Bibliographic record
Abstract
Abstract This book draws on more than 25 years of experience developing and evaluating anti-stigma programs to reduce negative and unfair treatment experienced by people with a mental or substance use disorder. It builds on a previous edition, Paradigms Lost: Fighting Stigma and the Lessons Learned, that identified new approaches to stigma reduction. This volume examines the newest approaches to stigma reduction with respect to structural stigma, public stigma, and internalized stigma. The goals of anti-stigma work must be to eliminate the social inequities that people with mental and substance use disorders and their families face to promote their full and effective social participation. Awareness raising and mental health literacy are important, but they do little to change the accumulated practices of social groups and social structures that systematically disadvantage those with mental and substance use problems. The book is written with one eye to the past (what we have done well) and one to the future (what we must still do). It goes into depth in targeted areas such as healthcare, workplaces, schools, and the media. We expect that this edition will be a useful sequel to Paradigms Lost, chronicling what we have learned as a global community regarding stigma related to mental illness and substance use and stigma-reduction approaches.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.057 | 0.020 |
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".