The First Amendment in Cross-Cultural Perspective: A Comparative Legal Analysis of the Freedom of Speech
Bibliographic record
Abstract
The First Amendment—and its guarantee of free speech for all Americans—has been at the center of scholarly and public debate since the birth of the Constitution, and the fervor in which intellectuals, politicians, and ordinary citizens approach the topic shows no sign of abating as the legal boundaries and definitions of free speech are continually evolving and facing new challenges. Such discussions have generally remained within the boundaries of the U.S. Constitution and its American context, but consideration of free speech in other industrial democracies can offer valuable insights into the relationship between free speech and democracy on a larger and more global scale, thereby shedding new light on some unexamined (and untested) assumptions that underlie U.S. free speech doctrine.\nRonald J. Krotoszynski, Jr., compares the First Amendment with free speech law in Japan, Canada, Germany, and the United Kingdom—countries that are all considered modern democracies but have radically different understandings of what constitutes free speech. Challenging the popular—and largely American—assertion that free speech is inherently necessary for democracy to thrive, Krotoszynski contends that it is very difficult to speak of free speech in universalist terms when the concept is examined from a framework of comparative law that takes cultural difference into full account.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.009 | 0.037 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| 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".