The Role of Law in Public Health: The Case of Family Planning in the Philippines
Bibliographic record
Abstract
Compared to neighboring countries, the Philippines has high fertility rates and a low prevalence of modern-method contraception use. The Philippine government faces political and cultural barriers to addressing family planning needs, but also legal barriers erected by its own policies. We conducted a review of laws and policies relating to family planning in the Philippines in order to examine how the law may facilitate or constrain service provision. The methodology consisted of three phases. First, we collected and analyzed laws and regulations relating to the delivery of family planning services. Second, we conducted a qualitative interview study. Third, we synthesized findings to formulate policy recommendations. We present a conceptual model for understanding the impact of law on public health and discuss findings in relation to the roles of health care provider regulation, drug regulation, tax law, trade policies, insurance law, and other laws on access to modern-method contraceptives.
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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 | 0.014 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.026 | 0.036 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".