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Social reproduction, migration and labour control regimes: understanding Filipino crew experiences in the UK fishing fleet

2024· article· en· W4392151391 on OpenAlexaff
Philip F. Kelly, Ria Jhoanna Ducusin

Bibliographic record

VenueWork in the Global Economy · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsYork University
Fundersnot available
KeywordsReproductionTemporalitiesSocial reproductionForbearanceSociologyDisciplineMobilitiesPolitical scienceEconomicsEcologySocial capitalSocial scienceFinance

Abstract

fetched live from OpenAlex

The notion of a labour control regime provides a conceptual framework for understanding the web of actors, institutions and norms that shape disciplinary mechanisms in the labour process. While labour regime approaches have drawn in multiple scales and diverse processes, this paper argues that international migration, and social reproduction in migrant source areas, must also be understood as part of the regime. Focusing on the case of Filipino migrants in the UK fishing industry, we use qualitative interviews conducted in the port of Fraserburgh, Scotland, and a migrant sending community in the province of Cebu, Philippines. We argue that the reproductive processes of workers’ lives in their home communities are an important underpinning of the labour regime they participate in when working on contracts overseas. We identify three sets of reproductive processes in particular: the trajectories of household poverty and debt that propel labour migration; the socialisation and social networks, as well as zones of recuperation, provided by home communities; and, the long-term temporalities of previous investments in fishery migration, as well as future aspirations for financial stability and intergenerational social mobility. While reproductive spaces and processes are not controlling mechanisms in themselves, they do represent an important part of the labour regime and they begin to explain migrant fishers’ forbearance in the face of a disciplinary labour regime.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score0.956

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 studies0.0000.000
Scholarly communication0.0010.000
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 head0.029
GPT teacher head0.294
Teacher spread0.265 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2024
Admission routes1
Has abstractyes

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