Bibliographic record
Abstract
The core goal of any country’s pension system is to provide an adequate system available to the full breadth of the population that is sufficient to prevent poverty in old age. It must be affordable by the employers and employees and other participants and robust enough to withstand major shocks, including economic, demographic, and political volatility. Recent events have demonstrated that Canada’s retirement system is not meeting this goal in part because of inadequate pension coverage. Ongoing economic problems have focused public attention on the need for Canadians to prepare for their own retirement and there is a growing recognition of the need for a new broadly based retirement savings vehicle. That is where the consensus largely ends. CARP’s longstanding focus with regard to the larger issues of pension plan coverage and savings adequacy has been on the 3.5 million middle income earners working for smaller employers and the 4.9 million earning less than $30,000 per year.i This grouping of 8.4 million Canadians tends not to have occupational plans and is most at risk for retirement income inadequacy. It is for this group primarily that advances in pension reform are needed. There are competing visions of what level of coverage is necessary, whether it must be mandatory, how big it should be, who should manage it and whether it can or must adequately address the needs of low
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.723 | 0.409 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".