First and Second-Trimester Surgical Abortion Providers and Services in 2019: Results From the Canadian Abortion Provider Survey
Bibliographic record
Abstract
OBJECTIVE: Our objective was to explore the workforce and clinical care of first and second-trimester surgical abortion (FTSA, STSA) providers following the publication of the updated Society of Obstetricians and Gynaecologists of Canada (SOGC) surgical abortion guidelines. METHODS: We conducted a national, cross-sectional, online, self-administered survey of physicians who provided abortion care in 2019. This anonymized survey collected participant demographics, types of abortion services, and characteristics of FTSA and STSA clinical care. Through healthcare organizations using a modified Dillman technique, we recruited from July to December 2020. Descriptive statistics were generated by R Statistical Software. RESULTS: We present the data of 222 surgical abortion provider respondents, of whom 219 provided FTSA, 109 STSA, and 106 both. Respondents practiced in every Canadian province and territory. Most were obstetrician-gynaecologists (56.8%) and family physicians (36.0%). The majority of FTSA and STSA respondents were located in urban settings, 64.8% and 79.8%, respectively, and more than 80% practiced in hospitals. More than 1 in 4 respondents reported <5 years' experience with surgical abortion care and 93.2% followed SOGC guidelines. Noted guideline deviations included that prophylactic antibiotic use was not universal, and more than half of respondents used sharp curettage in addition to suction. Fewer than 5% of STSA respondents used mifepristone for cervical preparation. CONCLUSION: weeks.
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 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".