Getting to the Root of the Problem: Supporting Clients With Lived-Experiences of Systemic Discrimination
Bibliographic record
Abstract
For many marginalized people, coping with discrimination is not a temporary condition. Rather it is endemic to living in a discriminatory society and a source of ongoing stress. In this paper, we explore the need to provide people struggling to cope with the skills to tackle not just the personal consequences of discrimination, but also to understand and address the root causes of their pain, and specifically the ones that lie outside of themselves. We propose using the concept of social capital to bring greater awareness among clients, clinicians, and society in general about the need to pair the treatment of personal distress with concurrent practices to understand and tackle larger systemic issues impacting their mental health. People with marginalized identities are often expected to find ways to cope with oppression and then sent back into a broken world, perhaps with stronger coping skills, but often ones which do not address the root cause or source of the pain, which is social injustice. We propose that it is therapeutically important to problematize, pathologize and address the systems and narratives that discriminate and cause people to need to cope, instead of focusing therapeutic interventions only on the internal resources of the person doing the coping.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".