Strengthening sustainability assessment in town planning in rural Saskatchewan
Bibliographic record
Abstract
The application of Sustainability Assessment (SA) within Canadian municipalities is a recent notion, but is quickly becoming widespread. The Government of Saskatchewan alone has already released two SA checklists. However, such tools are normally aimed at communities of all sizes, ranging from rural municipalities to big cities, without considering differences in the capacity base, needs, and conditions among those types of communities. Additionally, practical implementation of SA often does not reflect the scope of scientifically established criteria for SA tools. This paper will present the analysis of the 2009 Saskatchewan Sustainability Checklist for Municipalities (comparing it to one of the most prominent frameworks for SA and other similar checklists developed in Canada and internationally) in order to identify possible areas for improvement so that the Checklist reflects established SA principles and is sensitive to a small town context. Based on the results of interviews with 16 small town administrators in Saskatchewan, this thesis demonstrates that, from a theoretical perspective, both of the existing SA tools are deficient in a number of important ways. The tools mainly focus on evaluating the municipal and service provision, rather than evaluating the sustainability of a community as a whole, including such areas as environmental conditions; social equity; livelihood sufficiency; resource maintenance; and intragenerational and intergenerational equity. However, the research reveals even if all of the above-mentioned criteria are integrated within the existing tools, it will be challenging for municipalities to perform a full sustainability assessment, since small towns’ administrations often have limited financial and human capacity to perform such exercises. Additionally, there is a lack of understanding on how to integrate the results of an assessment into decision-making, and a perceived inability to change some of the existing economic or social conditions in a town, due to the limited scope of influence that local municipalities have. There is a need for an alternative approach to sustainability assessment in the case of small towns; one that is sensitive to their unique pressures, circumstances, and capacities to enact change.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".