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Record W3124049247

Web 2.0 Regulation: A Risk Management Process

2010· article· en· W3124049247 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueeYLS (Yale Law School) · 2010
Typearticle
Languageen
FieldComputer Science
TopicDigital Rights Management and Security
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsWorld Wide WebComputer sciencePublicationWeb contentThe InternetPublishingWeb 2.0Web developmentInternet privacyAdvertisingBusinessPolitical science
DOInot available

Abstract

fetched live from OpenAlex

In order to describe the law relating to Web 2.0, we have to look at the normativity that really operates there. Effective norms engender strong enough risks for stakeholders that they find it in their interest to comply. State legislation is not the only thing that governs Internet activities; the normativity that governs the resources associated with Web 2.0 flows from what the technology permits and prohibits, and also largely from stakeholder practices. Configurations and practices create risk or shift risk onto others. However, state regulators may consider that the risks arising out of Internet activities are worrisome enough that the state should impose obligations on stakeholders and thus modulate what they can do online. Through their regulations, states create risks for stakeholders.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.826
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.008
GPT teacher head0.228
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it