Bibliographic record
Abstract
Relevance of research. During the global financial collapse of 2008–2009, Canadian banks demonstrated stability and vastly avoided the international crisis. There was a view that Canada’s banking system was strict and overly risk-oriented, but after the crisis, it was recognized as logical in terms of lending, which required careful government supervision and regulation based on the principles of security and reliability. In fact, the World Economic Forum recognizes Canadian banks as the most stable in the world. So, all mentioned above prompted us to study the dynamics of the main indicators of the Canadian banking system. The aim of the study is to summarize and characterize the existing trends of banking system evolution in Canada. Methodological basis of the study is based on the analysis of the study of the Canadian banking system according to the indicators of the number of banking institutions, their profitability / loss, the quality of the loan portfolio and analysis of the largest banks in the country. A systemic analysis of the quantitative and qualitative composition of the above-mentioned banking indicators, synthesis and generalization were used to generalize and formulate conclusions. Scientific results. This article is devoted to the study of the dynamics of the main indicators of the Canadian banking system during the period from 2000 to 2019 inclusively. It is argued that the number of commercial banks has had a positive dynamics during the analyzed period, even the period of the global financial crisis of 2008-2009 has not reduced their number, which indicates the stability and prudent policy of commercial banks and the Central Bank as a whole. It has been established that 2019 is the year of the historical maximum assets of the Canadian banking system (more than 277% of Canada’s GDP). It is shown that the assets of eight largest banks in Canada account for 91% of the total assets of the banking sector. A record decline in the bank’s profits was recorded in 2009. The quality of the loan portfolio of commercial banks in Canada since 2009 shows a significant decrease in the share of outstanding loans. The practical significance of the study is to rate the strengths and weaknesses of the Canadian banking system. Significance / originality. The results achieved form an integrated view of the functioning of the Canadian banking system. The following studies will focus on methods and models for verifying the stability of banking systems, including the Canadian banking system.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".