SOCIOLOGIA POLÍTICA E GOVERNANÇA DIGITAL: perfil de recrutamento dos conselheiros indicados pelo governo ao Comitê Gestor da Internet (2004-2020)
Bibliographic record
Abstract
O Comitê Gestor da Internet (CGIbr) é o órgão responsável pela governança da Internet no Brasil, isto é, a regulamentação de seus elementos administrativos e estruturais. É formado por 21 membros e, destes, 8 são indicados pelo governo. Este trabalho tem por objetivo analisar, através do método prosopográfico, os perfis dos indicados entre os anos de 2004 e 2020. Foram analisadas as trajetórias de carreira profissional e educacional dos conselheiros. Além de analisar padrões de indicação, o trabalho também busca averiguar se há mudança nestes perfis entre os governos. Foi possível identificar que enquanto as primeiras formações, no governo Lula, apresentavam certa heterogeneidade de perfis, com presença de acadêmicos, a partir do governo Dilma se estabelece um padrão de homogeneização dos indicados, com destaque a burocratas da administração federal pós-graduados.
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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 | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".