How do midwives facilitate women to give birth during physiological second stage of labour? A protocol for a systematic review
Bibliographic record
Abstract
BACKGROUND: Midwives' practices during the second stage of labour vary nationally and internationally. We aim to retrieve evidence that supports high-quality intrapartum care by conducting a systematic review of the literature. METHODS: Electronic bibliographic databases including PubMed, EMBASE.com , Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, Maternity and Infant Care Database (through MIDIRS), and The Cochrane Library will be searched to identify studies that meet the inclusion criteria. No language or publication date constraints will be applied. Articles that pass the two-stage screening process will then be assessed for risk of bias and have their reference lists hand searched. DISCUSSION: A midwife's practice can be influenced by education and cultural practices but ultimately it should be informed by up-to-date research evidence. By analysing and synthesising the results of the studies, this systematic review will provide valuable insight into high-quality evidence-based midwifery care, which can inform practice, education and future research. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42018088300.
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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 | 0.112 | 0.113 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.014 | 0.016 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.055 | 0.010 |
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".