Science and Service: Doula Work and the Legitimacy of Alternative Knowledge Systems
Bibliographic record
Abstract
This dissertation explores the knowledge systems that doulas use to legitimate their work to the medical community, and to clients. "Doula" comes from a Greek word that means "a woman who serves." In contemporary English, doulas are women who provide other women with support during labor and childbirth. Although research shows that doula support can have positive physiological and psychological effects, doulas' lower social status in the birth fields constricts their reach to those who know about and can hire them privately. In the United States, obstetricians have authoritative knowledge over birth, and all others fall beneath them in the hierarchy of medicine. Doulas serve as a case for exploring the importance of certification and science, versus alternative forms of knowledge for legitimating their expertise within the field of childbirth. This research uses a mixed methods approach to explore the roles that authoritative versus alternative sources of knowledge play in doulas' attitudes and approaches to childbirth. Data come from the Maternity Support Survey, an original, cross-national survey of nurses, doulas, and childbirth educators in the United States and Canada. I also rely on content analysis of five large doula organizations' websites, and interviews with twenty-five doulas, and twenty-five mothers who hired or considered hiring a doula to support them during labor and delivery. This mixed methods research looks at how doulas can legitimate their role in order to better serve women.Results suggest that both authoritative knowledge systems (such as certification) and alternative knowledge systems (such as feminism) influence doulas' approach to legitimating their work. Scientific evidence serves as both an authoritative and alternative source of knowledge, depending on the context. This research has important implications for the future of doula support; while alternative knowledge systems allow doulas to empower women and challenge the dominance of medicalized birth, authoritative knowledge systems allow doulas greater access to the women who need them most. In order to reach a greater population of women, doulas need to find a balance between challenging authoritative medicine and working within it to best serve women.
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 | 0.035 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.018 | 0.086 |
| Scholarly communication | 0.032 | 0.030 |
| Open science | 0.003 | 0.022 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".