Cancellation of 2020 Conference: The Canadian Association of Action Research in Education
Bibliographic record
Abstract
After a very tumultuous spring, the executive of CAARE’s parent organization - the Canadian Society for the Study of Education (CSSE) - decided to cancel its upcoming conference in London, Ontario this June. CAARE has, of course, decided to follow suit. This was a lamentable decision but one that helped to insure public health. While presenters will not get a chance to discuss their research at the 2020 conference, we are happy to announce that we will still go through with the publication of the association’s conference proceedings, which will be found on the CJAR website in the coming months. In the long term, we hope to see all members of CAARE at the 2021 conference which will be held at the University of Alberta in Edmonton.
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 | 0.066 | 0.093 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.016 | 0.005 |
| Scholarly communication | 0.025 | 0.007 |
| Open science | 0.007 | 0.013 |
| Research integrity | 0.026 | 0.022 |
| Insufficient payload (model declined to judge) | 0.130 | 0.053 |
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".