Post-event report - EU-Canada Digital Partnership Week on ICT Standardisation
Bibliographic record
Abstract
The European Union (EU) and Canada have long-established agreements, as reiterated in the recent EU-Canada summit (23/06/2025), that underpin a strong and forward-looking cooperation for the digital era. These include the Comprehensive Economic and Trade Agreement (CETA), which facilitates trade and investment, and the EU-Canada Digital Partnership, launched to enhance collaboration on digital policy and technology governance. Such agreements reflect the EU and Canada’s shared commitment for a secure, inclusive, and human-centric digital transformation, that will enable them to maintain their sovereignty and competitiveness among technological and geopolitical shifts. In line with the EU International Digital strategy, the European Union will continue to promote its values-based approach on digital governance and digital standards to shape a global digital transformation that is human-centric, trustworthy, and respects human rights and fundamental freedoms.
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.016 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.041 | 0.013 |
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".