Peacekeeping Nation, Sociocultural Economics, and Institutional Development in Canada
Bibliographic record
Abstract
The paper examines how the “peacekeeping nation” identity of Canadians influenced institutional development in Canada. The author concludes that the culture of liberalism and peacemaking created an inclusive institutional environment and ensured political stability in Canada. Canadian peacemaking evolved in the context of institution building. Political stability in Canada was interconnected with the development of liberal values and a shared identity that united Canadian society in the age of dramatic social, cultural, and political shifts. Bradley–Terry model is used to analyze the Canadian peacemaking. The author systematizes the development of Canada’s peace support activities. It is found that the evolution of Canada’s engagement in peacekeeping operations fits into the business life cycle of “Childhood – Youth – Maturity – Old Age”. The stages of development of Canadian peacemaking are chronologically compared with the levels of stability in the context of secessionist and destabilizing trends in Quebec. The results of the comparison suggest that Canadian peacekeeping was driven by the desire of Canada’s political establishment to ensure country’s stability and national welfare. In other words, an economic interest influenced Canada’s engagement in peacekeeping activities. Applying one-way ANOVA helped to find that Canada’s gross national product could grow because of the stabilizing effects of the Canadian peacekeeping culture. Thus, the economic effect produced by sociocultural variables in general and the Canadian culture of peacemaking in particular is proven.
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 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 | 0.003 | 0.005 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".