Connecting Local to Global: Geographic Information Systems and Ecological Footprints as Tools for Sustainability
Bibliographic record
Abstract
Tools that support public engagement with sustainability are essential for local sustainability planning. This research investigates the ability of two geographic information system (GIS)-based tools to promote discussion of sustainability in a suburban context. A local ecological footprint tool and a community environmental atlas (an environmentally themed online mapping system) were created for seven suburban boroughs of Montreal. Variations of both tools have been used to support sustainability efforts, but their use has not been widely evaluated. Working from a public participation GIS (PPGIS) framework that recognizes the powerful influence of data representation, this research uses focus groups to evaluate how well these tools address three criteria that have emerged from the literature on public engagement in sustainability: interdependency across systems, reflexivity about personal and social decision making, and interactions across spatial scales. Whereas the atlas remains advantageous for discussing local spatial specifics, it was found that the ecological footprint helped people see the interconnections among systems, integrate local and global aspects of sustainability, and reflect on the values and assumptions underlying current social and economic structures.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".