Complexities in Sustainable Provision of GIS for Urban Grassroots Organizations
Bibliographic record
Abstract
Over the past decade there has been a significant increase in the use of geographic information systems (GIS) technologies by a plethora of social groups in various fields. Public participation GIS (PPGIS) has emerged to advance more equitable access to and more inclusive use of GIS among resource-poor and traditionally marginalized community-based organizations. The issue of sustainable provision of GIS for these community groups remains critical; thus, it is worth continuing investigation, particularly with respect to unravelling the dynamic process of GIS provision. This article presents such an attempt through a critical examination of the Data Center program in Milwaukee, which has been suggested as a valuable model of GIS provision in local PPGIS practice. This study proposes that a synthesized approach of scaled network analysis helps to better explain the dynamic process of social struggle for power and control within which the GIS provision is situated. The article illustrates how multiple scaled networks have been constructed by the Data Center to facilitate its GIS provision and examines the implications of this network construction to the dynamic production of its GIS provision.
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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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.014 | 0.029 |
| Scholarly communication | 0.020 | 0.018 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| 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".