208 Describing a strategy addressed to inform policies based on a health diagnosis of the migrant population in Andalusia (Spain)
Bibliographic record
Abstract
Abstract PTH 7: Health Policy and Health Services 2, B308 (FCSH), September 5, 2025, 11:30 - 12:24 Aims A report on the health diagnosis of the migrant population in Andalusia has been carried out to assess the health status, contribute to progress in the integration of statistics on migration and health, and inform policies to define actions and interventions that address the health inequalities that most affect migrants. Methods The report, which focuses on public health and social determinants, has analyzed data from official statistical sources and some studies of interest (National Institute of Statistics; Primary Care Clinical Database; Sociological Research Center; European Health Survey Spain; Eurostat; International Organization for Migration; European Commission for Refugee Aid). According to criteria of maximum exhaustiveness, descriptive statistical analyses were performed on multiple indicators related to: 1) sociodemographic characteristics, 2) main health indicators and their social determinants, and 3) interactions with health care services. Analyses were disaggregated by sex and age groups. Results The research team identified two areas of special relevance for informing policies: interaction with the public health system and lifestyles. The strategy chosen to impact policies has been the preparation and dissemination of Policy Briefs (PB), valuable communication tools aimed at decision-makers and which aspire to rapid change by offering pre-digested results and concrete recommendations. To elaborate recommendations for each PB, nominal groups were conducted with experts from public administration, health services and third sector, including migrants. Dissemination of PB results has been carried out reaching stakeholders and decision-makers from the aforementioned sectors. Moreover, the diagnosis report is published online at https://www.redisir.net. and a scientific paper is being prepared to describe the whole research and dissemination process and its limitations. Conclusions Although we can’t yet assess the impact on policies, it is urgent to overcome the methodological limitations presented by data from official sources in order to improve the quality of the research and the resulting policies.
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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 | 0.020 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".