Labour Migration and Economic Growth in East and South‐East Asia
Bibliographic record
Abstract
Abstract East and South‐East Asia will face major demographic changes over the next few decades with many countries’ labour forces starting to decline, while others experience higher labour force growth as populations and/or participation rates increase. A well‐managed labour migration strategy presents itself as a mechanism for ameliorating the impending labour shortages in some East Asia–Pacific countries, while providing an opportunity for other countries with excess labour to provide migrant workers who will contribute to the development of the home country through greater remittance flows. This paper examines such migration policy options using a global dynamic economic simulation approach and finds that allowing migrants to respond to the major demographic changes occurring in Asia over the next 50 years would be beneficial to most economies in the region in terms of real incomes and real GDP over the 2007–50 period. Such a policy could deeply affect the net migration position of a country. Countries that were net recipients under current migration policies might become net senders under the more liberal policy regime.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".