How can family nurse practitioners reduce barriers to intrauterine devices among Canadian women?
Bibliographic record
Abstract
Canada continues to struggle with high rates of unplanned pregnancies resulting in significant health, financial, and social implications. The best strategy in preventing unplanned pregnancies is with regular use of reliable and safe contraception. In Canada, most women rely on oral hormones and male condoms as their primary means of contraception, despite their reduced efficacy. IUDs, on the other hand, are a highly reliable, safe and reversible form of contraception, yet many Canadian women do not use them. A thorough literature review found that many factors act as barriers to IUD use in Canada, which were found to be impeding IUD use in Canada. Three categories of barriers to IUD use were identified: those associated with the IUD user, those associated with the healthcare provider, and those associated with the healthcare system. In response to these barriers, I have targeted a collection of strategies that could be implemented to help reduce them to assure reliable accessibility to IUDs 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 | 0.003 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".