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Record W1997119759 · doi:10.1080/08865655.2006.9695661

Transborder use of medical services among Mexican American students in a U.S. border university

2006· article· en· W1997119759 on OpenAlexvenueno aff
Leticia Fernández, Jon Amastae

Bibliographic record

VenueJournal of Borderlands Studies · 2006
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsSocioeconomic statusHealth careLanguage barrierDemographic economicsSisterPolitical scienceGeographyEconomic growthPsychologySociologyDemographyEconomicsPopulation

Abstract

fetched live from OpenAlex

The geographic and cultural proximity of sister cities along the U.S.‐Mexico border suggests that U.S. residents may circumvent financial, social, and legal barriers to healthcare by seeking care in Mexico. While most reports suggest that cross‐border use of healthcare is a common practice among low‐income Spanish‐speaking U.S. residents, little is known about groups with other socioeconomic profiles. We use data from a survey among students enrolled in a U.S. border university to examine their cross‐border utilization of healthcare. We find that use of cross‐border healthcare diminishes significantly with English language acquisition. The presence of kin on the Mexican side of the border and use of services in Mexico by co‐residents, however, increase the likelihood of students’ use of healthcare across 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)0.001
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.021
GPT teacher head0.363
Teacher spread0.342 · 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

Citations12
Published2006
Admission routes1
Has abstractyes

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