Mission Accomplished? A Comparative Exploration of Conservatism in the United States and Canada
Bibliographic record
Abstract
When analyzing institutions and events in the “New World,” observers from the “Old World” have rarely been motivated just by curiosity. In the aftermath of the French Revolution, both liberals and conservatives tried to paint a picture of the United States that was supportive of their own position in the domestic debates (von Beyme 1986: 25ff). Alexis de Tocqueville explicitly stated in the foreword of his seminal work on “Democracy in America” that his interest in the United States arose from his desire to seek “the image of democracy itself, with its inclinations, its character, its prejudices, and its passions, in order to learn what we have to fear or to hope from its progress” (de Tocqueville 1956: 36). Thus, the political instrumentalization of America, so pervasive in the current public discourse in Europe, is not a new phenomenon. Ever since the birth of the American nation, Europeans have tended to project their highest hopes or worst fears onto the “New World.”
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".