Bibliographic record
Abstract
It has been over thirty years since the decriminalization of abortion across Canada, however, many in need continue to face barriers accessing the healthservice (Erdman, 2017). Maritime provinces are known across the literature to have poor access to abortion services (Eggertson, 2001; Sethna & Doull, 2012; Sethna & Doull, 2013), yet little academic research has been conducted on the state of abortion acesss within the Nova Scotian context. This study seeks to provide an overview of the current state of abortion access across the province, identify prevalent barriers that impede patient access to abortion services and review the effectiveness of guiding legislation and policy, such as the Nova Scotia Department of Health and Wellness’ Framework for a High Perfoming Health and Wellness System (NS DHW Framework) and the Canada Health Act (CHA), in operationalizing access to healthcare services such as abortion. Barriers present within the current operations of the public healthcare system were identified by study participants as the most prominent barriers to abortion access in Nova Scotia. The study also identified significant disparities in abortion access between those living within rural and urban areas of Nova Scotia. Study participants made several recommendations to improve abortion access across the province, the majority of which concerned changes to be made within the current opertations and policies of the public healthcare system in Nova Scotia. The lack of primary care physicians across the province directly contributes not only to the poor access of abortion services but of all healthservices across Nova Scotia. Future studies concerning patient-identified barriers to abortion services specifically focused on marginalized populations are recommended for developping a better understanding of abortion access across Nova Scotia.
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".