Citations in Wikipedia for understanding research reach
Bibliographic record
Abstract
Objective: Wikipedia is the most frequently accessed online health information resource and is well positioned as a valuable tool for public health communication and knowledge translation. The authors aimed to explore their institution's health and medical research reach by analyzing its presence in Wikipedia articles. Methods: In October 2022, a comprehensive database search was constructed in PubMed to retrieve clinical evidence syntheses published by at least one author affiliated with McMaster University from 2017 to 2022, inclusive. Altmetric Explorer was queried using PubMed Identifiers and article titles to access metadata and Wikipedia citation data. 3,582 health evidence syntheses from at least one McMaster University affiliated author were analyzed. Results: Six percent (n=219) of health evidence syntheses from the authors' institution were cited 568 times in 524 unique Wikipedia articles across 28 different language editions. 45% of citations appeared in English Wikipedia, suggesting a broad global reach for the institutions' research outputs. When adjusted for open access publications, 8% of McMaster University's health evidence syntheses appear in Wikipedia. Conclusion: Altmetric Explorer is a valuable tool for exploring the reach of an institution's research outputs. Isolating Altmetric data to focus on Wikipedia citations has value for any institution wishing to gain more insight into the global, community-level reach of its contributions to the latest health and medical evidence.
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.
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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".