Mental Health and Distress as a Social Justice Issue: Guest Editors’ Preface and Acknowledgments
Bibliographic record
Abstract
When we conceived this project in January 2015, we decided to focus on pulling together critical research to examine, document, and problematize the pathological approach to human being by interrogating the increasing psychiatrization of human life and social problems.The biomedical or "psychocentric" approach has proliferated throughout society and can be seen in popular cultural expressions, organizational cultures, and academic discourse alike.The hegemony operates on different levels and through multiple mechanisms that blame the individual and thus erase the social context and social bases of many individualized problems in neoliberal society.Thus, in neoliberal culture, the forces of pathological individualism proliferate while social structural factors at play in mental, emotional, physical and social lives are expunged or downplayed.Implicit in our approach is the view that the struggle for mental health justice is a significant yet still largely unaddressed and unrecognized public health concern.It is our hope that this special issue will initiate a larger discussion about the mental and emotional problems and needs in our communities as a basic human right.It is in this vein that these essays seek to provide critical poststructuralist frameworks that interrogate the assumptions and certainties embedded in our extremely psychocentric cultural attitudes, beliefs, desires, and practices concerning the normal and the pathological.Our objective is to examine mental and emotional health and distress/difference as a social justice issue by examining the ways in which
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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 | 0.012 | 0.073 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.009 | 0.022 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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".