Research-based implications for policy and practice: outcomes from EDUsummIT 2019 (Quebec) – The 6th International Summit on Information Technology in Education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
EDUsummIT (International Summit on ICT in Education) is a global knowledge building community of researchers, educational practitioners, and policy makers committed to supporting the effective integration of research and practice in the field of ICT in education. In 2019, more than 100 researchers, practitioners and policy makers from across the world have gathered to discuss ways to fast track what researchers know about information technology in education, into sound policies and best practices at the local, regional, and national/international level. This symposium focuses on outcomes from the Thematic Working Groups (TWGs) from EDUsummIT 2019, then seeks audience feedback and input on the findings and ways to best bring the Call to Action recommendations into implemented reality. Five Thematic Working Group topics relevant to an EdMedia audience will be featured in this symposium, followed by an integrative Call to Action summary. Presenters will invite feedback, suggestions and recommendation from attendees during all phases of the symposium. Especially encouraged will be discussion of how individual attendees might take appropriate portions of the recommendations away from the symposium and begin implementations at their local levels.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it