The future of open data <b>The future of open data</b> , edited by Pamela Robinson and Teresa Scassa, Ottawa, University of Ottawa Press, 2022, xii, 246 pp., CAN$69.95(hard cover), CAN$39.95(soft cover), CAN$0(PDF), CAN$29.95(epub), ISBN 9780776629742(hard cover), ISBN 9780776629735(soft cover), ISBN 9780776629759(PDF), ISBN 9780776629766(epub), open access at https://ruor.uottawa.ca/bitstream/10393/43648/1/9780776629759_WEB.pdf
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
This book is the result of a five-year research project funded by the Social Sciences and Humanities Research Council of Canada.There are many parallels between Canada and Australia in terms of dat...
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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.014 | 0.153 |
| Open science | 0.042 | 0.042 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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