Reproductive Contributions of Foreign Wives in Taiwan: Similarities and Differences among Major Source Countries
Bibliographic record
Abstract
In light of the entrenchment of sub-replacement fertility and the sharp increase in the stock of foreign wives in Taiwan in recent years, this research studies the reproductive contributions of Taiwan’s foreign wives from the top five source countries (China, Vietnam, Indonesia, Thailand, and the Philippines), based mainly on an application of a multinomial logit model to the micro data of the 2003 census of foreign wives. Our main findings are as follows. First, the overall fertility level of the foreign wives was probably somewhat higher than that of the native-born women and definitely lower than the replacement level. Second, among the five nationalities, those from China were much less reproductive than those from the other countries, mainly because the former were more prone to (1) having a rather old marriage age, (2) having a very large spousal age gap, (3) being separated or divorced, (4) having their current marriage being their second marriage, and (5) having a veteran as the husband. Third, among the four Southeast Asian nationalities, those from Indonesia and the Philippines were more reproductive than those from Thailand and Vietnam. This contrast was a muted reflection of the fertility difference in countries of origin. Fourth, for every nationality, marriage duration and marriage age were the most powerful explanatory factors and must be included in the model to avoid getting misleading estimated coefficients of other less powerful explanatory factors, whereas current age was a spurious factor that should not be used in the model. Fifth, in the context of marriage duration and marriage age, the explanatory factors with rather strong explanatory powers for at least one nationality included spousal age gap, marital status, remarriage status, co-residence with parent, and wife’s employment status. Sixth, the expected negative effect of wife’s educational attainment on lifetime fertility turned out to be either non-existent or modest. In particular, it had practically no effect on the probability of being childless. These findings implied that getting better educated foreign wives could increase the quality of their children with little or no reduction in the number of their children and in their probability of being childless
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".