Bibliographic record
Abstract
This report presents a policy history of the Canada Pension Plan (CPP) disability benefit. The Canada Pension Plan is a national public insurance program that provides income pro-tection to workers in the event of a long-term interruption of earnings resulting from retirement, disability or death. The disability benefit delivers benefits to contributors who cannot work because of a severe and prolonged disability. The CPP also pays a flat-rate benefit to the eligible children of disability beneficiaries. The CPP disability benefit confers a number of important advantages not available through private insurance or most other income security programs. It provides disability coverage for all working Canadians including the self-employed (who are not eligible for workers ’ compensation or Employment Insurance). The CPP does not exclude workers on the basis of former medical history or require higher premiums for contributors deemed to be high risk. It takes some account of dis-ability-related costs by incorporating a flat-rate component into the benefit calculation. It guarantees coverage until recovery from the disability or until retirement or death. Unlike most private insurances, the CPP ensures full inflation protection. The CPP has seen steadily increasing caseloads since disability benefits were first paid in
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.068 | 0.011 |
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".