Bibliographic record
Abstract
This paper tells the story of the development of the Ontario Deprivation Index. A ‘deprivation index ’ is a list of items (or activities) considered necessary to have a standard of living above the poverty level, given prevailing social and economic conditions, but those who are poor are unlikely to be able to afford. The intent of the index is to distinguish the poor from the non-poor. With funding from the Metcalf Foundation, Daily Bread Food Bank and the Caledon Institute of Social Policy set out to construct such a list for Ontario. Using a community-based research approach, a three-stage process was undertaken to develop the measure, engaging those with lived experience while making an innovative contribution to poverty research and policy development. Statistics Canada refined this list and incorporated it into their Labour Force Survey, under the sponsorship of the Government of Ontario. The result of the process was the creation of the Ontario Deprivation Index, which constitutes one part of the multi-indicator “Child and Youth Opportunity Wheel ” in the Ontario Poverty Reduction Strategy. This is the first poverty measure to be developed through a unique partnership of a community organization, a policy think tank, government and Statistics Canada. It is also the first time a deprivation index has been developed in North America.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.498 | 0.280 |
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".