A Narrative Inquiry into the Experiences of Cervical Cancer Screening for Transgender Men
Bibliographic record
Abstract
This monograph-style dissertation delves into the experiences of cervical cancer screening (CCS) among four transgender men residing in Saskatchewan. CCS traditionally has been framed within the context of women's reproductive health, and it has seldom been inclusive of non-binary, gender-diverse, or transgender individuals. I noticed the need for more information when I started graduate school and began reflecting on my nursing practice. Nurses are usually providers on the front line who provide healthcare for transgender people. Nurses with advanced practice, including nurse practitioners, can routinely perform CCS. It was in my practice as a public health nurse providing CCS that I began to wonder about the experiences of transgender men and CCS. I wanted to come alongside transgender men to understand how to improve CCS experiences for transgender men.\nIn adopting narrative inquiry as the research methodology, I embraced a relational approach guided by the three-dimensional inquiry space: temporality, sociality, and place (Clandinin, 2013; Clandinin & Caine, 2013; Clandinin & Connelly, 2000). The narrative accounts intend to capture individual lives and the unique history of each participant. Participants met with me in person or over Zoom to engage in interviews spanning several months and engaged in open-ended conversations about life events influencing their CCS experiences. Narrative accounts shared multiple and layered details of their lives. Each participant has a detailed chapter where they shared not only narratives of CCS but narratives that explored the complex experiences within many different facets of life, including personal, social, and institutional stories (Clandinin & Rosiek, 2007). Within each person's narrative account, I found stories of how we can attend to people in a better, more holistic, and inclusive way.\nIt is increasingly important in today's political and social climate for healthcare providers (HCPs) to pay attention to the voices and experiences of transgender people. When exploring narrative threads across accounts, stories of healthcare, holistic health, and family and friends significantly shaped the participants CCS experiences. The narrative accounts of the four transgender men have implications across nursing practice, education, and policies. The stories embedded in this dissertation call for more inclusive, knowledgeable, and equitable care for transgender people in Saskatchewan.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.014 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".