Las experiencias migratorias de mujeres durante sus primeros años de inmigración en una región nórdica del Québec (Canadá)
Bibliographic record
Abstract
espanolInvestigacion cualitativa sobre las experiencias de inmigracion de 13 mujeres durante sus primeros anos en une region nordica de Quebec. Resultados: El discurso de las mujeres entrevistadas muestra que los principales obstaculos para su integracion pasaron por las barreras del idioma, el no reconocimiento de sus diplomas y de sus experiencias laborales en el pais de origen, la falta de formacion academica adaptada a las mujeres en la region que las acogio y el impacto de las condiciones invernales extremas en la salud psicologica de las mujeres. Conclusion: Es necesario sensibilizar a los profesionales de las ciencias sociales y profesionales de la salud para intervenir a partir del modelo intercultural en poblaciones inmigrantes. EnglishThe article adopts a qualitative approach in studying the immigration trajectories of 13 women during the first years following their arrival in the Quebec region of Abitibi. Results: The testimonies of the female participants show that the main obstacles to their integration in a remote area are linked to linguistic barriers, lack of accreditation of previous degrees and learning, lack of university programs adapted to women and the impact of the region’s harsh winter conditions on psychological well-being. Conclusion: The authors argue for raising awareness among social workers and health professionals in relation to the intercultural model approach.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".