PPGIS in neighbourhood planning: a strategy for inner-city community gardens, Winnipeg, Manitoba
Bibliographic record
Abstract
As spatial information has become more accessible and cheaper, interest in using Geographic Information System (GIS) has increased in a variety of fields including geology, social science, land management, and urban design. GIS has been considered a tool to provide geographically more accurate information and maps, but there are still underexplored questions about whether GIS is a tool that encourages or hinders active public participation in community planning practices; or whether it only intensifies fact-based research methods rather than encouraging more comprehensive approaches. In order to address these questions, this practicum examines how GIS may be useful to encourage public participation, how information and knowledge collected from residents or a neighbourhood can be applied to developing a GIS model and how these data may be incorporated with community plan. To analyze and illustrate the processes, this practicum explores community gardens in the Daniel McIntyre and St. Matthews Communities in Winnipeg, Manitoba and aims to develop a GIS model to assist with the process of identifying the strategical locations for future garden sites.
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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 | 0.002 | 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 | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".