Canadian UNESCO Chairs : reflections on the futures of education
Bibliographic record
Abstract
'UNESCO's Futures of Education is a global initiative to reimagine and rethink education by 2050. Through an open consultation process involving youth, educators, civil society, governments, businesses, and other stakeholders, it will gather ideas that will shape our future. A publication on how knowledge, education and learning will look like by 2050 will be presented during the next UNESCO General Conference in November 2021. A first issue called Humanistic Futures of Learning: Perspectives from UNESCO Chairs and UNITWIN Networks has been published in January 2020. This is the first collection bringing together the perspectives of a UNESCO flagship network that holds a privileged place in the research ecosystem. Indeed, the UNESCO Chairs are uniquely positioned contribute to the global debate on the futures of education. The call for contributions generated enormous interest; UNESCO received 178 submissions by more than 400 authors. Of these, a selection of 48 reflection papers by over 100 authors from 65 institutions were selected. The main findings were presented in January 2020 at the first meeting of the International Commission on the Futures of Education. We are particularly pleased that the contributions of six of our Canadian UNESCO Chairs have been selected to contribute to the global reflection'
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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 | 0.014 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".