O reconhecimento facial nas smart cities e a garantia dos direitos à privacidade e à proteção de dados pessoais
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
As smart cities comportam um sistema hiperconectado de pessoas e coisas, alimentado por dados. As tecnologias de reconhecimento facial, presentes nas smart cities da China, contribuem para os modernos processos de surveillance. O objetivo geral do estudo é compreender, a partir do caso chinês, as consequências da adoção do modelo de reconhecimento facial das smart cities no Brasil. O método de abordagem utilizado é o indutivo. O reconhecimento facial implica em consequências à uma razoável expectativa de privacidade, ao anonimato e à autonomia individual. Por isso, os direitos fundamentais de privacidade e proteção de dados pessoais são limites que devem ser observados, objetivamente, para a utilização desse modelo de smart cities no Brasil.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 it