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The Transnational Geographies of Immigrant Politics: Insights from a Comparative Study of Migrant Grassroots Organizing

2008· article· en· W1903984320 on OpenAlexaff
Patricia Landolt

Bibliographic record

VenueSociological Quarterly · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGrassrootsImmigrationPoliticsSettlement (finance)SociologyIdentity (music)Gender studiesBiology and political orientationPolitical scienceLaw

Abstract

fetched live from OpenAlex

Greater global interconnectedness produces a transformation in the ways in which groups constitute and interpret the boundaries of community formation and political practice. This article considers the ways in which a group engages (or not) with the possibilities for transnational identity formation and border-crossing politics granted by the changing structures of the global order. A comparative analysis identifies similarities and differences in the patterns of community formation and political engagement of Salvadoran migrants settled across different urban centers of North America. Variations in the territorial orientation and scales of immigrant political practice are explained by the national and city-level contexts of immigrant reception, the institutional opportunity structure in which migrant groups are embedded, and the nature of relations between migrants and their migrant and nonmigrant institutional interlocutors in places of settlement and their country of origin.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.005
Scholarly communication0.0030.003
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.053
GPT teacher head0.310
Teacher spread0.257 · 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

Citations62
Published2008
Admission routes1
Has abstractyes

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