2016 Census of Canada - Selected Characteristics for Housing - Vancouver, Toronto, Montreal CMAs at the Census Tract (CT) Level [custom tabulation] 001
Bibliographic record
Abstract
This dataset includes three tables which were custom ordered from Statistics Canada. There is a table each for Vancouver CMA, Montreal CMA, and Toronto CMA, and the tables contain variables regarding dwelling characteristics, tenure, and shelter cost. The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom order from Statistics Canada includes the following dimensions and variables: Geography: Montreal CMA, Vancouver CMA, Toronto CMA to the census tract level Total Shelter Cost: Under $500 to over $3000 in $500 intervals Shelter Cost to-Income Ratio: Spending less than 15%, 15-30%, 30-50%, 50% or more Tenure: Owner (including presence of mortgage), renter, subsidized housing, not subsidized housing Condominium Status: Condominium, not a condominium Household Size: 1 person, 2 persons, 3 or more people Number of Bedrooms: No bedroom or 1 bedroom, 2 or more bedrooms Structural Type: -Single detached house -Apartment with 5 or more stories -Semi-detached house, row house or other single detached house -Apartment or flat in a duplex -Apartment, building with fewer than 5 stories Household Income: Median income and average income only Original file names: EO3091_Table1_Montreal.ivt EO3091_Table1_Toronto.ivt EO3091_Table1_Vancouver.ivt
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.020 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.056 | 0.022 |
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".