Bibliographic record
Abstract
Denne artikel er et empirisk bidrag, som illustrerer dele af et decentraliseret sundheds- system, der har en recovery-orienteret tilgang til psykisk sygdom. Den er baseret på 4,5 måneders feltarbejde i Vancouver, der fandt sted i den verdensomspændende mentale sund- hedsorganisation Clubhouse (også kendt som Fountain House). Artiklen fremhæver, hvor- dan ”recovery” indeholder en dobbelthed, da ”recovery” både rummer muligheden for at få en bedre (en ”mere produktiv og meningsfuld”) fremtid, men samtidig bliver denne mulig- hed til et krav. Baseret på deltagerobservation og interviews med personale og medlemmer undersøger denne artikel, hvordan personalet føler sig forpligtet til at regulere og begrænse sig selv og træk ved deres psykiske sygdom for at kunne leve op til den standard for ”selv- kontrol”, som de skal lære medlemmerne gennem recovery-processen. Jeg argumenterer for, at handlingen af at skjule en bestemt adfærd gør personalet til et forskønnet – og dermed misvisende - peer-forbillede. Jeg påpeger, at denne misvisende forskønnelse kan skabe en urealistisk standard for, hvad det vil sige at leve med psykisk sygdom. Artiklen lægger således op til at overveje, om vi, ved at acceptere at nogle mennesker evner recovery, og andre ikke gør, ligeledes fjerner incitamentet til at lede efter årsager og forbedringer udenfor individet.
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 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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.344 | 0.177 |
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".