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Record W4294946003 · doi:10.1111/anti.12875

Unsettling Migrant Reintegration: The Serial <scp>Risk‐Taking</scp> of Returning Overseas Filipino Workers (<scp>OFWs</scp>) to Cordillera, Philippines

2022· article· en· W4294946003 on OpenAlexaff
Vanessa Banta

Bibliographic record

VenueAntipode · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsEntrepreneurshipGovernment (linguistics)State (computer science)Migrant workersPrecarityAcquiescenceColonialismFocus groupSociologyEmbodied cognitionPolitical scienceEconomic growthGender studiesEconomicsLawPolitics

Abstract

fetched live from OpenAlex

Abstract In 2017, the Philippine government boosted its campaign on Overseas Filipino Worker (OFW) reintegration, a set of programmes designed to aid returning Filipino labour migrants. In this paper, I examine migrant reintegration through the case of returned migrants to the province of Benguet, Philippines. Rather than use “sustainability of return” as main focus of assessment, I foreground instead the historical geographies undergirding the current reiteration of this migration policy. By doing so, I demonstrate how the “gambling” practices of returned migrants can be read as not an easy acquiescence to the neoliberal imperative for self‐entrepreneurship encouraged by the Philippine state. In highlighting gambling as an embodied strategy emerging from and through imperial histories, I argue that migrant reintegration gets revealed as rehearsal of certain colonial logics that have oriented certain peoples to the labour of serial risk taking for survival. Close attention to return migrants’ gambling practices raises urgent questions regarding the relentless push for entrepreneurship as development solution.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.024
GPT teacher head0.276
Teacher spread0.251 · 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 designNot applicable
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

Citations3
Published2022
Admission routes1
Has abstractyes

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