Prospective home owners' attitudes to housing
Bibliographic record
Abstract
A better understanding of people’s attitudes to housing is fundamental to attracting new residents and retaining those who already live in or close to the central city. As such, this study operating in a Canadian context adopts Hägerstrand’s model for the process of innovation diffusion. The study draws on the findings of an online survey and interviews with city planners in both Edmonton and Winnipeg to explore the demand and supply dimensions of city-center living and attitudes towards different types of housing and neighbourhood design. The study shows that the central area in Winnipeg and Edmonton are at different stages regarding housing. Prospective home owners who are interested in housing in the central area share a number of environmental attitudes. These attitudes were related to the care for recycling, the importance for eating organic food, the use of public transportation, volunteering in non-profit organization to help the community and the interest in attending cultural activities. Based on the results of the study, it can be expected that housing types such as apartments, townhouses and even loft housing can be more common in the future and especially in Winnipeg since apartments and townhouses are already common in Edmonton.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".