Capital market developments in the post‐October 1987 period: a Canadian perspective
Bibliographic record
Abstract
Purpose The purpose of this paper is to review the evolution of the Canadian financial environment since the stock market “crash” of 1987. Design/methodology/approach The paper provides a chronological account of significant events in the Canadian economic environment and capital markets, and how they have transformed the financial climate. Findings The late 1980s was a turbulent period with many changes in government and economic policies which were initiated at a time when governments were wracked with fiscal deficits, and just as the central bank appointed a dedicated inflation fighter. These changes worked their way through the system to contribute to one of the worst recessions in Canadian history. One of the symbols of disparity during this era was the Stock Market “Crash” of 1987, which was felt in Canada, as well as around the globe. However, for the last decade, the federal government has reported a surplus every year, and Canadians have benefitted from falling tax rates, declining interest rates, a strong stock market, and a rising currency. In fact, until September of 2008, all of these developments had contributed to unprecedented profitability in the financial services industry, until the recent widespread economic crisis in the US spread to Canadian and global economies. However, the Canadian economy seems much better poised to deal with such adversity than it was in October 1987. If the fall of 2008 is any indication, we will find out soon enough. Originality/value The paper demonstrates how fallout from the crash of 1987, as well as other subsequent developments, has contributed to significant changes in the financial environment.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.014 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".