Are Healthcare Systems Failing Immigrants? Transnational Migration and Social Exclusion in the Workers’ Compensation Process in Québec
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: The changing world of work, which increasingly depends on the use of temporary and atypical forms of employment, has had a disproportionate effect on the health and well-being of immigrants. When they have to find a health professional for the first time or report an accident at work, the journey through the maze of medical-administrative bureaucracy can be long and arduous. The aim of this article is to describe the analytical contribution of systems thinking by presenting three situations that illustrate the importance of connecting the individual, organizational, and societal levels, especially focusing on the interplay between these levels. Methods: The data analyzed in this article are taken from an initial qualitative exploratory study of a purposive sample of 40 individuals: (1) clinicians ( N = 15), (2) claims consultants and rehabilitation counselors ( N = 14), (3) employers ( N = 2), and (4) immigrant workers ( N = 9). Situations were analyzed using insights from grounded theory by identifying the interconnectedness of individual, organizational, and system-based factors that can have an impact on the return-to-work process. Results: By looking specifically at the context of occupational rehabilitation in contemporary Québec and the challenges faced by immigrant workers faced with multiple factors of precariousness, this article sets out to show how local healthcare systems are poorly equipped to respond to the new reality of transnational migration. Conclusion: Drawing from recent research in the area of systemic theory, this article posits that systems, which are poorly adapted to the new reality of transnational migration, have the unintended consequence of creating new forms of discrimination and social exclusion.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it