PPGIS in Community Development Planning: Framing the Organizational Context
Bibliographic record
Abstract
This article examines the local variability of public participation GIS (PPGIS) by urban community revitalization organizations, arguing that this variability is in part shaped by a variety of organizational factors. Existing research has shown PPGIS production to be highly context dependent, identifying an ever-growing set of key elements of this context, including a variety of locally available resources for GIS access and use as well as organizational capacities and characteristics. Contributing to current efforts to expand the conceptual basis of PPGIS research, this article argues that the conceptualization of organizational context must be expanded beyond internal capacities to include organizational networks with local actors, institutions, and resources; organizational knowledge and stability; and organization mission and priorities, all of which shape its activities and relationships, as well as the utility of available GIS resources. This broadened conception of organizational context enables a stronger explanation of the influencing role of organizations in PPGIS, as well as of local variability in PPGIS. These arguments are developed from comparative case study research with six Milwaukee, WI, community revitalization organizations engaged in PPGIS within a city-wide participatory planning initiative.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.010 | 0.040 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| 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".