Bibliographic record
Abstract
There has been a strong shift away from defined benefit (DB) pension plans toward defined contribution (DC) pension plans in the United States over the last 20 years. A variety of reasons for this shift have been proposed. In another paper in this issue, Krzysztof Ostaszewski presents a new hypothesis to explain the shift to DC plans in the United States. He argues that the decline in importance of DB plans is due to a shift in the way relative returns to macroeconomic factors of production, that is, capital and labor, are being rewarded in the national economy. This paper attempts to test the Ostaszewski hypothesis using Canadian data. In Canada there has been only a slight decrease in DB plan coverage. It is shown that the Ostaszewski theory does not fit the Canadian experience well. Instead, it is argued that pension regulation and tax legislation play a crucial role in pension design and reform. It is also argued that the difference in pension regulation and taxation in Canada versus the United States has directly influenced plan sponsors in considering their pension objectives, costs, and risks. Differences in the proportion of the workforce that is unionized may also be important. The paper concludes that pension regulation and taxation are more important variables than are macroeconomic reward systems in the use of DB versus DC pension plans.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".