Exploring the use of PPGIS in self-organizing urban development: Case softGIS in Pacific Beach
Bibliographic record
Abstract
The paper seeks to identify prerequisites for introducing an established PPGIS tool in the field of self-organizing urban development. On the basis of a SoftGIS study in Pacific Beach, San Diego, we argue that despite PPGIS applications’ close connection to formal urban planning processes, PPGIS tools can support local interaction and facilitate self-organizing urban development. We could identify three facilitating roles for softGIS. It functioned, firstly, as a tool with respect to the interplay of various community organizations; secondly, as a catalyst of the process foregrounding the citizen perspective in Pacific Beach, and thirdly, as a provider of legitimacy for the responsible community organization aiming at concrete interventions in the physical environment. This was possible as the community organization and the research team had a shared interest and related expertise, and agreed about the resulting spatial analysis. In the light of this study we welcome further experiments using advanced PPGIS tools with community organizations, and call for a closer scholarly dialogue between PPGIS and Community Informatics.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".