Bibliographic record
Abstract
The report examines income and low income in census metropolitan areas between 1980 and 2000. It examines the situation of families and the neighbourhoods they live in. It also examines the situation of recent immigrants, Aboriginal people and lone-parent family members. Median pre-tax income rose in virtually all Canadian census metropolitan areas (CMAs) over the 1980 to 2000 period. Incomes increased at both the top and bottom of the income distribution, but tended to rise faster at the top. In nearly all cities, income increased faster in the higher income neighbourhoods - measured at the census tract (CT) level - than it did in lower income neighbourhoods. The incidence of low income was at similar levels in 1980 and 2000, but the demographic composition of low income changed, reflecting rising low-income rates among some 'at-risk' groups, as well as demographic changes in the CMA. By 2000, recent immigrants comprised more of the low-income population, and a greater share of the residents in low-income neighbourhoods than they did in 1980. Recent immigrants had much higher low-income rates in 2000 than in 1980. In 2000, Aboriginal people and people in single-parent families had much higher low-income rates than others and were over-represented in low-income neighbourhoods. The share of income that low-income families received from government transfers rose over the period. The location of low-income neighbourhoods changed in some CMAs, reflecting a decline in low-income neighbourhoods in the city centre and a rise in low-income neighbourhoods in more suburban areas. The report examines before-tax income in CMAs using the 1981, 1986, 1991, 1996 and 2001 censuses of Canada.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".