A space to thrive: Addressing barriers to accessible housing for people with disabilities in British Columbia
Bibliographic record
Abstract
People with disabilities who make up nearly 25% of the population in British Columbia (BC) encounter barriers that hinder their full and equal participation in all aspects of society, including within the housing sector.Two housing crises are currently underway in BC -an affordability crisis and an accessibility crisis.Because of the combination of high costs and lack of suitable housing, people with disabilities are uniquely impacted by this problem.This study documents the barriers experienced by people with disabilities in relation to housing and their impact on people's quality of life.In order to analyze the policy problem, a literature review, evaluation of promising practices, and qualitative analysis of interview data was conducted, in which four policy options were determined and evaluated: (1) guiding principles for policy; (2) a province wide information campaign; (3) accessible modular housing; and (4) grants for housing providers.This study recommended all four of these options, in addition to the alignment of provincial, municipal, and non-governmental organizations mandates, and the improvement and development of standards that are focused on, and outline requirements for accessible housing.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".