Trans-Tasman Migration, Transnationalism and Economic Development in Australasia
Bibliographic record
Abstract
This paper focuses on migration between Australia and New Zealand, which has exhibited a strong, but cyclical, net movement towards Australia since the late 1960s. A long-term historical perspective is taken. Trans-Tasman migration is also compared with inter-island migration within New Zealand. It is argued that differential economic development, driven by forces of globalization, agglomeration and technological change, has been primarily responsible for the long-run changes in the distribution of population across the regions of Australasia. Asynchronous business cycles, demographic dynamics, perceptions, return migration and the high international mobility of New Zealanders (of whom one quarter of those aged 40–64 have lived abroad for a year or longer) are responsible for the short-run fluctuations. However, permanent and long-term migration is only a small fraction of total trans-Tasman population movement. Moreover, trans-Tasman migration has not offset New Zealand's ability to recruit population through immigration. Over the last three decades, the outflow of more than half a million New Zealand citizens has been compensated by a net inflow of three-quarter million citizens from elsewhere. The number of New Zealanders in Australia is expected to continue to grow but the migration flows are becoming increasingly diversified. One-third of the New Zealanders in Australia re-migrates within four years. Future trends will depend on New Zealand's ability to boost productivity growth, the real cost of air travel, retirement migration and the impacts of climate change.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".