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Record W2014452498 · doi:10.1080/08865655.2003.9695608

Migration in the life course of women in the border city of Matamoros, Tamualipas: Links to educational, family, and labor trajectories

2003· article· en· W2014452498 on OpenAlexvenueno aff
Raquel Márquez, Yolanda C. Padilla

Bibliographic record

VenueJournal of Borderlands Studies · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsLife course approachEducational attainmentInternal migrationDemographic economicsSociologyGender studiesOrder (exchange)Economic growthPolitical sciencePsychologyGerontologyDemographyPopulationEconomicsMedicineDevelopmental psychology

Abstract

fetched live from OpenAlex

Abstract This paper focuses on the role that migration plays in the life chances of women of very limited resources living in Matamoros, Tamaulipas, a major maquiladora site in Mexico. Due in part to the growth of the maquiladora industry, the Mexican border region experiences significant levels of migration. The maquiladora industry, which has been disproportionately geared to employment of women, has no doubt attracted female migration to the border (Pedraza 1991). Thus, in this study we are particularly concerned with understanding the dynamics of migration among women—both among women who are associated with the maquiladora industry and those who are not. Based on rich information obtained through life histories of a group of women from different age cohorts, we find that female migration patterns seem to be consistent with major life events, although the timing of migration was not always optimal. Furthermore, important variations existed for women of different age cohorts. For the older women, schooling was generally cut off prematurely in order to start working or to migrate, this was less often the case for the younger cohorts. In most cases, however, migration did not improve the lot of these women; and, in fact, the women were often caught in a spiral of reverse mobility that took them from low educational attainment to low‐level jobs to even lower level jobs with each shift in their life course. Notes Marquez is Assistant Professor in the Department of Sociology, University of Texas at San Antonio. Padilla is Associate Professor in the School of Social Work, University of Texas at Austin.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.361
Teacher spread0.334 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2003
Admission routes1
Has abstractyes

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