Newcomers in the Canadian housing market: a longitudinal study, 2001–2005
Bibliographic record
Abstract
The Longitudinal Survey of Immigrants to Canada (LSIC) is used to investigate the participation of immigrants in Canada's housing market during the first four years of the settlement process, beginning in 2000–2001. The analysis focuses on the changing rate of homeownership, crowding and affordability. Special attention is given to differences between landing classes and population groups (especially visible minority groups). In general, the housing situation of LSIC survey respondents improved remarkably over the years covered by the survey. This is registered in a much higher rate of homeownership in the third wave of the survey (at four years after landing) compared with the first (six months after landing). Similarly, the ratio of survey respondents spending more than 30 percent of their total family income on housing dropped dramatically, as did the percentage living in crowded conditions. In other words, at least according to the measures explored here, LSIC suggests that the proportion of immigrants in precarious housing situations drops significantly in the early settlement period. This positive outcome is not universally shared, however, and certain groups—notably refugees, and immigrants of black and MiddleEastern background—see much less improvement in their circumstances than the average survey respondent .
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".