A Model to Guide the Open Government Data Implementation in Public Agencies
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
This paper presents a model to diagnose maturity and capabilities of Public Agencies (PAs) in pursuing the open data principles and practices. The open data maturity model, called OD-MM, was piloted in ten PAs from three Latin American countries, validating in this way the web tool that operationalizes the model. This web tool is a valuable diagnostic tool for PA's, since it shows all weaknesses and provides the instrument (a roadmap) to progress in the implementation of open data. We also propose a guide to implement open data in PAs. This guide is the result of the OD-MM application in Latin American PAs. The guide is simple and orients decision makers so that PAs following the actions of the guide can see their improved capacities when facing a diagnosis of their institutional maturity in the implementation of open data.
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.
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 | 0.014 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.009 | 0.018 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.006 |
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