MétaCan
Menu
Back to cohort
Record W3160775010

A Proposal for Police Acquisition of ISP Subscriber Information on Administrative Demand in Child Pornography Investigations

2019· article· en· W3160775010 on OpenAlexaffabout
Colton Fehr

Bibliographic record

VenueSSRN Electronic Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicStalking, Cyberstalking, and Harassment
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsSeriousnessThe InternetInternet privacyBusinessChild pornographySupreme courtOrder (exchange)Service (business)PornographyComputer securityLawPolitical scienceComputer scienceWorld Wide WebMarketing
DOInot available

Abstract

fetched live from OpenAlex

The Supreme Court of Canada concluded in R v Spencer that police acquisition of subscriber information from an internet service provider engages a reasonable expectation of privacy. Although this conclusion is principled, it has also resulted in significant obstacles for police investigating child pornography offences. Applying for a production order is not, however, the only option that would pass constitutional muster. By focusing on the way in which information is revealed when combining internet subscriber information with a user’s Internet Protocol address, it is possible to significantly mitigate the seriousness of any invasion of privacy. This in turn can be used to justify significantly lower requirements for police conducting investigations into at least some online crimes.

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 imitation

Not 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.

metaresearch head score (Codex)0.037
metaresearch head score (Gemma)0.065
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.064
Threshold uncertainty score0.198

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.065
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0010.004
Bibliometrics0.0050.003
Science and technology studies0.0120.020
Scholarly communication0.0140.011
Open science0.0070.010
Research integrity0.0640.021
Insufficient payload (model declined to judge)0.0100.005

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 head0.012
GPT teacher head0.295
Teacher spread0.283 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueSSRN Electronic JournalSame topicStalking, Cyberstalking, and HarassmentFrench-language works237,207