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Record W3112504561 · doi:10.5509/2018914759

Postscript: Infrastructuralization: Evolving Sociopolitical Dynamics in Labour Migration from Asia

2018· article· en· W3112504561 on OpenAlexvenueno aff
Biao Xiang, Johan Lindquist

Bibliographic record

VenuePacific Affairs · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
FundersEconomic and Social Research Council
KeywordsDynamics (music)Political scienceEconomic geographyPolitical economyGender studiesDevelopment economicsGeographySociologyEconomic systemEconomics

Abstract

fetched live from OpenAlex

This article explores the trend of “infrastructuralization” in state-sponsored programs of low- and semi-skilled labour migration from Asia. These programs increasingly focus on facilitating migration rather than generating actual opportunities for mobility and substantive development. While providing training to develop skills targeting specific jobs in specific countries, the programs generally leave complaints about actual working conditions and wages to be managed by the migrants themselves. In this process, labour migration programs are infrastructuralized, meaning that there is an ongoing expansion and intensification of the socio-technical platform that makes mobility possible, as facilitation becomes an end in itself. This trend is tied to changes in the general development paradigm, labour and state-citizen relations across Asia, as well as the increasing importance of brokers in facilitating connection. This article first probes a number of internal dynamics around which infrastructuralization unfolds in practice. We then highlight how commercial intermediaries and public institutions, the two key actors in infrastructuralization, shape migration by producing context-specific migrant subjectivities, making aspirational work a central element of infrastructuralization. In the conclusion, we explore research agendas that can be developed further.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.844
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.265
Teacher spread0.256 · 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 designTheoretical or conceptual
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

Citations42
Published2018
Admission routes1
Has abstractyes

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