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Record W4205656019 · doi:10.25009/clivajesrcs.i15.2692

Políticas migratorias locales, paradiplomacia migratoria y federalismo mexicano en acción

2022· article· es· W4205656019 on OpenAlexfundno aff
Adriana Sletza Ortega Ramírez

Bibliographic record

VenueClivajes Revista de Ciencias Sociales · 2022
Typearticle
Languagees
FieldSocial Sciences
TopicMigration, Health, Geopolitics, Historical Geography
Canadian institutionsnot available
FundersUniversidad VeracruzanaUniversidad de GuadalajaraMcGill University
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Este artículo propone un planteamiento teórico-metodológico de conceptualización y análisis de las políticas migratorias locales y la paradiplomacia migratoria. Emplea una metodología longitudinal de observación y recolección de datos sobre las Oficinas Estatales de Atención a Migrantes (ofam) en México, durante una década, entre 2010 y 2020, explicando cómo se configura el federalismo migratorio mexicano y, en particular, cómo responde a las articulaciones de las dinámicas migratorias internacionales convergentes en México, por situarse en los corredores migratorios que conectan Mesoamérica con América del Norte. Palabras clave: Políticas migratorias, Paradiplomacia, Gobierno local, Federalismo, México

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 score0.105
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0030.002
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 head0.030
GPT teacher head0.334
Teacher spread0.304 · 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
Published2022
Admission routes1
Has abstractyes

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