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Record W4313469043 · doi:10.4324/9781003332671-5

Student voices

2023· book-chapter· en· W4313469043 on OpenAlexaboutno aff
D. Scharie Tavcer, Vicky Dobkins

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologySociology

Abstract

fetched live from OpenAlex

This chapter presents findings from student and staff participants who were interviewed or surveyed over the course of the research project. The research project had initially begun conducting in-person interviews at seven chosen PSIs across Canada but was halted when the COVID-19 pandemic closed campuses and then replaced with electronic surveys. Recruitment methods included posting an advert and anonymous link to the electronic survey on the social media sites of the chosen PSIs, as well as postings on the PSI’s student association or student group accounts and on the author’s Twitter, Facebook, and LinkedIn accounts with relevant hashtags and tags. Combining all modes of data collection resulted in 198 total participants (15 staff and 182 students) with an uneven distribution of participants among the seven PSIs. The findings reflect the participant’s understanding (and somewhat lack thereof) of consent, their perspectives on consent education, and their understanding of what programming and services are currently offered at their post-secondary institutions (PSIs). The research project revealed that 90% of respondents agreed that an online sexual consent education module should be mandatory for all students at their PSI, and an overwhelming majority (over 97%) believed that it should be mandatory for everyone, not just students.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.907
Threshold uncertainty score0.998

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.004

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 head0.086
GPT teacher head0.385
Teacher spread0.300 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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