2016 Census of Canada - Selected Characteristics for Housing - Vancouver, Toronto, Montreal CMAs at the Census Tract (CT) Level [custom tabulation] 001
Bibliographic record
Abstract
<p>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. </p> <p>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). <br /> For information on how to use Beyond 20/20, please see:<br /> http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf <br /> https://wiki.ubc.ca/Library:Beyond_20/20_Guide </p> <p><b>Custom order from Statistics Canada includes the following dimensions and variables:</b></p> <p>Geography: Montreal CMA, Vancouver CMA, Toronto CMA to the census tract level</p> <p>Total Shelter Cost: Under $500 to over $3000 in $500 intervals</p> <p>Shelter Cost to-Income Ratio: Spending less than 15%, 15-30%, 30-50%, 50% or more</p> <p>Tenure: Owner (including presence of mortgage), renter, subsidized housing, not subsidized housing</p> <p>Condominium Status: Condominium, not a condominium</p> <p>Household Size: 1 person, 2 persons, 3 or more people </p> <p>Number of Bedrooms: No bedroom or 1 bedroom, 2 or more bedrooms</p> <p>Structural Type: <br /> -Single detached house<br /> -Apartment with 5 or more stories<br /> -Semi-detached house, row house or other single detached house<br /> -Apartment or flat in a duplex<br /> -Apartment, building with fewer than 5 stories</p> <p>Household Income: Median income and average income only</p> <p>Original file names:<br /> EO3091_Table1_Montreal.ivt<br /> EO3091_Table1_Toronto.ivt<br /> EO3091_Table1_Vancouver.ivt</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 teacher head, 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".