(Des) cumprimento da transparência fiscal nos municípios populosos do Estado de Pernambuco
Bibliographic record
Abstract
Com o intuito de prevenir desvios e garantir a participação cidadã na gestão fiscal pública vários Estados modernos tem criado instrumentos associados ao uso de tecnologias da informação e comunicação. É neste contexto que se insere o princípio da transparência na gestão fiscal. Assim, o presente estudo tem por objetivo investigar se os municípios mais populosos do Estado de Pernambuco estão cumprindo com o que determina a legislação constitucional em relação à transparência fiscal. Para tanto, foi utilizado o método estatístico, do tipo documental e de abordagem qualitativa e quantitativa. A amostra do estudo empírico contemplou os municípios mais populosos do Estado de Pernambuco, Brasil durante os anos de 2014 a 2016. As evidências encontradas demonstraram que os municípios não estão cumprindo de forma integral os mandamentos legais de transparência fiscal da Administração Pública.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".