Reducing the rate of teen pregnancy in Canada: A framework for action
Bibliographic record
Abstract
In partnership with the Young/Single Parent Support Network of Ottawa-Carleton and Timmin's Native Friendship Centre, the Canadian Institute of Child Health has completed a framework to reduce the rate of teen pregnancy in Canada. The final document is called Pro-Action, Postponement, and Preparation/Support: A Framework for Action to Reduce the Rate of Teen Pregnancy in Canada. The objectives were to learn what is currently being done and what needs to be done on this issue across the country, and to explore the potential role of projects funded by the federal Canada Action Program for Children (CAPC) and Canada Prenatal Nutrition Program (CPNP) in reducing the rate of teen pregnancy. Being an extremely complex and sensitive issue, the report was a culmination of a number of research methods: over 40 key informants from diverse backgrounds and expertise were interviewed to determine the scope of the problem and potential solutions; a detailed literature review identified existing date and documentation on the topic, using both Canadian and international studies; youth surveys and focus groups were conducted in both on-reserve Aboriginal communities and non-Aboriginal communities.
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 | 0.048 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.030 | 0.023 |
| Scholarly communication | 0.017 | 0.006 |
| Open science | 0.010 | 0.016 |
| Research integrity | 0.014 | 0.017 |
| Insufficient payload (model declined to judge) | 0.003 | 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".