Measuring the attitudes of midwives toward sexual and gender minority clients: Results from a <scp>Cross‐Sectional</scp> survey in Ontario
Bibliographic record
Abstract
BACKGROUND: In Canada, Ontario midwives provide care to sexual and gender minority (SGM) people. Published literature shows how midwives' attitudes shape the experiences of lesbians, but research examining midwives' attitudes toward SGM people is lacking. Our study measured the attitudes of Ontario midwives toward SGM clients, hypothesizing that attitudes would be positive overall and that there would be no difference in attitudes across practice settings. METHODS: Paper surveys (n = 926) with an option to respond online were sent to Ontario midwifery practices. We measured midwives' attitudes toward sexual minorities (11 questions, scores ranged from 11 to 55) and gender minorities (9 questions, scores ranged from 9 to 45), with higher scores indicating more positive attitudes. Overall and subgroup analyses were performed. RESULTS: The 268 completed surveys indicated that midwives' attitudes were positive toward both sexual (mean score 49.2, maximum possible score of 55, ie, 89.4%) and gender minorities (mean score 38.9, maximum possible score of 45, ie, 86.4%). Analyses showed that attitudes toward SGM were associated with midwives' sexual identity and route of entry into the profession (ie, university-based vs bridging programs), but not practice setting. CONCLUSIONS: Although attitudes of this subset of midwives toward SGM clients were positive, volunteer bias could account for this finding since 32.6% of respondents identified as sexual minorities. Since the attitudes of midwives who entered the profession through the university-based education program were significantly more positive than those who entered through international bridging programs, future research should examine how SGM-related content is integrated into midwifery education and training curricula.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".