Perinatal Mental Health in Hamilton and Montreal
Bibliographic record
Abstract
Mental health concerns experienced by individuals during or up to one year after pregnancy fall under the umbrella of perinatal mental health. Estimates suggest that one in five people will experience a perinatal mental illness at some point during their pregnancy or up to one year postpartum. Racialized individuals with low socioeconomic status are at an increased risk to perinatal mental health. Perinatal mental illness is becoming an incredibly relevant topic in the sphere of public health and policy. Recently, the Canadian Task Force on Preventive Health Care released a recommendation against screening individuals for depression during pregnancy and the postpartum period (up to 1 year after childbirth), stating that there is low certainty of evidence for such screening measures. This received backlash, with groups like the Canadian Perinatal Mental Health Collaborative (CPMHC) speaking out. Prime Minister Justin Trudeau and the Minister of Mental Health and Addictions aim to “ensure timely access to perinatal mental health services”, as identified in a recent mandate letter. Given its current salience, this piece seeks to explore perinatal mental health programs in Ontario and Quebec, critically analyze their effectiveness, and suggest future areas of improvement.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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".