Merits and Challenges of Comparing the EU and Canada
Bibliographic record
Abstract
In the last decades, EU studies have increasingly broadened in terms of their theoretical and methodological approaches. By now, comparative concepts and theories are an integral part of studying the EU, which aids the study of its polity, politics, and policies. Despite the indisputable peculiarity of the EU as a political system, many scholars have stressed the value of using comparative approaches to study it. This thematic issue aims to investigate a specific case—the political system of Canada—as to its merit for comparison with the EU. While both systems have been described as sui generis in the past, forming a class of political system by themselves, recently the similarities between both have been stressed. This thematic issue gathers articles that compare different aspects of these two systems—focusing on polity, politics, and policy—to reap the benefits of the comparative approach and gain new insights into the functioning of both systems. The contributions to the thematic issue show the benefits that both Canadian political science and EU studies can gain from engaging in comparative exercises.
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 | 0.023 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.020 |
| Science and technology studies | 0.013 | 0.012 |
| Scholarly communication | 0.018 | 0.008 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".