Culturally tailored workers for specialised destinations: producing Filipino migrant subjects for export
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This multi-sited, mixed-methods study in Canada and the Philippines examines how migrant workers are manufactured and deployed to a range of global destinations by the Filipino migration apparatus. Building on scholarship examining how the Filipino state markets, selects and prepares Filipino (labour) migrants from and to the Philippines, I show that beyond seeking to produce a temporary migrant workforce with a ‘comparative advantage’ (including traits like ‘docile’, ‘hardworking’, ‘English-speaking’ and ‘loyal’), the state alongside recruiters and other actors in the migration industry also seek to produce workers with cultural knowledge of norms in receiving destinations. This is another dimension through which the Philippines aims to establish its ‘superiority’ in the international market for temporary labour. This study has implications for how we think about transnational labour brokering under highly saturated conditions, and the role of culture and other mediating factors in configuring ‘ideal’ worker constructions and flows.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it