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Record W2899219023

Studying Sexual and Gendered Violence Prevention in Higher Education: Local/Vertical, Global/Horizontal, and Power-Based Frames

2018· article· en· W2899219023 on OpenAlexaffvenue
Miglena S. Todorova

Bibliographic record

VenueCanadian women's studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHumanitiesPolitical scienceSociologyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Les recents travaux sur les programmes de prevention de la violence sexuelle et sexiste dans les campus des colleges et universitaires a travers le monde ont revele le peu d’efficacite de ces initiatives qui sont plutot des pratiques qui l’interdisent et dont les concepts sont ignores par les erudits du milieu. Cet article explore avec l’aide de cadres analytiques bases sur le pouvoir et ancres dans la theorie et les pratiques feministes transnationales, utilise trois scenarios. Le premier rapporte les notes d’un groupe de chercheurs qui ont collige les donnees sur la violence sexuelle dans une grande universite publique de Bulgarie et examine comment les recherches selon une methode de l’Union europeenne, selon une ong internationale feminine et des approches preventives et imaginatives americaines furent appliquees a l’ epistemologie bulgare. Le deuxieme scenario questionne les actions contradictoires des universites responsables de la violence envers les femmes et autres participants une education superieure tout en les protegeant contre cette violence. Le troisieme scenario suggere des programmes de prevention envers une population specifique d’etudiants, dans ce cas, envers les cinq millions d’etudiants qui transitent dans le monde de l’education et qui sont invisibles dans le champ de la prevention.

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)0.000
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 score0.635
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.057
GPT teacher head0.345
Teacher spread0.288 · 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.

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

Citations2
Published2018
Admission routes2
Has abstractyes

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