Housing in Atlantic Canada: The poverty factor i Director of the Centre for Housing Initiatives
Bibliographic record
Abstract
It seems a long time since the first conference on housing in Canada was hosted by the Canadian Welfare Council in 1968. There, D.V. Donnison said,.”.. poverty and its implications must be considered before housing policies can be explored. ” (1968, 16) Another statement by Donnison was starkly prophetic:... We assume too readily that democracy, plus education, plus rising productivity, the holy trinity of 19 th century liberals- must in time produce justice for all.... But what these will do is enable the strong, the smart and the fleet to become the majority while the weak, the slow and disabled (whether physically or socially) to be left behind, further and further behind. (34) The Atlantic Region has long been recognized as a “have-not ” area. Except for the Halifax urban area, the region has suffered the loss or down-grading of its current primary industries such as coal, steel and the fishery, and the lack of interest in other primary industries, such as agriculture and sustainable forestry. Even Halifax with its fanfare of success, has pockets of poverty that are on par with any large urban centre in Canada. Poverty or “low income ” in Atlantic Canada has been determined by the National
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.046 | 0.010 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.018 | 0.021 |
| Insufficient payload (model declined to judge) | 0.012 | 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".