Situating Wikipedia as a health information resource in various contexts: A scoping review
Bibliographic record
Abstract
BACKGROUND: Wikipedia's health content is the most frequently visited resource for health information on the internet. While the literature provides strong evidence for its high usage, a comprehensive literature review of Wikipedia's role within the health context has not yet been reported. OBJECTIVE: To conduct a comprehensive review of peer-reviewed, published literature to learn what the existing body of literature says about Wikipedia as a health information resource and what publication trends exist, if any. METHODS: A comprehensive literature search in OVID Medline, OVID Embase, CINAHL, LISTA, Wilson's Web, AMED, and Web of Science was performed. Through a two-stage screening process, records were excluded if: Wikipedia was not a major or exclusive focus of the article; Wikipedia was not discussed within the context of a health or medical topic; the article was not available in English, the article was irretrievable, or; the article was a letter, commentary, editorial, or popular media article. RESULTS: 89 articles and conference proceedings were selected for inclusion in the review. Four categories of literature emerged: 1) studies that situate Wikipedia as a health information resource; 2) investigations into the quality of Wikipedia, 3) explorations of the utility of Wikipedia in education, and 4) studies that demonstrate the utility of Wikipedia in research. CONCLUSION: The literature positions Wikipedia as a prominent health information resource in various contexts for the public, patients, students, and practitioners seeking health information online. Wikipedia's health content is accessed frequently, and its pages regularly rank highly in Google search results. While Wikipedia itself is well into its second decade, the academic discourse around Wikipedia within the context of health is still young and the academic literature is limited when attempts are made to understand Wikipedia as a health information resource. Possibilities for future research will be discussed.
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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 | 0.021 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.032 | 0.025 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".