skills in the Canadian official languages and represents the “distance” of an immigrant’s reported language to the Canadian official languages. Using the 20% micro-data files of the Canadian Censuses between 1981 and 2006, I assign each immigrant an index number based on two language measures: mother tongue and home language. French and English are defined as the Canadian official languages in Quebec and outside of Quebec, respectively. The main findings suggest that although immigrants’ mother tongues became more “distant” to the Canadian official languages in both regions over time, the language skill of an average immigrant based on home language remained almost the same in Quebec, in particular, between 1981 and 1996. In terms of immigrants’ socio-demographic characteristics and their labour market performance, general patterns were similar across the two regions, although there were significant differences by language groups. In particular, the change in immigrants’ wages by language groups is suggestive of the role of language skills in determining wages. The second chapter, “Immigrant versus native men? Substitutability and the role of linguistic diversity in Canada”, estimates the degree of substitutability between immigrant and native men by incorporating immigrants’ language skills into the analysis and calculates the potential wage effects of immigration on Canadian wages. Using the 20% micro-data files of the Canadian Censuses between 1981 and 2006 and imposing a nested-CES production function on the Canadian economy, I estimate immigrant-native substitutability based on immigrants’ language skills in addition to education levels and years of labour market experience. I use the LD Index to represent immigrants’ language skills by the distance of the mother tongue and home language of an immigrant to English outside of Quebec and to French in Quebec. I define three language groups for immigrants as the high language-skilled, the medium language-skilled, and the low language-skilled. The key findings are as follows. First, home language-based estimates suggest imperfect substitutability in Canada outside of Quebec in some cases. Second, by language skill groups, the low language-skilled immigrants are more likely to be imperfect substitutes for the Canadian-born. Third, the findings for Quebec are substantially different from those for Canada outside of Quebec. My simulations suggest that the long-run effect of immigration on immigrants’ wages was negative between 1981 and 2006 while the long-run effect of immigration on the wages of the Canadian-born was small but positive over the same period. The third chapter, “Gender, linguistic diversity, and labour market substitutability”, uses the same methodology and data sources as in the second chapter to incorporate female workers into the analysis of immigrant-native substitutability. This study estimates the elasticity of substitution between immigrant language groups and natives for female workers and the pooled sample of male and female workers. The findings suggest that the degree of substitutability between female immigrants and female natives is similar to the degree of substitutability between male immigrants and male natives. The main results do not change for the pooled sample. Due to potential differences between language accumulation processes between female and male immigrants, the third chapter also estimates female-male immigrants substitutability based on language skills, education levels, and years of labour market experience. The findings suggest that female and male immigrants are imperfect substitutes outside of Quebec regardless of language measures.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.370

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.025
GPT teacher head0.385
Teacher spread0.360 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2017
Admission routes1
Has abstractyes

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