Canadian educational resources about cannabis use and fertility, pregnancy and breast feeding: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Cannabis use in Canada is becoming more prevalent across all demographic groups due to increases in accessibility and lowered perceptions of harm. These patterns are mirrored among women of reproductive age, including women who are pregnant. Given increasing evidence for detrimental short- and long-term impacts of cannabis exposure on fetal, newborn and child outcomes, there is a need for high-quality, accessible resources providing reliable guidance and recommendations on this topic for both the public and healthcare providers. We will conduct a scoping review to identify and characterise all publicly available online educational resources discussing cannabis use related to fertility, pregnancy and breastfeeding developed by Canadian organisations. METHODS AND ANALYSIS: Using Arksey and O'Malley's scoping review methodology as a guide, we will search Medline (Ovid), Medline in Process (Ovid), Embase (Ovid), ERIC (Ovid), CINAHL (EBSCOhost) and Education Source (EBSCOhost). We will also conduct a grey literature search targeting the websites of national and independent Canadian obstetrical societies and networks, and government and public health offices that provide recommendations or guidance to individuals and their healthcare providers seeking information on cannabis use related to fertility, pregnancy or breastfeeding. ETHICS AND DISSEMINATION: Research ethics approval is not required for scoping review studies. We anticipate that this review's findings will be disseminated through traditional channels, including preprint and peer-reviewed publications and presentations at academic conferences. In addition, the resources and guidelines identified in the study will be gathered and made available online on a single comprehensive public repository. PROTOCOL REGISTRATION NUMBER: osf.io/p24y5.
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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 | 0.071 | 0.067 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.028 | 0.026 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.074 | 0.010 |
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".