"It's Not Always Named": Critical Perspectives on Antiracist Dialectical Behaviour Therapy with Racialized Youth
Bibliographic record
Abstract
Dialectical behaviour therapy (DBT) is a respected therapeutic modality that is broadly used in youth mental health care. Yet, there is a paucity of research on its applicability to and effectiveness for racialized clients. DBT is an evidence-based practice that rests on the dominant Eurowestern knowledge base of the mental health disciplines, rendering it a potential tool of domination. Some argue that critical race theory and critical race psychology can be used to develop an antiracist DBT framework, however, this approach is yet to be studied in practice. Using the lenses of critical race theory, critical race psychology, and postcolonial psychiatry, this research explores how critical practitioners account for race in practice and imagine possibilities for an antiracist DBT framework with racialized youth clients. Through semi-structured interviews with practitioners who integrate critical perspectives into their DBT work with racialized youth, this study highlights emerging themes related to critiquing and adapting DBT foundations, the relational foundation of cultural humility, and reimagining DBT through critical justice-oriented frameworks. This research seeks to contribute to the urgent need for therapeutic approaches which attend to race for racialized youth, who face disproportionate vulnerabilities in a mental health care system with an unrepresented dialectic of a fundamentally racist society.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.036 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".