Uncertain Belongings: Relationships, Money and Returned Migrant Workers in Port Vila, Vanuatu
Bibliographic record
Abstract
New Zealand’s Recognised Seasonal Employer (RSE) scheme allows Pacific islanders, including many from Vanuatu, to migrate as temporary agricultural labourers. For government stakeholders, the program’s success can be measured, in no uncertain terms, by the increased consumption of foreign goods and community development projects funded by returned migrants. Yet it is precisely in these terms, of new belongings and one’s sense of belonging, that returnees, especially young men, experience the greatest uncertainty. How should they use the money they earn overseas: to strengthen their kinship networks and communities by sharing their wealth, or to purchase clothes, stereos, cars, or even land, which will belong only to them as individuals? Each strategy has its potential promises and pitfalls, and the outcomes remain uncertain. Will workers who spend on belongings alienate themselves from their kin and island communities? And how might they be forging new kinds of belonging as young urban wage earners? In addition to exploring these questions, this paper suggests that these strategies might inform and inspire relevant policy that is able to better grapple with the very uncertainties the RSE helps to create.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".