Bibliographic record
Abstract
Welcome to volume 49, issue 3 of The Canadian Journal of Learning and Technology (CJLT). CJLT is a decades-old peer-reviewed journal that invites English or French submissions on the research and practice of education, technology, and learning. This bilingual journal is free-of-charge to anyone with access to the Internet, is multi-indexed, and presented in accessible formats. There are no article submission/publication fees or access charges. CJLT’s history dates back to where distance education was an innovation characterized by portable print-based material and non-digital technologies. This issue’s Notes section is presented by Dr. Olaf Zwacki-Richter. Here, he reviews the history of distance education with a view to current pressures on teaching and learning. The Origins of the Term Distance Education and the Roots of Digital Teaching and Learning is both articulate and accurate. It provides an inspiring view of new ways to define and use concepts of Open, Distance, and Digital Education (ODDE), based on historical education milestones. This prepares readers with a lens to the research articles which follow.
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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.139 | 0.100 |
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".