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Record W2153057875 · doi:10.1093/idpl/ips016

Systematic government access to private-sector data in Canada

2012· article· en· W2153057875 on OpenAlexaboutno aff
Jane Bailey

Bibliographic record

VenueInternational Data Privacy Law · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Criminal Justice and Data Protection
Canadian institutionsnot available
Fundersnot available
KeywordsPersonally identifiable informationStatuteBusinessCharterLaw enforcementGovernment (linguistics)Private sectorEnforcementInformation sharingLegislationNational securityLawPolitical science

Abstract

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In Canada, information privacy is implicitly constitutionally protected by the Charter of Rights and Freedoms (the Charter), as well as by provincial, territorial, and federal privacy statutes that regulate the collection, use, retention, and disclosure of personal information. The Privacy Act (PA) regulates federal government institutions' relationship with personal information, while private sector organizations' relationship with personal information is regulated by the federal Personal Information and Protection of Electronic Documents Act (PIPEDA) or by any substantially similar legislation promulgated in the province in which the private entity operates. These protections, however, are subject to numerous exceptions that allow information sharing between government entities and between private sector and state entities. Statutes enabling law enforcement access to personal information generally require prior authorization (subject to numerous exceptions). Domestic law enforcement agencies obtain prior authorization under the Criminal Code, while Canada's primary national security intelligence gathering agencies, the Communications Security Establishment of Canada (CSEC) and the Canadian Security Intelligence Service (CSIS) are subject to more relaxed provisions in their respective enabling statutes. While CSEC's capacity to intentionally conduct surveillance over communications in Canada without Ministerial authorization is limited, the agency continuously operates surveillance over foreign signals intelligence through Echelon, in cooperation with other signatories to the UK–USA Security Agreement. National security concerns have also led to laws requiring certain private sector entities to gather and disclose personal information about their clients to government agencies in relation to large financial transactions and air travel, as well as to increased impetus for information sharing between law enforcement and intelligence agencies. Although CSEC has ongoing access to communications outside of Canada, Canadian law enforcement agents' access to data outside of the jurisdiction generally arises from formal and informal networks, as well as to requests for assistance from partners under Mutual Legal Assistance Treaties (MLAT). The Office of the Privacy Commissioner of Canada (OPC) and its provincial and territorial counterparts play an active role in informing Canadians about informational privacy issues, including transborder flows of Canadians' personal information. With the 2012 announcement of Canada's first anti-terrorism strategy and the introduction of Bill C-30 in Parliament, Canadians are deeply involved in debate regarding expanded government access to personal information. As currently structured, Bill C-30 would, inter alia, mandate telecommunications service providers (TSPs) to disclose to designated state agents certain personal information that is currently only subject to voluntary disclosure, require TSPs to ensure their technical infrastructures are intercept compatible, allow ‘inspectors’ warrantless access to TSPs' facilities, and provide civil and criminal immunity for TSPs who voluntarily retain data for and/or produce data to the state if it would be otherwise lawful for them to do so, while also broadening judicial powers to issue production and retention orders.

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)0.005
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.174
Threshold uncertainty score0.959

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.027
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.015
Science and technology studies0.0110.005
Scholarly communication0.0090.002
Open science0.0020.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.154
GPT teacher head0.374
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

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 designQualitative
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

Citations7
Published2012
Admission routes1
Has abstractyes

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