Evaluating Community Engagement through Argumentation Maps—A Public Participation GIS Case Study
Bibliographic record
Abstract
Significant advances in public participation geographic information systems technology and online mapping platforms have not translated into enhanced citizen participation in democratic planning processes. This study contributes to addressing this gap by evaluating the engagement of members of an urban community in sustainable neighbourhood planning through argumentation mapping. The study provided an online public discussion forum, together with a neighbourhood map to which the participants could link their discussion contributions. On the basis of participation statistics, contents of contributions, and responses to a survey, we discuss the participants' technical and engagement experiences. The sixteen registered participants lived within or near the ‘Queen West Triangle’ in downtown Toronto, Canada. They rated themselves as experienced computer users and consequently found the participation in the online discussion forum to be easy. The contributions showed a great degree of interest and knowledge in the issues of sustainable community development. However, while the majority of participants also rated themselves as comfortable with map reading, they found the handling of the online neighbourhood map difficult and did not use the option to link their comments to the map.
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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 | 0.019 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".