Developing geographic information infrastructures for local government: the role of trust
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The United States's National Spatial Data Infrastructure (NSDI) model presumes that the local government agencies of counties and municipalities will share their geographic information freely with government agencies of regions, states and federal agencies. This article takes up the issue of local government involvement in the NSDI by asking the question: why should local governments involve themselves in the NSDI? This question is informed by considering the social and technological imbrication of the NSDI . One of the oldest spatial data infrastructure projects, the NSDI offers insights into the complexity of implementing infrastructure in federal models of shared governance. This article focuses on the political and financial dimensions of developing infrastructure among local governments. Trust is quintessential at this level of government. Local government agency activities experience an inherently closer coupling with political representatives and with different agencies in both intramunicipal and intermunicipal activities. Building the NSDI is fundamentally an interagency act and thus a matter of trust. Trust is a key issue in the development of the NSDI, as the results of a study of Kentucky local government agencies indicate .
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it