Caledon Response to Liberal Poverty Strategy
Bibliographic record
Abstract
Toronto. The Liberal strategy is to be praised for its recognition of poverty as a serious national problem that needs political leadership and an explicit focus to achieve clear results. While the speech puts forward some important ideas in a number of key policy areas, several of the proposals will not help reach the intended goal of a dramatic reduction in poverty. We suggest some alternative reforms. poverty reduction targets Far and away the most important commitment is to set official poverty reduction targets and monitor progress against poverty. This major advance in Canadian social policy would make government more accountable and would improve our understanding of the complex factors that cause poverty. A difficult but crucial task in setting and monitoring poverty reduction targets will be to devise better ways to measure poverty. Canada is alone among advanced nations in not having official poverty lines. Our ‘unofficial official ’ poverty lines, Statistics Canada’s low income cut-offs (LICOs), have served for decades as de facto poverty lines, and will have to continue to serve in the absence of a better measure. But they never were intended to function as poverty lines, and they have some
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.013 | 0.012 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".