GIS for the public sectorc Experiences from the city of Belo Horizonte, Brazil
Bibliographic record
Abstract
Belo Horizonte was one of the first Brazilian municipal administrations to develop an urban Geographic Information System. Situated within the local government tradition of local government, the development and implementation of the Geographic Information System (GIS) commenced in 1989 and has proceeded significantly to the extent that it has become the most complete experience of its kind throughout Brazil, with applications covering areas such as education, health, sanitation, urban planning, transportation and traffic, among others. This article reflects on the experiences of this GIS project, from the technology acquisition and team formation phases, through the creation of the geographic database, to the development of applications and dissemination among users. Current perspectives for the continuing expansion of GIS technology usage in Belo Horizonte are also presented. This “successful” experience of GIS implementation is contrasted with some GIS projects in India to highlight probable areas of emphasis in future GIS projects in developing countries.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".