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Record W6942606074 · doi:10.14288/1.0448205

HART (2025) - 2021 Census of Canada - Selected Characteristics of Households and Dwellings for Housing Need related to Federal HNA Template - Canada, all provinces and territories at the Census Division (CD) and Census Subdivision (CSD) level [custom tabulation]

2025· dataset· en· W6942606074 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Collections · 2025
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsCensusTable (database)American Community SurveyOrder (exchange)PopulationSubdivisionHousehold incomePopulation statistics

Abstract

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Note: Data on gender diverse households (formerly "2SLGBTQ+" households) has been added as of March 28th, 2025. For more information, please visit HART.ubc.ca. Housing Assessment Resource Tools (HART) This dataset contains 18 tables which draw upon data from the 2021 Canadian Census of Population. The tables are a custom order and contain data pertaining to core housing need and characteristics of households and dwellings. This custom order was placed in collaboration with Housing, Infrastructure and Communities Canada to fill data gaps in their Housing Needs Assessment Template. 17 of the tables each cover a different geography in Canada: one for Canada as a whole, one for all Canadian census divisions (CD), and 15 for all census subdivisions (CSD) across Canada. The 18th table contains the median income for all geographies. Statistics Canada used these median incomes as the "area median household income (AMHI)," from which they derived some of the data fields within the Shelter Costs/Household Income dimension. 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 data fields: Geography: - Country of Canada, all CDs & Country as a whole - All 10 Provinces (Newfoundland, Prince Edward Island (PEI), Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta, and British Columbia), all CSDs & each Province as a whole - All 3 Territories (Nunavut, Northwest Territories, Yukon), all CSDs & each Territory as a whole *- Data on gender diverse households is only available for geographies (provinces, territories, CDs, CSDs) with a population count greater than 50,000. Data Quality and Suppression: - The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released. - Area suppression is used to replace all income characteristic data with an 'x' for geographic areas with populations and/or number of households below a specific threshold. If a tabulation contains quantitative income data (e.g., total income, wages), qualitative data based on income concepts (e.g., low income before tax status) or derived data based on quantitative income variables (e.g., indexes) for individuals, families or households, then the following rule applies: income characteristic data are replaced with an 'x' for areas where the population is less than 250 or where the number of private households is less than 40. Source: Statistics Canada - When showing count data, Statistics Canada employs random rounding in order to reduce the possibility of identifying individuals within the tabulations. Random rounding transforms all raw counts to random rounded counts. Reducing the possibility of identifying individuals within the tabulations becomes pertinent for very small (sub)populations. All counts greater than 10 are rounded to a base of 5, meaning they will end in either 0 or 5. The random rounding algorithm controls the results and rounds the unit value of the count according to a predetermined frequency. Counts ending in 0 or 5 are not changed. Counts less than 10 are rounded to a base of 10, meaning they will be rounded to either 10 or Zero. Universe: Private Households in Non-farm Non-band Off-reserve Occupied Private Dwellings with Income Greater than zero. Households examined for Core Housing Need: Private, non-farm, non-reserve, owner- or renter-households with incomes greater than zero and shelter-cost-to-income ratios less than 100% are assessed for 'Core Housing Need.' Non-family Households with at least one household maintainer aged 15 to 29 attending school are considered not to be in Core Housing Need, regardless of their housing circumstances. Data Fields: Tenure Including Presence of Mortgage and Subsidized Housing; Household size (7) 1. Total - Private households by tenure including presence of mortgage payments and subsidized housing 2. Owner 3. With mortgage 4. Without mortgage 5. Renter 6. Subsidized housing 7. Not subsidized housing Housing indicators in Core Housing Universe (12) 1. Total - Private Households by core housing need status 2. Households examined for core housing need 3. Households in core housing need 4. Below one standard only 5. Below affordability standard only 6. Below adequacy standard only 7. Below suitability standard only 8. Below 2 or more standards 9. Below affordability and suitability 10. Below affordability and adequacy 11. Below suitability and adequacy 12. Below affordability, suitability, and adequacy Period of construction (10) 1. Total – Period of Construction 2. Before 2016 3. 1960 or before 4. 1961 to 1980 5. 1981 to 1990 6. 1991 to 2000 7. 2001 to 2005 8. 2006 to 2010 9. 2011 to 2015 10. 2016 to 2021 (Note 1) Note 1). Includes data up to May 11, 2021. Structural type of dwelling and Household income as proportion to AMHI (16) 1. Total - Structural type of dwelling 2. Single-detached house 3. Apartment in a building that has five or more storeys 4. Other attached dwelling 5. Apartment or flat in a duplex 6. Apartment in a building that has fewer than five storeys 7. Other single-attached house 8. Row house 9. Semi-detached house 10. Movable dwelling 11. Total – Private households by household income proportion to AMHI 12. Households with income 20% or under of area median household income (AMHI) 13. Households with income 21% to 50% of AMHI 14. Households with income 51% to 80% of AMHI 15. Households with income 81% to 120% of AMHI 16. Households with income 121% or more of AMHI Selected characteristics (12) 1. Total – Private households by presence of activity limitation (Q18e only) 2. HH has at least one person who had an activity limitations reported for Question 18 e) only 1 3. Total – Age of primary household maintainer 4. 18 to 29 years 5. Total – Private households by military service status of the HH members 6. HH includes a person who is currently serving member and/or veteran 11. Total – Private households by shelter cost proportion to AMHI_1 12. Households with shelter cost 0.5% and under of AMHI 13. Households with shelter cost 0.6% to 1.25% of AMHI 14. Households with shelter cost 1.26% to 2% of AMHI 15. Households with shelter cost 2.1% to 3% of AMHI 16. Households with shelter cost 3.1% or more of AMHI* Median income (2) 1. Number of households 2. Median income of household ($) The household median income in the custom tabulation were estimates from a 25% sample-based data that have undergone weighting. These weights were applied to the sample data to produce estimates from the census long-form sample. The incomes used were drawn from the previous tax year, and therefore represent 2020 dollars. [Only in "Census 2021 - Gender Diverse HHs" file] Genderdiversity (2) 1. Total - Gender diversity status of households 2. HH is gender diverse File list (19 total): Original data files (18): 1. Census 2021 - Table 1 - Median Incomes.ivt 2. Census 2021 - Table 2 - Canada.ivt 3. Census 2021 - Table 3 - Census Divisions.ivt 4. Census 2021 - Table 4 - Ontario CSDs.ivt 5. Census 2021 - Table 5 - BC CSDs.ivt 6. Census 2021 - Table 6 - Alberta CSDs.ivt 7. Census 2021 - Table 7 - Manitoba CSDs.ivt 8. Censu

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.062
Threshold uncertainty score0.316

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.016
Science and technology studies0.0030.000
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0620.020

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.

Opus teacher head0.018
GPT teacher head0.230
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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