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Record W3202081699 · doi:10.29173/alr2668

Canadian Hack-Back?: A Consideration of the Canadian Legal Framework for Private-Sector Active Cyber Defence

2021· article· en· W3202081699 on OpenAlexaffvenueabout
Kristina V. Gerke

Bibliographic record

VenueAlberta Law Review · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCybersecurity and Cyber Warfare Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsBusinessPrivate sectorLaw and economicsLawComputer securityPolitical scienceComputer scienceSociology

Abstract

fetched live from OpenAlex

In recent years, a debate has emerged over the extent to which victims of cyber security intrusions should be permitted to conduct activities in response — in particular, activities with effects in networks outside the victim’s own. Such controversial efforts are often referred to as active cyber defence (ACD) or, more colloquially, as “hack-back.” While multiple researchers have written about how private-actor ACD fits within the United States legal framework, this topic remains understudied from a Canadian perspective, raising the question of how Canadian legislation may address ACD. Currently, Canadian legislation implicitly prohibits most, if not all, ACD efforts, but international law likely leaves room for countries to legalize certain forms of ACD. Going forward, there may be a significant benefit to Canadian legalization of ACD if these efforts are limited to “intelligence gathering” and constrained by strict government oversight.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient 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 score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.303
Teacher spread0.274 · 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.

Study designTheoretical or conceptual
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

Citations2
Published2021
Admission routes3
Has abstractyes

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