Every scar tells a story: Insight into people’s self-injury scar experiences
Bibliographic record
Abstract
Scarring, a common and salient consequence of non-suicidal self-injury (NSSI), remains an under-explored issue in the field. Thus, the current investigation explored NSSI scar perspectives using online testimony from members of a popular NSSI message board; focus was attenuated to a series of message board posts pertinent to people's experiences with scars resulting from NSSI. Data (message board posts) were collected using the website's search function. A total of 53 posts involving discussion of people's NSSI scar perceptions and experiences were retained. A thematic analysis of the data indicated that individuals viewed their scars in a number of ways. Many viewed scars in a resilient manner, often in the context of a self-narrative. Others, however, were unaccepting of their scars (e.g. expressed feelings of shame, hatred, or disgust). For some, they were able to gradually accept their scars but only after a period of difficulty. And, finally, some individuals expressed mixed feelings toward their scars (e.g. a love/hate relationship). Hence, scars stemming from NSSI seem to differentially impact individuals who self-injure. Possible implications for research and clinical practice are discussed.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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 teacher head, 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".