Bibliographic record
Abstract
Unfitting Stories: Narrative Approaches to Disease, Disability, and Trauma illustrates how stories about ill health and suffering have been produced and received from a variety of perspectives. Bringing together the work of Canadian researchers, health professionals, and people with lived experiences of disease, disability, or trauma, it addresses central issues about authority in medical and personal narratives and the value of cross- or interdisciplinary research in understanding such experiences. The book considers the aesthetic dimensions of health-related stories with literary readings that look at how personal accounts of disease, disability, and trauma are crafted by writers and filmmakers into published works. Topics range from psychiatric hospitalization and aestheticizing cancer, to father-daughter incest in film. The collection also deals with the therapeutic or transformative effect of stories with essays about men, sport, and spinal cord injury; narrative teaching at L’Arche (a faith-based network of communities inclusive of people with developmental disabilities); and the construction of a “schizophrenic” identity. A final section examines the polemical functions of narrative, directing attention to the professional and political contexts within which stories are constructed and exchanged. Topics include ableist limits on self-narration; drug addiction and the disease model; and narratives of trauma and Aboriginal post-secondary students. Unfitting Stories is essential reading for researchers using narrative methods or materials, for teachers, students, and professionals working in the field of health services, and for concerned consumers of the health care system. It deals with practical problems relevant to policy-makers as well as theoretical issues of interest to specialists in bioethics, gender analysis, and narrative theory. Read the chapter “Social Trauma and Serial Autobiography: Healing and Beyond” by Bina Freiwald on the Concordia University Library Spectrum Research Repository website.
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 | 0.000 |
| 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) | 0.002 | 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 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".