Bibliographic record
Abstract
This paper discusses and describes measures of poverty and, on the basis of that discussion, proposes a public policy response that more closely and more easily targets income support to where it is most needed and most effective. Our review of poverty measures shows there are many holes that prevent advocates and policy-makers from obtaining a clear picture of who is in poverty and the depth of that poverty. The Market Basket Measure is the most finely tuned to identifying where impoverished families live and that is in large part why it was recently adopted by the federal government to gauge its anti-poverty policies. The government of Alberta, on the other hand, evaluates its policies using a measure of poverty that allows no consideration that costs of living might vary by community. Social assistance is the main policy instrument through which the federal and provincial governments provide assistance to people in need. We show that the growing emphasis of increasing social-assistance support via child benefits provides no increase in support in what has been for some time the majority of social-assistance cases. What’s more, despite a great deal of evidence that the cost of meeting basic needs varies widely by community, the amount of assistance provided is the same regardless of where one lives in the province. We propose a modification to how social assistance is provided that makes allowances for the fact poverty is deeper in some parts of the province than others and that provides support to individuals and families whether or not they have children. Our proposal is superior to rent control as a means of dealing with falling housing affordability, removes barriers to people receiving social assistance from moving to seek employment, and has features similar to a guaranteed basic income. It is also inexpensive. We estimate the cost of our proposal to be equivalent to less than one per cent of the provincial health-care budget.
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 | 0.019 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".