Nothing and Everything: Fibromyalgia as a Diagnosis of Exclusion and Inclusion
Bibliographic record
Abstract
The diagnostic process promises a label that validates patients' embodied experiences and a road map for living with and treating illness. Drawing on 31 qualitative interviews with women and men in Canada and the United Kingdom who have been diagnosed with fibromyalgia (FM), in this article, I examine the participants' experiences of the diagnostic process and how they feel about receiving this label. The interviews reflect that the FM label is plagued by uncertainty because the diagnosis is based on the absence of verifiable pathology. The respondents' narratives also reveal that FM is a vague diagnosis that includes a multitude of symptoms, overlaps with several other diagnoses, and results in feelings of doubt regarding whether it is the correct label. Thus, the participants' narratives reflect that the FM diagnosis is largely an empty promise because it fails to provide definitive answers or confer meaning and legitimacy to their illness experiences.
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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 | 0.021 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.045 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| 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".