Balancing Governmental Jurisdiction: The History of the Division of Legislative Powers and Its Impact on Canadian Unemployment Insurance
Bibliographic record
Abstract
This project aims to demonstrate how the division of jurisdictional powers between the federal and provincial governments prevented the implementation of unemployment insurance in Canada. The first section delineates a historic analysis by briefly expanding on the initial conflict in which “unemployment” and “insurance” were established in their respective jurisdictions. The second section focuses on the Great Depression as the instance of greatest need for unemployment insurance that influenced a more aggressive approach by the Federal government. The third section addresses R. B. Bennett’s New Deal, in which he attempted to introduce the Employment and Social Insurance Act in 1935 as a means of establishing Federalist control over unemployment. The fourth section analyzes the legal arguments surrounding the New Deal that led to its ultimate failure. The last section focuses on how William Lyon Mackenzie King finally managed to implement a policy through the amendment of the British North American Act. Through this research, I discovered that, by assigning unemployment to the provinces and insurances to the Dominion, the division of powers in Canada prevented any impactful decision-making in aiding citizens suffering from unemployment. The fact that unemployment insurance was only implemented after constitutional amendment serves to demonstrate the importance of recognizing the division of powers. Once the division of powers was altered, all jurisdictional conflict pertaining to the matter ceased to exist between the two levels of government, suggesting that the governments had the physical means of addressing unemployment, but hesitated to do so, for political reasons.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| 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".