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Record W1977156883 · doi:10.5130/ijcre.v7i1.3395

Engaging evaluation research: Reflecting on the process of sexual assault/domestic violence protocol evaluation research

2014· article· en· W1977156883 on OpenAlexaff
Mavis Morton, Anne Bergen, Melissa Horan, Sara Crann, Danielle Bader, Linzy Bonham

Bibliographic record

VenueGateways International Journal of Community Research and Engagement · 2014
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsGeneral partnershipScholarshipSociologySexual assaultTheme (computing)Community engagementDomestic violenceProtocol (science)Engaged scholarshipPublic relationsCommunity-based participatory researchPsychologyParticipatory action researchPoison controlHuman factors and ergonomicsPolitical scienceMedicineComputer science

Abstract

fetched live from OpenAlex

In keeping within the theme of CU Expo 2013, ‘Engaging Shared Worlds’, this case study examines and reflects on a complex community-university partnership which developed to conceptualise, design, conduct and communicate evaluation research on one community’s sexual assault and domestic violence protocol. As community-university partners coming together for the first time, we reflect on the purpose of our engagement, the characteristics and principles which define our partnership and our potential to teach graduate students how to undertake community-engaged scholarship.Keywords: Community-engaged research, evaluation research, complex community-university partnerships, scholarship of engagement, practice research

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.350
metaresearch head score (Gemma)0.397
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.650
Threshold uncertainty score0.801

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3500.397
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0180.029
Scholarly communication0.0170.014
Open science0.0050.023
Research integrity0.0060.011
Insufficient payload (model declined to judge)0.0040.001

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 head0.882
GPT teacher head0.738
Teacher spread0.144 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designQualitative
DomainEvaluation
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

Citations5
Published2014
Admission routes1
Has abstractyes

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