AVALIAÇÃO DE POLÍTICAS PÚBLICAS DE DESENVOLVIMENTO SUSTENTÁVEL: DILEMAS TEÓRICOS E PRAGMÁTICOS
Bibliographic record
Abstract
A discussão sobre o desenvolvimento sustentável tornou-se objeto de interesse público e acadêmico. Todavia existem dilemas na implementação de políticas públicas e avaliação de experiências sustentáveis no país. A proposta deste artigo é discutir alguns critérios de avaliação e sustentabilidade, tais como eficácia, eficiência, efetividade, prudência ecológica, eficiência econômica e justiça social. Para tanto, a revisão bibliográfica apoiouse em autores que tratam destes temas, entre eles destacamos: Arretche (1999), Cavalcanti (1995) e Sachs (1993). Para o êxito de uma política pública se faz necessário avaliar estes critérios para mensurar os custos/benefícios e os impactos desejados. Palavras-chave: avaliação, políticas públicas, desenvolvimento sustentável, efetividade.
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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 | 0.036 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.009 | 0.036 |
| Scholarly communication | 0.035 | 0.026 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".