Internet Intermediaries Liability. A North American Perspective or Perspectives from the United States and Canada
Bibliographic record
Abstract
The Marco civil da Internet establishes a brand new framework for liability of Internet intermediaries regarding third parties’ contents and activities. Besides providing general immunity schemes for Internet access providers and Internet application providers, Section III frames two derogatory regimes regarding revenge porn and copyright. The latter still needs to be designed. This chapter compares this new piece of legislation within both Canadian and United States frameworks. The analysis suggests Brazil is not the first to set different frameworks for varying matters. Based on fact that it is the only one to be consistent with principles set by the Marco civil da Internet, this paper will argue that Brazil should frame the upcoming copyright scheme with regards to Canada’s notice-and-notice framework.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.015 | 0.015 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".