Bridging Borders: A Comparative Study of Policy Measures and Initiatives Promoting Labor Market Integration of Immigrant Women in Sweden and Canada 2015-2023
Bibliographic record
Abstract
This study provides a comparative analysis of labor market integration policies for immigrant women in Sweden and Canada from 2015 to 2023, using Carol Bacchi's framework of "what is the problem represented to be” (WPR). It explores how Canadian and Swedish policies construct the “problem” for female immigrants' labor market integration by examining underlying assumptions, values, and discourses within these policies. The study uses a postcolonial feminist and intersectional lens to critically assess how gender, immigration, and labor market dynamics intersect with policy frameworks. Analyzing the representations and effects of these policies, this study highlights the differences and similarities between the approaches of the two countries. It also considers the wider sociopolitical context that influences policy development and implementation. The study reveals that Canadian and Swedish policies identify a combination of structural and individual shortcomings as the "problems" for immigrant women integrating into the labor markets of these countries. The comparative analysis between the nations reveals that while both countries identify similar "problems," their strategic actions and targeted interventions differ. Canada has a more comprehensive approach to labor market integration and focuses more on efforts to restructure harmful structures. In contrast, Swedish initiatives focus more on individual adaption over systemic change by implementing targeted initiatives for immigrant women's adaptation to existing labor market structures. The findings of this study contributeto migration and labor studies by revealing the complex layers of policy and its impact on the labor market opportunities of immigrant women.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".