Recovery : the experts' experience of formal and informal supports
Bibliographic record
Abstract
This thesis explores the experience of recovel'y from a persistent ment¿tl illness ancl suppofts that facilitate it.The experts were consulted through a process of naruative interviews where they shared their experience of recovery.Seve n participants were interviewed, 2 rnen and 5 women.They had each been diagnosed with one of the following mental illnesses: schizophrenia, bipolar disolder or clepression.They had been manergin-9 the illness fbr at least 5 yeals and had not had a hospitalization in the 2 years prior to being inten,iewed.Grouncled theory was used in an efïort to Lrncover common themes in their experience of recovery.Two theories emerged including commonìy experienccd supports that f acilitated recovery and a distinction between the.jor-rrney to clia-enosis and the -joulney to recovery.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".