Selection and use of contraceptive methods among internal migrant workers in three large Chinese cities: A workplace-based survey
Bibliographic record
Abstract
OBJECTIVES: To describe the current status of the decision-making process with regard to the use of contraceptive methods among internal migrant workers in three large Chinese cities. METHODS: A total of 4313 sexually active internal migrant workers were recruited in Beijing, Shanghai, and Chengdu. Information on contraceptive use was collected by means of questionnaires. RESULTS: Contraceptive prevalence was 86% among unmarried sexually active migrant workers and 91% among married workers. The main contraceptive methods used by married migrants were the intrauterine device (51%), condoms (25%) and female/male sterilisation (17%); the main methods resorted to by unmarried, sexually active migrants were condoms (74%) and oral contraceptives (11%). The contraceptive method applied by 20% of married respondents had been selected by other people, without they themselves having their share in an informed choice. Adopting the contraceptive decisions made by others was associated with being a married migrant, a construction or service worker, a rural-urban migrant, a migrant living in collective or rented rooms, or a migrant with more children. CONCLUSIONS: Many internal migrants in these large cities did not choose their contraceptive method on their own. Efforts enabling and encouraging migrants to make informed choices are needed.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".