Transdisciplinary Imagination: Addressing Equity and Mistreatment in Perinatal Care
Bibliographic record
Abstract
Inequities in birth outcomes are linked to experiential and environmental exposures. There have been expanding and intersecting wicked problems of inequity, racism, and quality gaps in childbearing care during the pandemic. We describe how an intentional transdisciplinary process led to development of a novel knowledge exchange vehicle that can improve health equity in perinatal services. We introduce the Quality Perinatal Services Hub, an open access digital platform to disseminate evidence based guidance, enhance health systems accountability, and provide a two-way flow of information between communities and health systems on rights-based perinatal services. The QPS-Hub responds to both community and decision-makers' needs for information on respectful maternity care. The QPS-Hub is well poised to facilitate collaboration between policy makers, healthcare providers and patients, with particular focus on the needs of childbearing families in underserved and historically excluded communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.030 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.034 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.004 | 0.013 |
| Insufficient payload (model declined to judge) | 0.005 | 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".