Systems, definitions and identity : the socio-political disability/illness identity triangle
Bibliographic record
Abstract
Lived experiences of people with multiple sclerosis (MS) are explored vis-vis: 1) disability support program & service systems, & disability organizations, including a Disability Rights Organization & a Disease-Specific Voluntary Health Agency; 2) definitions of disability & chronic illness in Disability Studies, Feminist Disability & Population Health Discourse & definitions in disability policy; &, 3) self & collective identity before & after diagnosis vis--vis the first two dimensions.Qualitative participatory methods ouflined by Ristock & pennell (1996) were used.The study was guided by an advisory committee of people with MS, the Manitoba League of Persons with Disabilities (MLPD) & the Multiple sclerosis society of canada, Manitoba Division (MSSC).A sample of s women and 1 man, reflecting a broad representation of socio-economic, ethnic background, living arrangement, MS related impairments & association with primarily the MSSC found the following: 1) 'disability identity' is viewed negatively, influenced also by experience prior to MS; 2)the existence of a disconnect between critical awareness of social model definitions, self identity, & group identfcation; 3) cognitive dissonance caused by contradictions between policy definitions and self identity; 4) perceptions of definitions of 'disability' & 'chronic illness' are as varied as those in the literature; 5) accessing support services pre & post MS is dramatically different.The implications of these findings are discussed.ilt 6.To explore the implications of this information in terms of coalition building between disability advocacy groups such as the MLPD and voluntary health agencies such as the MSSC.Learninq Obiectives 1.To develop comprehensive understanding and skill in participatory research methods.2. To develop comprehensive understanding and skill in qualitative research methods.3. To develop comprehensive understanding and skill in research from a social- political disabi lity framework Following the introduction, Chapter One provides background information, including the 'disease' context of the research, the partner organizations, a discussion of terms and a literature review of disability definitions, models of disability, feminist disability discourse, population health principles, the chronic illness and disability dialectic, and a brief environmental scan.Chapter two details the methods, and chapter three entails findings and discussion.Chapter four is a discussion of the implications of the research and self-reflections on the work.Conclusions, references, bibliography and appendices follow this.
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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 | 0.001 | 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 | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".