“I would love for there not to be so many hoops … ”: recommendations to improve abortion service access and experiences made by Indigenous women and 2SLGTBQIA+ people in Canada
Bibliographic record
Abstract
Acknowledging the barriers in accessing sexual and reproductive health services that disproportionately impact Indigenous women and 2SLGTBQIA+ people, coupled with the lack of knowledge surrounding Indigenous peoples' experiences with abortion, we present qualitative findings from a pilot study investigating Indigenous experiences of accessing abortion services in Canada. We focus on findings related to participant recommendations for improving safety and accessibility of abortion services made by and for Indigenous people in Canada. Informed by an Indigenous Advisory Committee consisting of front-line service providers working in the area of abortion service access and/ or support across Canada, the research team applied an Indigenous methodology to engage with 15 Indigenous people across Canada utilising a conversational interview method, between September and November 2021. With representation from nine provinces and territories across Canada, participants identified with Anishinaabe, Cree, Dene, Haudenosaunee, Inuit, Métis and/ or Mi'kmaq Nations. Five cross-cutting recommendations emerged, including: (1) location, comfort, and having autonomy to choose where the abortion takes place; (2) holistic post-abortion supports; (3) accessibility, availability, and awareness of non-biased and non-judgemental information; (4) companionship, advocacy, and logistical help before and during the abortion from a support person; and (5) cultural safety and the incorporation of local practices and knowledges. Recommendations demonstrate that Indigenous people who have experienced an abortion carry practical solutions for removing barriers and improving access to abortion services in the Canadian context.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.037 | 0.013 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".