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Record W3114367262

TECHNOLOGY-FACILITATED VIOLENCE AGAINST WOMEN & GIRLS: ASSESSING THE CANADIAN CRIMINAL LAW RESPONSE

2019· article· en· W3114367262 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Canadian Bar Review · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsDignityCriminal lawAutonomyDomestic violencePolitical scienceSexual violenceCriminologyLawSociologyPoison controlHuman factors and ergonomics
DOInot available

Abstract

fetched live from OpenAlex

Alongside increasing awareness of the ways in which digital technologies can be used to facilitate violence against women and girls, there have come questions about the applicability and efficacy of Canadian criminal law responses. Rooted in a feminist perspective and based on a review of over 400 reported cases involving technology-facilitated violence (TFV), the authors argue that Canadian criminal law both can and should respond. Technology-facilitated violence against women and girls (TFVAWG), like violence against women and girls (VAWG) more generally, undermines their rights to sexual integrity, dignity, autonomy and to equal participation in public and private life. Criminal law responses are an important mechanism for expressing public disapprobation of TFVAWG’s negative effects on these fundamental rights. However, the authors’ review reveals certain shortcomings in achieving survivor-centred outcomes. Recognizing these and other limitations of criminal law, the authors also assert that proactive approaches aimed at broader social transformation will be essential to ensuring the full and equal participation of women and girls in a digitally connected world.

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)0.006
metaresearch head score (Gemma)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.033
GPT teacher head0.333
Teacher spread0.301 · 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