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Record W4252116011 · doi:10.21203/rs.2.16134/v1

Facilitators and barriers to advancing binational health coverage strategies for undocumented Mexican migrants in the United States of America

2019· preprint· en· W4252116011 on OpenAlexaboutno aff
Armando Arredondo, Emanuel Orozco, Ana Lucía Recamán, Alejandra Azar

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsMexican americansImmigrationPolitical scienceLawEthnic group

Abstract

fetched live from OpenAlex

Abstract Background: Within the framework of a new national health program with emphasis on universal coverage strategies and in the context of revision/adjustments to the North American Free Trade Agreement (NAFTA/TEMEC), the present study aimed to identify barriers, facilitators and challenges for the development of strategies on social protection in the health of migrants and their families. Material and methods: Evaluative research based on a qualitative analysis with a cross-sectional design. The techniques of documentary analysis, applied political analysis (mapping of actors), in-depth interviews and case studies were used. In the first stage, key actors were mapped at the federal level and senior executives and health officials, federal deputies, senators and members of the Mexican foreign service were interviewed. In the second stage, field work was carried out in the state of Guanajuato and California; State health service officials, state government officials, municipal officials, health unit workers, representatives of CSOs and relatives of migrants were interviewed. The analysis of the interviews was carried out through the ATLAS-Ti software, as well as the mapping of actors and feasibility analysis through the POLICY MAKER software. Results: The main results allowed to identify indicators on barriers and facilitators regarding social actors, binational agreements under NAFTA/TEMEC, institutional spaces, interaction between social actors, as well as the impact and type of relations for a greater advance in binational health policies. Several obstacles were reported, including the fears that undocumented emigrants have in the U.S. of being arrested and deported if they use public health services in the U.S. The stakeholders also believed that many Mexican emigrants do not have a culture that values health insurance. Conclusions: In the context of reforms and adjustments of health systems that are being discussed in parallel in the revision and adjustments of NAFTA/TEMEC (United States of America, Mexico and Canada), the facilitators and barriers identified can be used to strengthen the development of bi-national strategies with different schemes of social protection in the health of undocumented migrants and their families on both sides of the border.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.020
GPT teacher head0.360
Teacher spread0.340 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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