Bioethics in Childbirth Care: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: Ensuring women's rights during childbirth care based on humanized and bioethical principles results in better quality of care and patient safety and provides positive childbirth experiences. OBJECTIVE: We aim to explore the available evidence on the application of bioethical principles in the general context of childbirth care. METHODS: Our scoping review will follow the Joanna Briggs Institute Reviewer's Manual. Published and unpublished bibliographic materials will be considered based on the following inclusion criteria: reports of the application of bioethical principles (concept) in assistance to the predelivery, childbirth, and postpartum periods (population) in the hospital context (context). We will search for relevant studies in PubMed and the Virtual Health Library, including MEDLINE, LILACS, BDENF, SCiELO, Web of Science, and Google Scholar. Two reviewers will perform the screening of titles and abstracts, read the full texts, and extract data from the selected articles. The data will then be organized and expressed into categories based on their content. RESULTS: The analyzed data will be presented through flowcharts, tables, and descriptive narratives. A paper summarizing the findings from this review will be published in a peer-reviewed journal. In addition, a synthesis of the key findings will be disseminated to health services linked to university hospitals in Brazil. They will also be shared with the academic community and policy makers involved in the Childbirth Assistance Network, which will potentially adopt our recommendations in their decision-making process regarding childbirth care practice in Brazil. CONCLUSIONS: The findings from this review will inform, through the translation of knowledge, childbirth support groups, feminist movements, movements in favor of humanization of childbirth, and other childbirth support networks in the country. TRIAL REGISTRATION: Open Science Framework; https://osf.io/kczyr/.
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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 | 0.144 | 0.159 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.015 | 0.014 |
| Bibliometrics | 0.019 | 0.019 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.082 | 0.017 |
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".