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Record W4366602221 · doi:10.1111/acer.15087

Development and validation of the <scp>C‐SHADE</scp> scale for measuring perpetration of common sexually harassing and aggressive behaviors in drinking environments

2023· article· en· W4366602221 on OpenAlexafffund
Kathryn Graham, Sharon Bernards, Antonia Abbey, Charlene Y. Senn, Tara M. Dumas, AnnaLise Trudell, Peter Donnelly, Samantha Wells

Bibliographic record

VenueAlcohol Clinical and Experimental Research · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsPublic Health OntarioUniversity of TorontoWestern UniversityUniversity of WindsorCentre for Addiction and Mental Health
FundersCanadian Institutes of Health Research
KeywordsHarassmentAggressionPsychologyAlcohol consumptionPoison controlInjury preventionClinical psychologyDemographyEnvironmental healthSocial psychologyMedicineAlcohol

Abstract

fetched live from OpenAlex

BACKGROUND: Sexual aggression (SA) is ubiquitous in drinking environments. Although such behavior is often seen as normal and acceptable, the targets of SA experience many negative consequences. This research aimed to develop a valid measure of common acts of SA in drinking settings for estimating prevalence and evaluating prevention initiatives. METHODS: We developed a questionnaire measure of common acts of sexual harassment and aggression in drinking environments (C-SHADE) based on descriptions of SA behavior from our own and others' research. The measure was validated in a cross-sectional survey of 335 men aged 19 to 25 using webpanels from an online survey company. Validation measures included: a modified version of the Sexual Experiences Survey (M-SES), measures of SA by peers in drinking environments, SA-related attitudes, expectancies about sexual effects of alcohol, and alcohol consumption. RESULTS: The C-SHADE showed high internal consistency (α = 0.96) and was significantly correlated with M-SES (r = 0.52), SA by peers (r = 0.61 to 0.70), SA-related attitudes/expectations (r = 0.38 to 0.55), and measures of alcohol consumption (r = 0.22 to 0.36). Overall, 71.9% of participants reported SA using the C-SHADE versus 24.7% with the M-SES. We compared the responses of participants who reported perpetration on both measures (N = 83), on only the C-SHADE (N = 141), and among nonperpetrators (N = 89; excluding four participants who reported perpetration only on the M-SES). The M-SES/C-SHADE perpetrators scored significantly higher than C-SHADE-only perpetrators and nonperpetrators on most SA-related and drinking measures, while C-SHADE-only perpetrators scored significantly higher than nonperpetrators on peer SA and two attitude measures. CONCLUSIONS: The C-SHADE is suitable for measuring prevalence and evaluating interventions in drinking settings. The C-SHADE confirmed a high prevalence of SA in drinking settings and identified an important group of C-SHADE-only perpetrators for whom interventions that focus on situational precipitators of SA in drinking settings may be especially useful.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.295
GPT teacher head0.500
Teacher spread0.205 · 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 designObservational
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

Citations4
Published2023
Admission routes2
Has abstractyes

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