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Record W4408954490 · doi:10.1080/17441692.2024.2446720

Addressing ‘wicked complex problems’: Qualitative understandings of sexual violence prevention in male-dominated industries

2025· article· en· W4408954490 on OpenAlexaff
Sarah Vrankovich, Sharyn Burns, Giselle Woodley, Jacqueline Hendriks

Bibliographic record

VenueGlobal Public Health · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsImpact
FundersGovernment of Western Australia
KeywordsQualitative researchSexual violencePoison controlSociologyGender studiesSuicide preventionHuman factors and ergonomicsOccupational safety and healthInjury preventionStructural violenceCriminologyPsychologyPolitical scienceMedicineEnvironmental healthSocial sciencePolitics

Abstract

fetched live from OpenAlex

Globally there has been increased focus on the prevalence of sexual violence in workplaces, including the mining industry. In Western Australia, where this study is situated, this industry is a significant employer, predominantly male-dominated, and the prevalent use of fly-in-fly-out schedules can blur work and social life. Consequently, efforts to prevent and manage workplace sexual violence have become a priority, leading to the development and implementation of various strategies and resources. Qualitative interviews were conducted with 34 participants, including sexual violence prevention professionals (n = 16) and mining industry workers (n = 18). Reflexive thematic analysis identified systemic and behavioural considerations that may be transferrable to other male-dominated workplaces. Participants emphasised the importance of primary prevention training programmes that included engaging activities, realistic scenarios, careful use of language, humour and inspirational facilitators. Genuine consultation with workers is critical to ensure key messages are appropriately received. Prevention interventions also need to be supported by appropriate reporting mechanisms and support processes for victim/survivors. This research aims to provide an understanding of current sexual violence prevention initiatives within the Australian mining sector, offering recommendations for future approaches tailored to industries and contexts with similar dynamics.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.657
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
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 head0.343
GPT teacher head0.498
Teacher spread0.156 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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