Meaning-making in 'outsider art' as a reflection of stigma and marginalization in mental illness.
Bibliographic record
Abstract
The public engages directly with conceptions of mental illness through the meaning-making process in outsider art. Marginalization is acknowledged in current research as a considerable barrier to recovery from mental illness. The focus of this thesis is the critical visual analysis of meaning-making in outsider art to identify processes and practices which reinforce stigma and marginalization of artists diagnosed as mentally ill. The analysis of meaning-making processes at the sites of production, image and audience provides important insights for contemporary mental health research, policy and practice. Psychiatric/mental health knowledge, practices and research play a significant role in marginalization at the sites of meaning-making and so have considerable potential, authority and responsibility to reduce stigma and marginalization. Changing the process within mental health-arts has potential to reduce marginalization for artists with mental illness, increase inclusion and the reduce stigma of mental illness. --P.ii.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.066 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".