MuNet, A New Way to Improve Municipalities
Bibliographic record
Abstract
In this paper, we present the project denominated Efficient and Transparent Municipalities – MuNet, developed by the Organization of American States – OAS, with the sponsorship of the Canadian for International Development Agency – CIDA. The aim of this project was to help Latin-American municipalities to use ICT tools to improve efficiency and transparency in its activities. The project was developed between 2005 and 2006 in 22 municipalities distributed in 11 countries, with the support of 5 experts of 5 different nationalities. The first phase followed a diagnostic of the general situation of the municipality, including technological aspects, and also transparency perceptions. Then a proposal of strategy to apply electronic government was developed with the collaboration of a Consultancy Team and the Task Force defined by the Major in each municipality. Furthermore, all the participants in the project received a virtual course about fundamentals in electronic government strategies. With the document approved by the society and the political ambit the Consultancy Team accompanied the Task Force in the implementation process, using in some cases the technological support of the project, specifically with software applications to develop the WEB page of the municipality – MuniPortal –, another software – MuniCompra – to improve the buying process and a last one to support the creation of a one stop window for the municipality services – MuniServi –. Additionally, this paper also presents evidence of the implementation process and the general data about the diagnostics developed.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".