Academic opinions of Wikipedia and Open Access publishing
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 examine academics’ awareness of and attitudes towards Wikipedia and Open Access journals for academic publishing to better understand the perceived benefits and challenges of these models. Design/methodology/approach – Bases for analysis include comparison of the models, enumeration of their advantages and disadvantages, and investigation of Wikipedia's web structure in terms of potential for academic publishing. A web survey was administered via department-based invitations and listservs. Findings – The survey results show that: Wikipedia has perceived advantages and challenges in comparison to the Open Access model; the academic researchers’ increased familiarity is associated with increased comfort with these models; and the academic researchers’ attitudes towards these models are associated with their familiarity, academic environment, and professional status. Research limitations/implications – The major limitation of the study is sample size. The result of a power analysis with GPower shows that authors could only detect big effects in this study at statistical power 0.95. The authors call for larger sample studies that look further into this topic. Originality/value – This study contributes to the increasing interest in adjusting methods of creating and disseminating academic knowledge by providing empirical evidence of the academics’ experiences and attitudes towards the Open Access and Wikipedia publishing models. This paper provides a resource for researchers interested in scholarly communication and academic publishing, for research librarians, and for the academic community in general.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.013 |
| Open science | 0.001 | 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