Análise dos indicadores para aferição das iniciativas da Sociedade da Informação propostas pelo governo colombiano
Bibliographic record
Abstract
This article presents the results of a research aimed to establish whether the indicators proposed by the Colombian government to measure the progress within the Information Society, IS, in the country allows to determine digital inclusion processes. Indicators were classified as follows: aspects that enable digital inclusion and participation in the IS, guidelines for evaluation (supply / demand for services); and population. The main results were the identification of 273 indicators, of which 67.4% assesses enabling aspects and 32.6% assesses participation. 83.9% of the indicators evaluates the offer and 16.1%the demand. Furthermore, we found that 12.5% of the indicators focuses on measuring population groups, from which 47% measure vulnerable groups. The results show that it is necessary to propose indicators that helps to understand the participation of citizens in the information society.
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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 | 0.009 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".