Examining Cesarean Section Rates in Canada Using the Modified Robson Classification
Bibliographic record
Abstract
OBJECTIVE: Canada's cesarean delivery (CD) rate continues to increase. The Society of Obstetricians and Gynaecologists of Canada advocates the use of the modified Robson classification for comparisons. This study describes national and provincial CD rates according to this classification system. METHODS: All 2016-2017 in-hospital births in Canada (outside Québec) reported to the Discharge Abstract Database were categorized using the modified Robson classification system. CD rates, group size, and contributions of each group to the overall volume of CD were reported. Rates by province and hospital peer group were also examined (Canadian Task Force Classification III). RESULTS: A total of 286 201 women gave birth; among these, 83 262 (29.1%) had CDs. Robson group 5 (term singleton previous CD) had a CD rate of 80.5% and was the largest contributing group to the overall number of CD (36.6%). Women whose labour was induced (Robson group 2A) had a CD rate almost double the rate of women with spontaneous labour (Robson group 1): 33.5% versus 18.4%. These latter two groups made the next largest contributions to overall CD (15.7% and 14.1%, respectively). There were substantial variations in CD rates across provinces and among hospital peer groups. CONCLUSION: The study found large variations in CD rates across provinces and hospitals within each Robson group, thus suggesting that examining variations to determine the groups contributing the most to CD rates (Robson groups 5, 2A, and 1) may provide valuable insight for reducing CD rates. This study provides a benchmark for measuring the impact of future initiatives to reduce CD rates in Canada.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".