Unmet contraceptive needs among refugees.
Bibliographic record
Abstract
OBJECTIVE: To describe what women of reproductive age who received primary care at a refugee health clinic were using for contraception upon arrival to the clinic, and to quantify the unmet contraceptive needs within that population. DESIGN: Retrospective chart review. SETTING: Crossroads Clinic in downtown Toronto, Ont. PARTICIPANTS: Women of reproductive age (15 to 49 years) who first presented for care between December 1, 2011, and December 1, 2012. To be included, a woman had to have had 2 or more clinic visits or an annual health examination. Exclusion criteria for the contraception prevalence calculation were female sexual partner, menopause, hysterectomy, pregnancy, or trying to conceive. MAIN OUTCOME MEASURES: Contraception use prevalence was measured, as was unmet contraceptive need, which was calculated using a modified version of the World Health Organization's definition: the number of women with an unmet need was expressed as a percentage of women of reproductive age who were married or in a union, or who were sexually active. RESULTS: Overall, 52 women met the criteria for inclusion in the contraceptive prevalence calculation. Of these, 16 women (30.8%) did not use any form of contraception. Twelve women were pregnant at some point in the year and stated the pregnancy was unwanted or mistimed. An additional 14 women were not using contraception but had no intention of becoming pregnant within the next 2 years. There were no women with postpartum amenorrhea not using contraception and who had wanted to delay or prevent their previous pregnancy. In total, 97 women were married or in a union, or were sexually active. Unmet need was calculated as follows: (12 + 14 + 0)/97 = 26.8%. CONCLUSION: There was a high unmet contraceptive need in the refugee population in our study. All women of reproductive age should be screened for contraceptive need when first seeking medical care in Canada.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".