EMPIRICAL STUDY Illustrating the (in)visible: Understanding the impact of loss in adults living with secondary lymphedema after cancer
Bibliographic record
Abstract
Life with a disability is often riddled with paradoxes, one of which is being visibly marked, while personal experiences, losses, and challenges remain hidden. Our article draws attention to this paradox among people who live with secondary lymphedema after cancer (SLC). SLC is a relatively unfamiliar chronic condition within medical and lay discourses of cancer, which proves challenging for the many cancer survivors who are in search of information and understanding. Thirteen men and women with SLC were recruited from two research sites (Fredericton, NB, and Ottawa, ON, Canada) to participate in semi-structured interviews about the physical and psychosocial aspects of SLC. Using a methodology of interpretive description, our analysis of participant interviews reveals the complex ways in which men and women felt both visible and invisible within various contexts. We discuss three majors themes: (in)visibility and appearance related to material losses; (in)visibility and action connected to visible losses in function, as well as invisible struggles to care for oneself; and the loss of present and future well-being, as SLC renders some limitations visible while potentially obscuring a hopeful future indefinitely. Our research indicates that timely diagnosis of SLC would be an immediate first step in recognizing the physical and emotional dimensions of the condition. To accomplish this, increased awareness is needed. To enhance quality of life for those living with SLC, the development of new resources and psychosocial supports is also required.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| 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".