The effects of land use, transportation infrastructure and housing affordability on growth management in the GVRD: a study of household travel behaviour and location decisions
Bibliographic record
Abstract
A great deal of planning literature in the last decade has been devoted to growth management and the concept of land use and transportation interactions. "New" approaches to planning, such as Transit Oriented Development (TOD) and Neo-Traditional Neighbourhood Design, are products of this evaluation of current development practices. The influence of housing affordability and accessibility, although intuitively related to the growth management problems of urban sprawl and automobile dependence, has often been overlooked. The purpose of this research is to bridge important gaps in our understanding of how residential land use and transportation infrastructure investments are shaping unsustainable growth and travel patterns in the GVRD, which is the main problem being addressed. The research objectives related to this problem are the correlation of observed trends in growth, housing and travel indicators, the determination of the importance of price and accessibility factors in household location decisions, and the analysis of the role that land use and transportation decisions have played in influencing housing costs and accessibility. To provide a context for understanding the scope of the problem and the relationships between the research results and proposed recommendations, the applicable literature, theory, and policies in the areas of growth management, land use, transportation and housing are given. Supporting research results include: a survey of senior stakeholders in the region on land use, transportation and housing issues; a synthesis of significant socioeconomic, growth, transportation and housing data; a summary of surveys outlining preferences for residential location and housing type; and an analysis of Place of Work data crosstabulated against Place of Residence and socioeconomic variables. The results show a strong dependency between location decisions and the cost and accessibility of housing, particularly for the critical group of younger households with children. Policy recommendations, based on the research and covering land use, transportation, housing, governance and education, are proposed to address the main sustainability problems studied. The recommendations focus on promoting affordable, higher density communities, with a choice of transportation modes, as an attractive alternative to lower density, automobile-dependent suburbs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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 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".