“Mourning Parts You Dreamed of Losing—But Not This Way”: The Experience of a Nonbinary Person Diagnosed With Breast Cancer
Bibliographic record
Abstract
Purpose: Nonbinary breast cancer (NBBC) patients have unique healthcare needs that may not be met due to the gendered nature of breast cancer. Herein we explore the multifaceted experiences of an NBBC person. Methods: Qualitative intensive case study methodology was employed. Multisource data was gathered, including an in-depth interview, blogposts examination, and drawn comic evaluation analyzed using polytextual thematic analysis to generate themes. Methodologic rigor was pursued using member checking, maintaining an audit trail and holding several meetings to agree upon themes. Results: The participant's treatment included a double mastectomy, chemotherapy, and radiation. Using multisource triangulation, four themes were identified, named leading , negotiating , being in-between , and confining . Leading encompasses feeling the responsibility of paving the way for NBBC patients. The participant described, for instance, how their blogposts were created as a resource, to ameliorate the “lack of representation” they felt clinically and online. Negotiating encapsulates negative experiences in healthcare settings and having to mentally prepare before entering them. In both interview and blogpost, they mentioned “going into medical spaces [preparing] to be misgendered”. Being in-between highlights their intersecting identities shared in their blogposts, and the lack of support groups that supported their intersecting identities, “I felt like an island.” Finally, confining captures the lack of control they felt over their gender expression, which was especially salient during chemotherapy when they were hyperaware of how they were perceived “I don’t know if [people] see the baldness and flatness as a choice.” Conclusion: This individual experienced significant psychosocial stress from isolation, misgendering, and gender dysphoria magnified by the pink-washing of their breast cancer journey.
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 | 0.000 | 0.001 |
| 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".