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Record W2917138573 · doi:10.3390/socsci8020071

Graduate Students, Community Partner, and Faculty Reflect on Critical Community Engaged Scholarship and Gender Based Violence

2019· article· en· W2917138573 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSocial Sciences · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsScholarshipPublic relationsService-learningSociologyEngaged scholarshipMainstreamPolitical sciencePedagogy

Abstract

fetched live from OpenAlex

This article reflects on the challenges and opportunities associated with community engaged learning at the graduate level, and challenges higher education to do more to support the teaching–research–service nexus. The community university partnership involved a graduate student class, a faculty member, and a community member from a provincial not for profit association. We examined our principled and collaborative process of critical community engaged scholarship geared toward addressing violence against women, and more specifically, femicide. Our research resulted in knowledge mobilization tools that could be used to inform various audiences (e.g., women’s shelter staff, the public, government, and journalists) about how mainstream media sources report and portray the issue of femicide. Our work had an explicit social justice focus with aims to generate a better understanding of the structural causes of violence against women and historically-created gendered hierarchy and its ongoing impacts. This paper offers insights for others interested in pursuing community engaged research within a community engaged learning environment.

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.

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)0.029
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0290.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0270.002
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.004
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 head0.470
GPT teacher head0.506
Teacher spread0.036 · 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