"We are all Developing Countries": Canada and International Copyright History: Fault Lines in the Map of International Copyright
Bibliographic record
Abstract
In this paper I will make three arguments, drawing on the historical experience of Canada with the Berne Convention between 1886, when the Berne Convention was founded, and 1971, its last revision. First, Canada, though aligned with the most powerful countries on issues of international copyright, has a unique and important history with international copyright that is very different from the histories of the major powers. Second, for many middle powers, the Berne Convention was a symbol of progress in international law, and a hallmark of a civilized country. Canada has aligned with the major powers on issues of international copyright. Though this alignment has not always comfortable, it stems in part from a desire to be associated with ideas of progress and civilization, and to be aligned with one�s largest trading partners. Third, I ask, what contribution do middle powers make to the international copyright system today?
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".