Protocol for a systematic literature review of research on the Wikipedia
Bibliographic record
Abstract
Context: Wikipedia has become one of the ten-most visited sites on the Web, and the world's leading source of Web reference information. Its rapid success has attracted over 1,000 scholarly studies that treat Wikipedia as a major topic or data source. Objectives: This article presents a protocol for conducting a systematic mapping (a broad-based literature review) of research on Wikipedia. It identifies what research has been conducted; what research questions have been asked, which have been answered; and what theories and methodologies have been employed to study Wikipedia. Methods: This protocol follows the rigorous methodology of evidence-based software engineering to conduct a systematic mapping study. Results and conclusions: This protocol reports a study in progress.
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 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 | 0.174 | 0.219 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.019 | 0.017 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.010 | 0.015 |
| Insufficient payload (model declined to judge) | 0.119 | 0.029 |
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".