(In)visible Choices: Articulation Work and the Rise in US Maternal Mortality
Bibliographic record
Abstract
The US maternal mortality is double that of the UK and Canada and still rising. This is a public health crisis, and draws our attention to systemic issues with US health care, as maternal mortality is a core statistic used to indicate health care quality. Responding to the increasing number of women dying during one of the most common experiences with the medical system will require organizing a diverse group of stakeholders over a long period of time. Due to the unevenly distributed nature of the crisis, with Black women 243% more likely to die in childbirth or from childbirth-related causes will also require us to incorporate underrepresented voices into the current system. To examine these issues, we conducted interviews with public health experts working to address maternal mortality. We found that articulation work practices in public health limit the ability of experts to initiate contact with the very stakeholders they need to build relationships with to address the rise in maternal mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".