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Record W1950697498 · doi:10.5334/sta.cs

Gender-Specific Election Violence: The Role of Information and Communication Technologies

2013· article· en· W1950697498 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueStability International Journal of Security and Development · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHarmInformation and Communications TechnologyICTSEmpowermentPoliticsPolitical sciencePublic relationsCriminologySociologyLaw

Abstract

fetched live from OpenAlex

<p class="p1">The rising influence of new information and communication technologies (ICTs) has paralleled the rapid development of women’s political participation worldwide. For women entering political life or holding public positions, new ICTs are frequently used as tools of gender-specific electoral and political violence. There is evidence of ICTs being used to perpetrate a broad range of violent acts against women during elections, especially acts inflicting fear and psychological harm. Specific characteristics of ICTs are particularly adapted to misuse in this manner. Despite these significant challenges, ICTs also offer groundbreaking solutions for preventing and mitigating violence against women in elections (VAWE). Notably, ICTs combat VAWE through monitoring and documenting violence, via education and awareness-raising platforms and through empowerment and advocacy initiatives.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score0.142

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.018
GPT teacher head0.265
Teacher spread0.247 · 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