Contingent Relations: Migrant Wellbeing and Economic Development in Rural Manitoba
Bibliographic record
Abstract
Drawing on ethnographic fieldwork conducted in rural Manitoba and the Philippines, this paper uses the example of the small town of Douglas, which since 2009 has been home to a small Filipino community, as a tenuous counter-point to the accounts of exclusion that dominate the scholarship on Temporary Foreign Labour in Canada. This paper draws on ethnographic research conducted in Manitoba with the region's newest immigrants-those recruited to ensure the viability of the new, diversified rural regional economy, and more specifically, the tourism and hospitality sector, established in the 1970s. In 2009, unable to meet its labour needs regionally, a local hotel began recruiting temporary foreign labour. By 2014, the Hotel had recruited 71 workers from the Philippines, most of whom arrived through Canada's Temporary Foreign Worker Program; others having arrived through the province's immigration scheme, the Manitoba Provincial Nominee Program (MPNP). A reflection of the ubiquity of globalized Filipino migration, the well-being of these workers had long been informed by economic development in the Philippines and the centrality of international labour mobility to that state project. What emerges from the data is a simultaneous acceptance and contestation of the conditions of transnational family life, and moreover-reflecting the focus of this special issue-the extent to which migrant well-being shifts in accordance to labour mobility regimes responsive to development. Migrant workers and their families are implicated in these connected, yet differently motivated, state projects. And while particular narratives concerning their contributions come to be valorized and even celebrated, their mental, physical, affective, and relational well-being is often over-looked by those who benefit from their labour and mobility. Of equal importance is the provincial state's participation in this process through the provision of permanent residency to existing and in-coming migrants. While this benefits individual families, it does not inherently challenge the logics of neoliberalism; rather, drawing on its nuances, it create new possibilities for capital accumulation and exploitation, while offering some protection for select families who are willing and able to abide by the terms established by their employer and the Manitoba state.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".