Labor Migrations in Taiwan: Characterization and Interpretation Based on the Data of the 1990 Census
Bibliographic record
Abstract
In this paper we characterize and interpret patterns of labor migration in Taiwan, including (1) lifetime labor migration up to 1990 and (2) 1985–90 labor migration, based on the data of the 1990 Census. To gain better insights, the 1985–90 migrations are decomposed into three types: primary, return, and onward. Our major findings are as follows. First, lifetime labor migration was highly efficient in transferring labor into North Region from all other regions of Taiwan and contributed to Taiwan's transformation into one of the newly industrialized economies. Second, the 1985–90 labor migration in Taiwan responded quickly to the spatially unbalanced impacts of economic restructuring and globalization in the 1980s and resulted in a major turnaround in population redistribution: a shift from a long-lasting dual-pole (north–south) concentration pattern developed since the 1930s toward a single-pole concentration pattern in the north. Third, primary migration was much more voluminous than return and onward migrations, and rural prefectures had the typical pattern of a ‘loser’: a large net loss of primary migrants, countered by a small net gain of return migrants, and somewhat aggravated by a small net loss of onward migrants. Fourth, the greatest beneficiaries in terms of educational selectivity were Taipei city (the command center of the globalized Taiwanese economic system) and Hsinchu city (the so-called silicon valley of Taiwan). Fifth, the losses in the quantity and quality of human resources due to migration did not result in socioeconomic decline in rural prefectures because these losses were compensated for largely by the rural-ward financial transfer of central government and partly by the remittances sent back by rural out-migrants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".