Migration and development in the South Pacific
Bibliographic record
Abstract
For the past quarter of a century migration has been the most important\ndemographic variable in large parts of the South Pacific region. Within the region\nthere is extensive rural-urban migration and beyond the region international\nmigration to the metropolitan states of USA, Australia and New Zealand. The\nscale of this movement has changed perceptions of development, posed problems\nfor national development (and especially for agricultural development) and con\ntributed to rapid social and economic change, as island states and islanders have\nincreasingly focused their social and economic aspirations outwards. Pressures\nfor migration continue to increase at the same time as the opportunities for\nsatisfying such pressures are declining, and as international migration becomes\nan increasingly overt political issue.\nThis collection of recent papers examines the changing context and impact of\nmigration in eight different states in the region, reviewing such issues as the brain\nor skill drain, remittances and investment, employment strategies of migrants,\nthe impact of migration on inequality and uneven development and the overall\nrelationship between migration and development. Migration is more closely\nlinked to social issues, including education and suicide, than in many earlier\ndiscussions and there is also a strong emphasis on the historical evolution of\nstructures of migration. The various papers demonstrate the great variety in the\nstructure and impact of migration and recognize the tasks involved in incorporat\ning such diversity into appropriate policy formation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".