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Record W2263532909

Text and Context: Making Sense of Canada's New Personal Information Protection Legislation

2000· article· en· W2263532909 on OpenAlexaffabout
Teresa Scassa

Bibliographic record

VenueSSRN Electronic Journal · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicFreedom of Expression and Defamation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsLegislationVariety (cybernetics)Context (archaeology)NormativePersonally identifiable informationGeneralityPrivacy policyInternet privacyInformation privacy lawPrivacy lawInformation privacyPrivacy by DesignBusinessData Protection Act 1998LawPolitical scienceComputer scienceEconomicsManagement
DOInot available

Abstract

fetched live from OpenAlex

The normative provisions relating to privacy in Canada's new Personal Information Protection and Electronic Documents Act are as general as one might expect, given their origin in a voluntary, multi-sectoral model Code. The generality which is the virtue of a model code, however, may well be a vice for mandatory and enforceable legislation. This paper provides a critique of the provisions of the legislation that deal with the key concept of consent. The author argues that the problems with the legislation will make it particularly difficult for businesses and consumers alike to determine what privacy protections are required across a range of different circumstances. The author then explores a variety of tools which may be of use in determining what measures are required in different circumstances in order to comply with the legislation. These include the office of the Privacy Commissioner, past practice, other legislation, sectoral codes, privacy seal programs, P3P and privacy statement generators.

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 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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.923
Threshold uncertainty score0.820

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 head0.009
GPT teacher head0.237
Teacher spread0.227 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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

Citations0
Published2000
Admission routes2
Has abstractyes

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