Leveraging the Strengths of Psychologists With Lived Experience of Psychopathology
Bibliographic record
Abstract
Psychopathology is a common element of the human experience, and psychological scientists are not immune. Recent empirical data demonstrate that a significant proportion of clinical, counseling, and school psychology faculty and graduate students have lived experience, both past and present, of psychopathology. This commentary compliments these findings by leveraging the perspectives of the authors and signatories, who have personal lived experience of psychopathology, to improve professional inclusivity in these fields. By "coming out proud," the authors aim to foster discussion, research, and inclusion efforts as they relate to psychopathology experiences in psychological science. To that end, the authors describe considerations related to disclosure of lived experience, identify barriers to inclusion, and provide concrete recommendations for personal and systemic changes to improve recognition and acceptance of psychopathology lived experience among psychologists.
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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 | 0.022 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.057 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.002 | 0.026 |
| Research integrity | 0.005 | 0.014 |
| 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".