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Record W4385207602 · doi:10.60082/2817-5069.3817

A Commercial Law of Privacy and Security for the Internet of Things by Stacy-Ann Elvy

2022· article· en· W4385207602 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOsgoode Hall law journal · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDigital Transformation in Law
Canadian institutionsnot available
Fundersnot available
KeywordsDigitizationScrutinyInternet of ThingsInternet privacyThe InternetBusinessLegal aspects of computingPerspective (graphical)Computer securityLawTelecommunicationsPolitical scienceComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

FROM SMART CARS TO SMART REFRIGERATORS, the internet of things (IoT) has revolutionized various facets of our lives. These novel developments galvanized what scholars now deem to be the Fourth Industrial Revolution. This new era is characterized by technology-driven innovation that marries aspects of the physical, digital, and biological domains, going so far as to defy preconceived notions of human capabilities and behaviour. The societal proclivity towards digitization and automated processes has spurred the proliferation of companies entering the technology arena. Corporations are leveraging emerging technologies to cater to consumers’ idiosyncratic needs more effectively. Central to this objective is the collection of consumer data, which invites scrutiny from a privacy and security law perspective.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.948
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.225
Teacher spread0.200 · 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