Land use planning in the Greater Golden Horseshoe for the rural-urban fringe: A case study assessment of regional approaches
Bibliographic record
Abstract
In 2006 the Province of Ontario implemented two land-use strategies aimed at curbing urban sprawl and protecting agricultural and environmentally sensitive lands in the Greater Golden Horseshoe. The strategies were the Growth Plan for the Greater Golden Horseshoe, 2006 and the Greenbelt Plan, 2005. The Growth Plan represents the government of Ontario's strategy to accommodate and facilitate population and economic growth within the GGH (i.e. where to grow). The Greenbelt Plan sets the framework for the permanent protection of agricultural lands and environmental resources through a natural heritage system (i.e. where not to grow). However, there is a substantial amount of land within the Greater Golden Horseshoe where specific policy directions have been omitted. These lands are located along the rural fringe of urban settlement areas and the inner boundary of the Greenbelt Plan Area. The research paper selects 4 case study areas, the Region of Peel, Region of Halton, City of Hamilton, and Waterloo Region and evaluates the community characteristic and land use approaches taken by the regions to plan for their rural-urban fringe lands. The study concludes that each regional area designates lands within the rural-urban fringe for rural and agricultural uses and has key policy directions to support the viability of the lands. However, policy directives within the Growth Plan for the Greater Golden Horseshoe requires regional authorities to plan for projected population and employment growth which facilitates the conversion of rural and agricultural lands within the rural-urban fringe to accommodate projected growth. The outcome is a policy framework, which allows for encroachment along the rural-urban fringe through special policy area designations that identify the location of future growth areas to accommodate growth projections. With the provincial growth directive in place, the case study regions take similar approaches with respect to planning for future growth. The community character analysis shows that manufacturing and transportation/warehousing are specialized industries (by place of residence) in the sampled GGH regions and the rural-urban fringe within each case study region has been identified to accommodate future employment land needs. In addition, more affluent communities with stronger rural presences such as Halton and Waterloo have implemented more protective land use policies aimed at protecting the rural and agricultural areas beyond the minimum requirements of the Growth Plan. The lack of policy direction with respect to the vision/role for rural-urban fringe lands in the GGH combined with a projection based growth framework in the Growth Plan creates a policy environment where urban uses will continue to encroach upon the rural-urban fringe lands. In the current policy framework, rural and agricultural land uses in the rural-urban fringe can be considered as interim uses, until such time, as urban growth is to be accommodated. Better policy direction is required to provide a vision and role for the rural-urban fringe lands within the GGH context to allow for the long term and sustainable use of the lands.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".