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Record W2963978093 · doi:10.1177/1077801219856115

Innovating the Problem Away? A Critical Study of Anti-Rape Technologies

2019· article· en· W2963978093 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.

Bibliographic record

VenueViolence Against Women · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsTrent University
Fundersnot available
KeywordsUnintended consequencesInternet privacyVariety (cybernetics)Context (archaeology)Wearable computerThe InternetComputer securityPoison controlWearable technologyMobile technologyHuman factors and ergonomicsMobile deviceComputer scienceMedicineMedical emergencyPolitical scienceWorld Wide Web

Abstract

fetched live from OpenAlex

In the context of expanding preventative strategies for addressing sexual violence, we are witnessing the emergence of an array of new anti-rape technologies targeted at women. These tools, promoted primarily through the Internet, include a variety of apps for mobile phones, signal- and alarm-emitting wearable technologies, and internal and external body devices. Based on analyses of websites promoting such instruments, we critically examine these devices with respect to their possible benefits, limitations, and unintended physical, social, and legal consequences for women. We suggest that unanticipated outcomes may undermine both victims and their cases, those the technologies are ostensibly designed to help.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.783
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.024
GPT teacher head0.330
Teacher spread0.306 · 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