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Expectativas de migración internacional en estudiantes de enfermería en México, Distrito Federal

2010· article· es· W2155747136 on OpenAlexaboutno aff
Yetzi Rosales-Martínez, Gustavo Nígenda, Omar Galárraga, José Arturo Ruíz-Larios

Bibliographic record

VenueSalud Pública de México · 2010
Typearticle
Languagees
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceDemographyGeographySociologyArt

Abstract

fetched live from OpenAlex

OBJECTIVE: To analyze the factors associated with the expectations to migrate abroad among nursing students in Mexico City. MATERIAL AND METHODS: A cross-sectional study was conducted with a non-random sample of 420 students. A logistic regression model was estimated. RESULTS: A total of 69% of the informants expressed their intention to move abroad, to look for employment (65%) and/or to continue their studies (26%). Of those, 50% would choose Canada as their destination, followed by Spain and the United States. The variables associated with migration expectations were: age, income, having relatives abroad, and perception of poor labor conditions and low wages in Mexico. CONCLUSIONS: Results are consistent with international literature. Low wages, poor labor conditions and the limited possibilities for professional development in Mexico are factors that contribute to generate migration expectations among nursing students. Additionally, optimistic perceptions about the job market and the labor demand in more developed countries heighten expectations to migrate.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.021
GPT teacher head0.394
Teacher spread0.373 · 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; both teacher heads agree on what is shown here.

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

Citations14
Published2010
Admission routes1
Has abstractyes

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