Bibliographic record
Abstract
Today, both the United States and Canada are experiencing a decline in Single-Employer Sponsored Defined Benefit (DB) Pension plans. In some instances, they are being replaced by Defined Contribution (DC) or Individual Account [e.g., 401(k)] plans; in other cases, by nothing. It appears that traditional sponsors of DB plans have concluded that their cost (or its variability) is larger than the rewards (e.g., a loyal work force). At the same time, two stock market meltdowns in less than a decade have indicated to all the frailties of Individual Account DC systems. What we need is a new pension system that brings most of the advantages of the DB and DC plans to the participants, while minimizing their disadvantages. We must also recognize the skill set of the participants (e.g., do not expect a blue collar worker to be an investment professional) and not anticipate or require anomalous markets (e.g., ever-stronger equity returns). Size matters. Larger plans can run at lower per unit expense ratios, and can also achieve entry into a wide variety of investment products (e.g., private placements) not available to a small plan. Larger funds also benefit from risk sharing through “Law of Large Numbers”. The model proposed is a “Jointly Governed Target Benefit Pension plan”. Such plans would have many features in common with today’s Ontario Multi-Employer Pension Plans (MEPPs), the Canada/Quebec Pension Plans (C/QPP), TIAA-CREF in the United States and the Dutch national plan. For the plan sponsor, this is a DC plan. Inherent in the concept are that smaller plans (and even individual plans) could commingle their assets to achieve “size” (e.g. a minimum investment portfolio of $10B). Investment management would be at arm’s length from the plan itself.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".