Why Do Midwives Stay? A Descriptive Study of Retention in Ontario Midwives
Bibliographic record
Abstract
This descriptive, exploratory study was designed to examine why Ontario midwives stay in clinical practice. AllregisteredmidwivesintheprovincewereinvitedtocompleteaWebbasedsurveyanda response rate of 37% was ascertained. Descriptive statistics were used to analyze quantitative data while inductive content analysis was employed to analyze qualitative data. Midwives enjoy their work and are highly committed to the profession. Relationships with clients and making a difference through their work are key factors in retention. Midwives report that autonomy in their work is another mediator of job satisfaction. Important support mechanisms for midwives include: relationships with their partner,colleagues and family. Barriers faced in clinical practice include: the need for greater flexibility in working patterns, as well as, conflict with hospitals with midwifery and/or non-midwifery colleagues. These findings are discussed and recommendations for future research are offered.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".