Ana and the Internet: A review of pro‐anorexia websites
Bibliographic record
Abstract
OBJECTIVE: The purpose of this article is to describe the content of pro-anorexia websites, both qualitatively and quantitatively. METHOD: An Internet search protocol was developed to identify pro-anorexia websites. A grounded theory approach was used to generate themes from Internet-based information. Basic descriptive analysis was employed to report on key website characteristics. RESULTS: Twenty pro-anorexia websites met inclusion criteria. Saturation of themes was achieved after review of 12 websites. Key website characteristics included purpose of website (75%), information about webmaster (67%), website disclaimers (58%), and information on "tips and tricks" (67%). Religious metaphors, lifestyle descriptions, and "thinspiration" (inspirational photo galleries and quotes that aim to serve as motivators for weight loss) were frequently present. A total of 10 themes were generated. The most prevalent themes included control, success, and perfection. CONCLUSION: Health-care providers and caregivers should be aware of pro-anorexia websites and their content, as these websites contain information that promote and support anorexia nervosa.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".