Research communities and open collaboration: the example of the Digital Classicist wiki
Bibliographic record
Abstract
The so-called Web 2.0 technologies bring with them new opportunities and new challenges in the field of scholarship. With social software we have a new set of tools with innovative possibilities and it is up to the community of practitioners in the area of the intersection between scholarship and technology to make effective use of them. This paper is part of the author's continuing research into the use of social software (blogs and wikis amongst others) as tools for education (meaning teaching and learning) and research. The primary interest is in how these new tools might facilitate cooperative learning and cooperative research, and help to build communities both of learning and of practice. Put simply, how can they be used to encourage and facilitate people working together, to be a medium for open collaboration; why is this necessary; and what perceived problems need to be addressed to make this happen?
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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.022 | 0.028 |
| Scholarly communication | 0.018 | 0.023 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".