EXPLORING MI'KMAQ WOMEN'S EXPERIENCES WITH PAP SMEAR SCREENING IN NOVA SCOTIA
Bibliographic record
Abstract
Mi’kmaq women in Nova Scotia are reported to have lower rates of Papanicolaou (Pap) smear screening and have higher rates of cervical cancer compared to non-Aboriginal women. Much of the cervical cancer literature reflects mainstream values and tends to essentialize Aboriginal women as one at-risk homogenous group lacking knowledge about cervical cancer prevention. The primary purpose of this qualitative participatory study was to explore Mi’kmaq women’s and primary healthcare providers’ experiences with Pap smear screening and to consider the broader historical, economic, and socio-political contexts that shape those healthcare experiences. Mi’kmaq women’s experiences accessing Pap screening services, their encounters with healthcare providers and the health care system, and women’s past experiences with Pap smear screening were also explored. This inquiry was grounded in postcolonial feminist perspectives and Indigenous principles in a two-eyed seeing approach. Community facilitators were identified to assist with recruitment and the research process. Women participated in talking circles to learn about and shape the study. Sixteen Mi’kmaq women and five healthcare providers participated in two semi-structured interviews. Five themes were identified from the women: a) Finding Our Way, b) Our Understanding and Perceptions about Pap Smear Screening, c) The Impact of History on Our Health and Healthcare Experiences, d) Healthcare Providers’ Encounters: “Making a Difference in Our Path to Paps,” and e) “The Healthcare System is Complicating Our Going for Paps.” Two themes were identified from healthcare providers: a) Understanding the Realities of Aboriginal Women’s Lives and b) Fostering Aboriginal Women’s Access to Pap Smear Screening. This research contributes to an understanding of the continued impact of wider historical, political, and socioeconomic conditions that have resulted from colonialism, residential schools, and assimilation on Pap smear screening. It reinforces the importance of not essentializing women’s views or experiences and recognizing that some are accessing Pap smear screening regularly in spite of challenging circumstances. Mi’kmaq women have been underrepresented in the previous Pap smear screening literature. It is critical that healthcare providers understand how they can improve access to Pap smear screening and the screening process itself.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".