Bibliographic record
Abstract
On the basis of international and national statistical reports the article examines how Canada’s role in the global banking system has changed since the early 1970s until now. Throughout almost the entire period under study the country’s share in world banking assets, despite some fluctuations, exceeded its share in the world GDP. For many decades, the Canadian banking community managed to maintain a strong international position and overcome various economic crises, including the Great Recession of 2008–2009, without significant losses. The stability could be explained by the long-standing institutional features of the Canadian banking system (for example, practice of regular license renewal), as well as a fairly flexible combination of market freedom and government regulations during the period under review. Canada’s position in the rankings has changed as follows: being the sixth largest power in the global banking in 1970, the country went down to 12th position by the mid-1990s, but then began a new ascent, and returned to sixth place in 2020. Canada’s current share remains somewhat lower than in 1970, which could be explained by a significant increase in the number of countries operating at the global banking arena. Toronto is the undisputed leader in banking among Canadian cities; back in the late 1970s it got away from its main competitor (Montreal) against the challenging political events of that period. Currently, Toronto ranks sixth in the world in terms of the total assets of local banks. The next most important centers (Montreal, Levis and to some extent Edmonton) also enjoy a fairly great and stable prestige within the global banking system. Despite the dominance of Toronto, the continued independent role of these financial hubs gives additional stability to Canada’s banking community.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".