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Record W2029468682 · doi:10.1080/13811118.2011.616154

The Possible Risks of Self-Injury Web Sites: A Content Analysis

2011· article· en· W2029468682 on OpenAlex
Stephen P. Lewis, Thomas G. Baker

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueArchives of Suicide Research · 2011
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPoison controlInjury preventionContent analysisHuman factors and ergonomicsOccupational safety and healthSuicide preventionEnvironmental healthMedical emergencyMedicine

Abstract

fetched live from OpenAlex

The goal of this study was to examine the content of non-suicidal self-injury (NSSI) Web sites, often shared via e-communities. Using a content analysis, 71 Web sites were investigated. Web sites depict NSSI as: an effective coping mechanism (91.55%), addictive and difficult to stop (87.23%), and not always painful (23.94%). Almost all Web sites had melancholic tones (83.10%); several contained graphic photography (29.58%). Most NSSI messages (61.97%) were ambivalent (NSSI-accepting and deterring). Finally, several Web sites (11.27%) provided testimony that NSSI-content is triggering. Findings mirror recent work and NSSI material on these Web sites may normalize and reinforce NSSI. Professionals may need to assess the online activity of individuals who self-injure. Despite its risks, the Internet may serve as a vehicle to reach those who self-injure.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.372
GPT teacher head0.458
Teacher spread0.086 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it