The struggle for security: Risk, politics and pension policy in Ontario, 1960-2016
Bibliographic record
Abstract
This dissertation traces the rise and decline of Ontario’s workplace pension system that has resulted with growing emphasis on Canada’s public pension system, focusing on the postwar period to 2016. Since the mid-1980s, workplace pension coverage in Ontario and across Canada has been decreasing, calling into question the ability of this system to provide adequate retirement income for future workers. Currently, large private and public sector employers such as Air Canada, General Motors Canada and Canada Post are seeking to replace secure defined benefit plans with less secure defined contribution plans. Given these trends, policymakers at the provincial and federal levels have attempted to remedy the insecurity produced by diminishing coverage rates. Using Ontario as a case study to examine Canada’s retirement income system, this dissertation asks: Why has the risk of saving for retirement shifted, and what factors have driven this? Drawing from 22 semi-structure interviews with pension professionals, descriptive statistics, and Hansard Parliamentary transcriptions, several findings are established. First, although risk has been increasingly individualized since the 1990s, there is a limit to how much risk workers are willing to accept before political coalitions form to demand government play a larger role in establishing retirement income security. Risk transfer is thus contingent on union power, retiree activism, business lobbying, and the ideological position of governing parties. Second, the rise of individualized risk is generating new provincial/federal political dynamics in the field of pension policy, in which the failure of Canada’s workplace pension systems is impacting the welfare state politics of Canada, pointing to the emergence of a new period of pension politics. This finding leads to the conclusion that in the field of pension policy in Canada, the assertion by risk theorists that globalizing forces are transforming the welfare/citizenship nexus away from a model premised on risk sharing to one in which the state must facilitate the needs of rational, risk taking citizens does not adequately describe recent trends in Canadian pension policymaking.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.022 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".