The Brazilian Civil Rights Framework for the Internet (or the Virtual Times of a Postmodern Law)
Bibliographic record
Abstract
the paper presents a critical perspective about the article "Le temps virtuel des lois postmodernes ou comment le droit se traite dans la société de l'information" ("The Virtual Time of Postmodern Laws, or How the Law is Processed in the Information Society"), published by the philosopher and jurist François Ost, with the purpose of conducting a case study through the Brazilian law "Marco Civil da Internet" ("Civil Rights Framework for the Internet").The article analyzes the profound changes in the way the law came to be produced and interpreted, in the passage from the forms of writing and printing based on paper to the forms of text processing and communication based on computers and networks.The law known as "Marco Civil da Internet" (Law 12,965 / 2014) was used here as a validity test of the main elements of the text under examination, by means of illustrations and references published by the international media, especially after the diplomatic incidents arising from the revelations of the electronic monitoring of international telecommunications, conducted by the National Agency of Security (NSA) of the United States of America.The study concludes that Ost's article, published even before the Internet massification, can be considered as a premonitory insight about the changes in the operation and reproduction of law in the postmodern society, in which the hierarchical and pyramidal understanding of law moves to a distributed and networked understanding and
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.019 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".