Addressing injustices toward individuals with schizophrenia-spectrum conditions: a call to action for social work practice
Bibliographic record
Abstract
The field of social work has a lengthy history of training social workers for community mental health settings, and an ethical commitment to advance human rights and social justice. However, individuals with schizophrenia-spectrum conditions continue to suffer from myriad social injustices, including poverty, social isolation, and lower-life expectancy. This paper outlines these injustices, and reviews historical social work contributions and current training for supporting this population. Finally, the authors outline actions to 1) adopt national practice guidelines that formally acknowledge injustices, including anti-oppressive practice guidelines that are inclusive of lived experience, and 2) revitalize social work’s contributions to models of care for schizophrenia-spectrum populations.
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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 | 0.054 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.021 | 0.036 |
| Scholarly communication | 0.016 | 0.021 |
| Open science | 0.005 | 0.028 |
| Research integrity | 0.024 | 0.046 |
| 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".