Proceedings of the 2007 international symposium on Wikis
Bibliographic record
Abstract
The 2007 International Symposium on Wikis brings together wiki researchers, practitioners, and users. The goal of the symposium is to explore and extend our growing community. The symposium has a rigorously reviewed research paper track, as well as plenty of space for workshops, posters, panels, demonstrations, and open discussions. We intend WikiSym 2007 to be an exiciting venue for anyone who is involved in using, researching, or developing wikis. We recognize the online world is always evolving, and we also welcomed contributions which are about other online media consistent with the wiki philosophy of being open, organic and participatory. Given the interdisciplinary nature of wikis, we have especially invited contributions from researchers and practitioners from a wide range of fields including: business, marketing, law communications and media studies computer science, human-computer interaction history, political science, geography information and library science linguistics, discourse analysis, language studies natural sciences, medicine . We were very happy at the positive support, and we did get submissions covering all aspects that we suggested. For the research paper track, we received 39 submissions. Of these, we accepted 9 as full papers, and 11 as short papers. All submissions were reviewed by at least three members of our international program committee, and acceptance was decided by consensus. We feel that the wiki idea is continuing to gain pace as it reaches many people who see the benefits and fascination of this simple but far-reaching approach to sharing knowledge in a community.
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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.016 | 0.016 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.072 | 0.044 |
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".