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Record W2944343067 · doi:10.3390/socsci8050144

The Categorized and Invisible: The Effects of the ‘Border’ on Women Migrant Transit Flows in Mexico

2019· article· en· W2944343067 on OpenAlexafffund
Carla Angulo-Pasel

Bibliographic record

VenueSocial Sciences · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsWilfrid Laurier UniversityBalsillie School of International Affairs
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsInvisibilityVulnerability (computing)State (computer science)Border SecurityPolitical scienceNarrativeConstruct (python library)Government (linguistics)SociologyCriminologyGender studiesPolitical economyLawComputer security

Abstract

fetched live from OpenAlex

In an increasingly globalized world, border control is continuously changing. Nation-states grapple with ‘migration management’ and maintain secure borders against ‘illegal’ flows. In Mexico, borders are elusive; internal and external security is blurred, and policies create legal categories of people whether it is a ‘trusted’ tourist or an ‘unauthorized’ migrant. For the ‘unauthorized’ Central American woman migrant trying to achieve safe passage to the United States (U.S.), the ‘border’ is no longer only a physical line to be crossed but a category placed on an individual body, which exists throughout her migration journey producing vulnerability as soon as the Mexico–Guatemala boundary is crossed. Based on policy analysis and fieldwork, this article argues that rather than protecting ‘unauthorized’ migrants, which the Mexican government narrative claims to do, border policies imposed by the state legally categorize female bodies in clandestine terms and construct violent relationships. This embodied illegality creates forced invisibility, further marginalizing women with respect to finding work, and experiences of sexual violence and abuses by migration actors. The analysis focuses on three areas: the changing definition of ‘borders’; the effects of categorization and multiple vulnerabilities on Central American women; and the dangers caused by forced invisibility.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
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 head0.007
GPT teacher head0.287
Teacher spread0.280 · 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.

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

Citations15
Published2019
Admission routes2
Has abstractyes

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