Bibliographic record
Abstract
O presente artigo propõe a tese de que a proteção de dados é, por natureza, uma área extraordinariamente complexa e exige, por isso, uma regulamentação complexa e de múltiplos níveis. A moderna proteção de dados requer novas abordagens jurídicas, e o artigo oferece uma análise teórica e jurídica levando em conta o direito alemão e europeu. A hipótese é de que os padrões de pensamento elementares precisam ser construídos de maneira diferente para se alcançar uma legislaçãoadequada de proteção de dados, tendo em vista: (i) a complexidade do assunto – sob o ponto de vista dos dados, informações, conhecimento e fluxo de dados e informações, decisões e respectivas consequências; (ii) a complexidade dos interesses protegidos dos indivíduos afetados; e (iii) a complexidade dos conceitos apropriados para a regulamentação.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.007 | 0.033 |
| Scholarly communication | 0.019 | 0.013 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".