Wikipedia for academic publishing: advantages and challenges
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.
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore the potential of Wikipedia as a venue for academic publishing. Design/methodology/approach By looking at other sources and studying Wikipedia structures, the paper compares the processes of publishing a peer‐reviewed article in Wikipedia and the open access journal model, discusses the advantages and challenges of adopting Wikipedia in academic publishing, and provides suggestions on how to address the challenges. Findings Compared to an open access journal model, Wikipedia has several advantages for academic publishing: it is less expensive, quicker, more widely read, and offers a wider variety of articles. There are also several major challenges in adopting Wikipedia in the academic community: the web site structure is not well suited to academic publications; the site is not integrated with common academic search engines such as Google Scholar or with university libraries; and there are concerns among some members of the academic community about the site's credibility and impact in academia. Originality/value This paper promotes a fundamental idea for adjusting methods of creating and disseminating academic knowledge. It is a valuable resource for those interested in academic innovation, for research librarians, and for the academic community in general. This topic has not been sufficiently addressed in the literature.
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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.007 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it