Income inequality between visible minorities and whites: A comparison between Quebec and the rest of Canada
Bibliographic record
Abstract
Objectives. Studies that have examined wage differentials between visible minorities and whites living in Canada found that, even though most immigrants since the 1990s have had similar levels of educational attainment (even greater) relative to native-born Canadians, most have a lower income compared to the latter group, especially visible minority immigrants. Few of those studies, however, have examined income inequality experienced specifically by visible minorities, concentrating instead on immigrants overall. This constitutes an important gap in the literature given that visible minorities, both native-born and immigrants, are more likely to experience a wage gap with respect to native-born whites than white immigrants. In addition, only a small number of studies have taken a detailed look at income inequality experienced by visible minorities living in Quebec, compared to visible minorities living in the rest of Canada. This is an important limitation given that Quebec is one of the Canadian provinces where much of the conflict regarding the integration of individuals who might appear as different from the majority is occurring. Thus, this dissertation aims at addressing those lacunas by studying wage differentials between visible minority members and whites, comparing Quebec to the other Canadian provinces.Method. This dissertation uses the 2006 Census and 2011 National Household Survey and employ the Oaxaca-Blinder decomposition model in order to separate the wage gap into two parts: a part that can be explained by sociodemographic and human capital characteristics, and a part that cannot be explained by such observable characteristics and, thus, more likely due to discriminatory practices. Results. The first analysis demonstrates that there are significant wage differences between visible minority groups and white individuals in Quebec, but that these wage gaps are mostly explained by individual characteristics. However, unexplained portions of these wage gaps remain, potentially indicating the presence of discrimination. Moreover, the rest of the analyses show strong evidence that some minority groups who live in Quebec might be more financially disadvantaged than visible minorities living in the rest of Canada. However, the reason why Quebec has the largest wage gaps seem in large part because of the disadvantageous socio-demographic and human capital characteristics that visible minorities living in Quebec have. Conclusion. Findings reveal that most of these large gaps are explained by the fact that visible minorities who live in Quebec have characteristics that disadvantage them in the labor market. This might be related to Quebec’s immigration policies that differ slightly from the rest of Canada. Thus, social policies should concentrate even more on language training courses as well as other integration initiatives. However, findings also reveal the presence of discrimination in the province of Quebec when it comes to wage differentials, especially when it comes to the language and the nativity and duration status of visible minorities, which should be acknowledged as well.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".