Bibliographic record
Abstract
The Centre for the Study of Learning and Performance (CSLP) is a Montreal-based research centre of excellence that focuses on the generation of new knowledge about education through research and the mobilization of knowledge, working in partnership with educational practitioners by collaborating around the tools, techniques, and strategies for effective teaching and learning. Despite the strong provincial and federal interest in e-learning, there is neither uniform nor substantial evidence its effectiveness – especially without careful attention to the importance of pedagogical features in the design of educational software. There are no quick or effortless technological panaceas for learning, but educational technology can be a powerful tool when it is well designed, carefully validated, and properly implemented. Researchers at CSLP have developed an initial set of state-of-the art knowledge tools as part of the Learning Toolkit (LTK), which promote the development of essential educational competencies, including literacy, numeracy, inquiry, and self-regulation. They are available without charge to supplement and support classroom instruction.
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 | 0.015 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.016 | 0.040 |
| Open science | 0.004 | 0.028 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.015 | 0.009 |
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".