Bibliographic record
Abstract
In this paper I will examine the political and public health dimensions of global Safe Motherhood initiatives in order to: 1) consider the full range of implications for public health action in this area of women’s health. The leading cause of maternal death, hemorrhage (WHO 2005: 62), is associated with, if not a proxy for, induced (often illegal) abortion, yet availability of safe abortion services is a cautiously stated (at best) objective of the initiatives. Further, Safe Motherhood programs aim to improve pregnancy and birthing outcomes through various means (namely by promoting family planning, emergency obstetrical care, universal access to skilled birth attendants, improved education), but do not adequately address the (pro)natalist bent of the programming. The language of “Safe Motherhood” reinforces the primacy of the role of mother for women (Rance 1997: 10), which can narrow the scope of policy intervention to improve health; and 2) consider the extent to which Safe Motherhood initiatives attend to both inequality and identity. According to Costello, Azad and Barnett, there are many “reasons why a policy of health centre-based interpartum care might not be the most successful or cost-effective approach to reduce mortality in high mortality settings during the next decade” (2006: 1477). They cite various cultural and other contextual factors that interact with patterns of care and health status, which are often neglected in public health discussions of MMR reduction. Similarly, cultural preferences for “natural,” “traditional,” or “normal” birth often compete with or contradict Safe Motherhood initiatives, and should be considered in relation to public health protocols and objectives.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.047 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".