Crazy, Weak, and Incompetent: A Directed Content Analysis of Self-Injury Stigma Experiences
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite significant impacts to mental health and support-seeking, non-suicidal self-injury (NSSI) stigma remains under-studied and poorly understood. Recently, the NSSI Stigma Framework was proposed, conceptualizing NSSI stigma as comprising six constructs (origin, concealability, course, peril, aesthetics, disruptiveness) that manifest across four perspectives (public, self, anticipated, enacted). The present study investigated the extent to which this framework can account for individuals’ NSSI stigma experiences using a directed content analysis. Written responses from 99 university undergraduates (Mage = 21.5, SD = 3.7; 83.8% female) generated 731 data units for analysis, of which 299 (40.9%) were coded. Results demonstrated support for the public and enacted perspectives, with participants describing stigma experiences within friendships, families, schools, and workplaces. Data pointed to both direct and indirect experiences of public stigma, suggesting a more nuanced understanding of this perspective is required. While there was sufficient support for a majority of elements, more work is needed to verify the applicability of the self and anticipated perspectives. Our findings contribute to a growing body of research investigating NSSI stigma, and provide preliminary support for the utility of the NSSI Stigma Framework in identifying multiple facets of NSSI stigma. Implications for intervention and future research are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it