Bibliographic record
Abstract
In many parts of the world, including Thailand, marriage is being delayed and increasing proportions of women and men will never marry. The results reported in this article are based on microdata samples of the 1970, 1980, 1990 and 2000 Thai censuses, supplemented by focus group data. The increases in proportions never-married that had been observed between 1970 and 1990 continued through the decade of the 1990s. However, unlike earlier decades, changes in the 1990s were much greater for men than for women. Much of the difference in proportions never-married among women can probably be explained by changing socioeconomic composition of the population, but this may be less true for men. There is some evidence of a marriage squeeze for highly educated women and for men with the least formal schooling. Qualitative data suggest that while marriage may no longer be necessary, there remain abundant social pressures, particularly for women to formalize unions. Most young people still expect to get married at some point, if a suitable partner can be found, since the positive aspects of marriage still seem to outweigh the negative ones. Financial circumstances remain very important, however, in ascertaining whether one is ready or able to marry.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.029 | 0.009 |
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".