Status Immigrant, Non-Status Migrant, & Canadian-Born Families
Bibliographic record
Abstract
The opinions expressed in this or any paper published by the Centre for Urban and Community Studies do not necessarily reflect the views of the Centre, or those of the University of Toronto. Centre for Urban and Community Studies • Cities Centre • University of Toronto • www.urbancentre.utoronto.caBetter Off in a Shelter? iii Executive Summary One significant segment of Canada’s unhoused population is families with children. Within this group are many immigrant and refugee families. Homelessness and shelter life impose great stress on mothers and their children. For immigrants who are also undergoing the stress of adapting to a new environment and a new culture, which may include learning English, the stress is compounded. A better understanding of the way in which discrimination contributes to homelessness among immigrant and refugee families with children can improve public policy and programs for immigrant families, thereby reducing family homelessness. The study focused on Toronto, where almost half of all immigrants settle after their arrival in Canada. Toronto is also one of the highest-cost housing markets in Canada and the city where newcomers face the greatest affordability problems, and therefore the greatest risk of homelessness.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.032 | 0.002 |
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".