Giving Birth Outside the Health Care System in New Brunswick: A Qualitative Investigation
Bibliographic record
Abstract
Introduction: There is limited research data on unassisted childbirth (a planned out-of-hospital birth without the attendance of a regulated care provider) in Canada; this means that there is a lack of understanding of its prevalence and of the childbearing women’s motivations. This study aimed to uncover women’s reasons for planning to give birth in the absence of an attendant licensed to practice in New Brunswick, in order to create insight into mainstream maternity care practices through those who have rejected them. Methods: In-depth qualitative interviewing with women who have had planned home births in New Brunswick in the past 10 years. Results: Participants had a variety of motivations and influences that played in their decision to have an unassisted home birth, including deeply held beliefs about childbirth and the need to manifest these beliefs in their experiences of birth. Participants expressed their desire to be the locus of control in their childbirth experience and believed they could best accomplish this outside of the hospital setting. Influences included ideological stance toward birth, the attitudes of their families and friends, and birth stories they had heard. Conclusion: This study demonstrates that when women’s needs are not met by mainstream health services, some will choose to give birth in the absence of a skilled provider or independent attendant. This gives rise to the need for discussion between all care providers and parturient women to better understand unmet needs and unaddressed fears around hospital birth. This article has been peer reviewed.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.020 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".