On the Competitiveness of the Canadian Stock Market
Bibliographic record
Abstract
Even if the competitiveness of the Canadian securities market is a central argument in the ongoing debate related to the proposal of a single securities commission, the exact level and the evolution of this market are largely undocumented. The numerous changes that modified the structure of the securities market during the last twenty years probably explain this lack of evidence. Two dimensions of the market's competitiveness deserve attention. The first one is the proposition that the Canadian market is unable to compete with other markets in attracting and keeping new listings and transactions. The second one is the proposition that a discount penalizes firms that finance in Canada relative to the U.S. We address the first proposition by carefully analyzing the evolution of the Canadian market from 1990 to 2007 in terms of market capitalization, number of listed companies and trading volume. We then compare the increase observed in Canada with similar data from other countries. We analyze the discount argument in light of recent studies that explain this phenomenon, and document this discount on other markets. The objective of this paper is to provide documented evidence that could ground the debate on the optimal regulatory structure for the Canadian market.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".