Stigmatizing Our Own: Self-Relevant Research (Me-Search) Is Common but Frowned Upon in Clinical Psychological Science
Bibliographic record
Abstract
How often do clinical psychologists have a lived experience with, or close connection, to their research? Does the field of psychology accept this “me-search”? We undertook the first investigation of self-relevant research (aka “me-search”) and attitudes toward self-relevant researchers in a representative North American sample ( N = 1,776) of faculty, graduate students, and other individuals affiliated with doctoral programs in clinical, counseling, and school psychology. More than 50% of participants had conducted self-relevant research, and those from minoritized backgrounds were more likely to conduct self-relevant research. When judging experimentally manipulated vignettes, participants who had not engaged in self-relevant research made more stigmatizing judgments of self-relevant research and self-relevant research disclosure than did those who engaged in self-relevant research. Psychologists and trainees had more negative attitudes toward self-relevant research on mental health topics (suicide, depression, schizophrenia) than physical health topics (cancer). We discuss how prejudice toward self-relevant research and mental illness negatively impacts ongoing diversity and inclusion efforts from within clinical psychological science.
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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 | 0.076 | 0.178 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.008 | 0.028 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.003 | 0.005 |
| 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".