Risky investments : turning return migrants and national heroes into entrepreneurs in the Philippines
Bibliographic record
Abstract
This dissertation “follows the policy” of return and reintegration for returning overseas Filipino workers (OFWs) to the Philippines. At once a global policy model and migration policy specific to and rooted in the very labor and economic conditions of the Philippines, the reintegration examined here is as socio-spatial process constituted and shaped by various actors, subjects and institutions. Specifically, it asks why and how reintegration policies are facilitated at this very conjuncture of Philippine labor export history through an investigation of interconnected sites. First, I outline the “return assemblage” composed of state agencies, non-governmental organizations and private institutions invested in the return migration of OFWs. Then, I conduct a close study of what “reintegration” means for a self-organized, volunteer group of middling migrants who conduct financial literacy and entrepreneurship training for OFWs. Lastly, I continue my ethnographic and interview-based research with farmworkers from Japan and Vancouver, BC to examine how small enterprise has become the newest form of “gambling” for life and survival in Benguet, a region north of the Philippines. This dissertation contends that reintegration as it stands today is primarily built on the neoliberal logic that return migrants must be transformed first into financial literate subjects, and then into “entrepreneurs” who will eventually invest in the Philippines. Thus, rather than ensure sustainable lives for migrant returnees, this study argues that reintegration functions as governance and development strategy that seeks to transforms OFWs into self-reliant subjects in the midst of the state’s withdrawal of any social welfare for its returning citizens. It suggests that questions of migrant reintegration today impel a theoretical and methodological return to the colonial and imperial legacies of neoliberal development policies such as entrepreneurship and livelihood programs in the Philippines. In doing so, my study reveals how processes of migrant reintegration exacerbate long-enduring governance mechanisms for the nation’s surplus populations. By taking this deeper and expansive view of Philippine migrant reintegration across its multiple spaces, this dissertation contributes to critical scholarship on the areas of migration-development nexus, migration governance, financialization and shaping of financial subjectivities, and the ongoing processes of neoliberalization in the Global South.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".