Bibliographic record
Abstract
The publication is devoted to the analysis of manifestations of modern anti- Americanism in Canada. Even though since the middle of the 20th century, Canada and the USA have become the largest partners in economic, trade, security relations, etc., in Canada, negative views of the USA, American politics, and society are widespread. In Canada, as in other countries of the world, anti-Americanism has a wave-like character: surges of positive opin- ion were replaced by surges of negative attitude towards the USA. Donald Trump's second coming to power has sparked a new wave of anti-Amer- icanism around the world, including in Canada. The article characterizes negative attitudes towards the United States and Donald Trump, particu- larly during the 2024 election campaign and in the first weeks of the new head of the White House in office. The greatest indignation among Cana- dians is caused by Donald Trump's statements that Canada should become the 51st state of the United States, as well as his policy on tariffs in the field of trade. The main reasons for the growth of anti-Americanism in Canada are the issues of preserving Canadian national identity and sovereignty and the danger of losing it, which has become a priority for Canadian domestic policy at the beginning of Donald Trump's second term. Nevertheless, in Canada, there are also supporters of D. Trump and the prospects of joining the USA, a significant part of which are primarily supporters of the Con- servative Party of Canada. A new wave of anti-Americanism in Canada is a natural phenomenon. On the one hand, the main factor that activated it was external, namely the loud statements and the first policy steps of the new head of the White House - Donald Trump, who raised tariffs and proclaimed the idea of turning Canada into the 51st state of the USA. On the other hand, an internal factor also plays a specific role in the growth of anti-American- ism, namely the beginning of the election race for the Canadian parliament.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.049 | 0.020 |
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".