National Question in the U.S. and Canada’s Domestic Politics: Conclusions from the Comparative Analysis
Bibliographic record
Abstract
The conclusions of the research «National Question in the U.S. and Canada’s Domestic Politics: Comparative Analysis» are proposed for consideration here. For the first time in Ukrainian political science, a cross-national comparison of the USA and Canada in the context of the analysis of the national question was carried out. Namely, its essence was clarified, the peculiarities of multicultural practices in the USA and Canada (cultural pluralism and multiculturalism) were analyzed, and an analysis of ethno-racial discrimination and ethnic mobilization was conducted. The research methodologically conceptualized and developed a comparative political study of interethnic interactions with the use of a research strategy for comparing most similar systems (for example, the USA and Canada). The case study method has been substantiated and applied, involving the method of structural and focused comparison as a tool of cross-national research (for example, the USA and Canada), and also proved that the method can be effective in comparative political science. In the research, the indexation of immigration policy was conceptualized, and a scientific apparatus (a logical sequence of conceptualization, measurement and aggregation) for further cross-national studies in which the object is the national question in general and the migration policy in particular was developed. The theoretical results of the research can be used for the further design of models of binary implicit comparison of similar states. The case study method has not yet been properly applied in Ukrainian political science; therefore, the method proposed by the author for a structured and focused comparison of cases can be useful for both scholars and practitioners when comparing phenomena and processes. The author proposed the concept and design of a study of the already forgotten issues of the national question, which has been proven not to be outdated even in such advanced polyethnic states as the USA and Canada. The scientific results obtained by the author can be used by subjects of internal policy, first of all in the practice of public authorities. The proposed method of indexing immigration policy can serve scholars, legislators, government officials, and employees of the executive authorities to carry out cross-national and/or cross-temporal comparisons.
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 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 | 0.000 |
| 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".