Bibliographic record
Abstract
With this issue, a 12-year effort has now come to a new plateau in its vision and reach. How little did the journal’s founders know where it would lead when the endeavor was first brought to realization at the annual meeting of the Ontario Educational Research Council in 1998. Here, after seeing a thriving action research community at the grass-roots level in the province, they decided that some outlet should be created for the dissemination of its results and recommendations. The title of this resource was christened the Ontario Action Researcher, named for two important reasons: First, their initial intention was to focus almost solely on the Ontario scene to the exclusion of all outsiders. As such, it was hoped that local talent would be nurtured in this diminutive hothouse, and connections could be made in a small geographical area. Second, they hoped that by avoiding a more “academic” title (such as journal, annals of, etc...) it could bridge the gap between the often disconnected populations of teacher and scholar. Based on this belief, equal members of the two groups held positions on the original editorial panel. And with this nascent philosophy, the journal tootled off from the gate to meet its supporters and critics.
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 | 0.224 | 0.353 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.020 | 0.013 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".