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Record W2805849179

Hegemonic masculinity and rape culture: negotiating manhood at a Canadian university

2018· dissertation· en· W2805849179 on OpenAlexfundaboutno aff
Lesley S. Derraugh

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2018
Typedissertation
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMasculinityHegemonic masculinityGender studiesNegotiationHegemonyContext (archaeology)SociologySocial psychologyPolitical sciencePsychologySocial sciencePoliticsGeographyLaw
DOInot available

Abstract

fetched live from OpenAlex

Using in-depth qualitative interviews with 12 male-identified individuals between the ages of 19 and 25 recruited from the Memorial University community, this project examines how men negotiate the complexities of hegemonic masculinity in a society in which that hegemonic masculinity is constructed as violent. This research is prompted by the current crisis in North America of campus rape culture and grounded in the need to identify solutions to the rate of sexual violence occurring in university communities. To examine masculinities in this context, I explore this key question: How do male-identified individuals understand and negotiate the intricacies of masculinity and societal expectations of what it means to “be a man”? to explore this, I turn to the following sub-questions: a) to what extent do participants identify with hegemonic notions of masculinity? b) what developmental experiences have most influenced their self-identification (either positively or negatively) with traditional masculine norms? c) how is rape culture understood, perceived and perpetuated (or challenged) by male-identified university students? Drawing on the theoretical work of gender researchers such as Raewyn Connell and Michael Kimmel, this thesis will include insights into the ways in which masculinities are being reproduced, challenged and resisted.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.432
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0110.002
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0020.002
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 head0.031
GPT teacher head0.281
Teacher spread0.249 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2018
Admission routes2
Has abstractyes

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