Selected Proceedings of the IDEAS Conference Transforming Pedagogies: Learn – Design – Innovate
Bibliographic record
Abstract
Innovators, Designers, Educators, Academics and Students (IDEAS) 2019, Transforming Pedagogies is the sixth conference hosted by the Werklund School of Education at the University of Calgary. The mandate of the conference is to improve education through research, evidence-informed decisions across teaching, learning, and leadership. The conference brings together innovators, designers, K-12 practitioners, school leaders, post-secondary educators, consultants, undergraduate and graduate students, ministry personnel, academics, and researchers. All proposals to the conference go through a blind review process. Those proposals that potential presenters indicate will be submitted to the proceedings undergo a second double-blind review. The accepted proposals for the proceedings are invited to submit papers for the Proceedings of the IDEAS Conference, following the conference. These papers undergo a double-blind peer-review process that involves a minimum of two people reviewing each proposal. The reviewers’ feedback provides recommendations to the authors for improving and revising their manuscripts. Authors are required to address reviewers’ comments for the final version.
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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.182 | 0.050 |
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".