Access and utilisation of social and health services as a social determinant of health: the case of undocumented Latin American immigrant women working in Lleida (Catalonia, Spain)
Bibliographic record
Abstract
Although Spain has social and healthcare systems based on universal coverage, little is known about how undocumented immigrant women access and utilise them. This is particularly true in the case of Latin Americans who are overrepresented in the informal labour market, taking on traditionally female roles of caregivers and cleaners in private homes. This study describes access and utilisation of social and healthcare services by undocumented Latin American women working and living in rural and urban areas, and the barriers these women may face. An exploratory qualitative study was designed with 12 in-depth interviews with Latin American women living and working in three different settings: an urban city, a rural city and rural villages in the Pyrenees. Interviews were recorded, transcribed and analysed, yielding four key themes: health is a tool for work which worsens due to precarious working conditions; lack of legal status traps Latin American women in precarious jobs; lack of access to and use of social services; and limited access to and use of healthcare services. While residing and working in different areas of the province impacted the utilisation of services, working conditions was the main barrier experienced by the participants. In conclusion, decent working conditions are the key to ensuring undocumented immigrant women's right to social and healthcare. To create a pathway to immigrant women's health promotion, the 'trap of illegality' should be challenged and the impact of being considered 'illegal' should be considered as a social determinant of health, even where the right to access services is legal.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".