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Virtual Rape

2006· article· en· W3189532686 on OpenAlexaff
Richard C. MacKinnon

Bibliographic record

VenueJournal of Computer-Mediated Communication · 2006
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsCytodiagnostics (Canada)
Fundersnot available
KeywordsVirtual realitySocial realitySocial constructionismOrder (exchange)SociologySocial lifeEpistemologyComputer scienceHuman–computer interactionBusinessSocial sciencePhilosophy

Abstract

fetched live from OpenAlex

The current social construction of rape in virtual reality is not a worthwhile endeavor in that it forces theorists to adapt an undesirable concept in order to import it into virtual reality. Rape exists as such in “real life” because of the social construction of women relative to the social construction of men. The relationship of these constructions is not and does not have to be analogous in virtual reality because virtual reality presents an opportunity for social reordering. Among these opportunities is the exploration of the ramifications of bodies presented arbitrarily. Given these opportunities, theorists seeking to pursue positive constructionism ought to endeavor to develop virtual-reality specific constructions which empower rather than import real life constructions which victimize.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.037
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0060.004
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0370.005

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 head0.027
GPT teacher head0.318
Teacher spread0.291 · 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

Citations41
Published2006
Admission routes1
Has abstractyes

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