Marathon maternity oral history project: Exploring rural birthing through narrative methods.
Bibliographic record
Abstract
OBJECTIVE: To explore how birthing and maternity care are understood and valued in a rural community. DESIGN: Oral history research. SETTING: The rural community of Marathon, Ont, with a population of approximately 3500. PARTICIPANTS: A purposive selection of mothers, grandmothers, nurses, physicians, and community leaders in the Marathon medical catchment area. METHODS: Interviews were conducted with a purposive sample, employing an oral history research methodology. Interviews were conducted non-anonymously in order to preserve the identity and personhood of participants. Interview transcripts were edited into short narratives. Oral histories offer perspectives and information not revealed in other quantitative or qualitative research methodologies. Narratives re-personalize and humanize medical research by offering researchers and practitioners the opportunity to bear witness to the personal stories affected through medical decision making. MAIN FINDINGS: Eleven stand-alone narratives, published in this issue of Canadian Family Physician, form the project's findings. Similar to a literary text or short story, they are intended for personal reflection and interpretation by the reader. Presenting the results of these interviews as narratives requires the reader to participate in the research exercise and take part in listening to these women's voices. The project's narratives will be accessible to readers from academic and non-academic backgrounds and will interest readers in medicine and allied health professions, medical humanities, community development, gender studies, social anthropology and history, and literature. CONCLUSION: Sharing personal birthing experiences might inspire others to reevaluate and reconsider birthing practices and services in other communities. Where local maternity services are under threat, Marathon's stories might contribute to understanding the meaning and challenges of local birthing, and the implications of losing maternity services in rural Canada.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".