Exploring the impacts of the GPNO and the Far North Act on Official Plans and a Community-Based Land Use Plan
Bibliographic record
Abstract
Population shifts in Northern Ontario are eliciting provincial attention in the form of policy documents aimed at mitigating the consequences of population decline. There is a steady decrease in the population throughout Northern Ontario, a region often perceived as quite different to its southern counterpart due to social, geographical, geological, and economic differences. The population peaked in 1991 at 822,450 residents, but has steadily declined to 797,000 residents in 2016 and is predicted to see another 2.1% decrease to 782,000 by 2041 (Ministry of Finance, 2019). \n \nTwo primary documents were released to mitigate the consequences of these shifting populations and to promote growth across municipal and reserve jurisdictions: the Growth Plan for Northern Ontario (GPNO) and the Far North Act (FNA) for First Nation’s communities, respectively. However, little research has shown how these planning documents impact Official Plans and Community-Based Land Use Plans. This report explores how the planning legislation impacts local land-use planning in Official Plans and Community Based Land Use of Hearst, Kapuskasing, Timmins and Constance Lake which are geographically close, but with varying population sizes. \n \nIt is show that the Growth Plan for Northern Ontario, although paved with good intentions, does not provide realistic growth measures for the municipalities of Hearst, Kapuskasing, and Timmins. The municipalities involved limited their inclusion of the 13 growth initiatives meant to diversify their economy, and rather maintained their focus on their economic heritage of resource extraction. As for the Far North Act, the plan directly impacts Constance Lake’s Community-Based Land Use Plan for growth initiatives and land-use plans, but forces us to consider why First Nation communities do not have the same freedom with their land-use plans compared to municipalities. In the end, four recommendations are presented in the hopes of inspiring change at the local and provincial level.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".