MétaCan
Menu
Back to cohort
Record W4395694484 · doi:10.15402/esj.v10i1.70833

Using Literature Review to Inform an Anti-Oppressive Approach to Community Safety

2024· article· en· W4395694484 on OpenAlexaffvenueabout
Julie Chamberlain, Stacy Cardigan Smith, Dagen Perrott

Bibliographic record

VenueEngaged Scholar Journal Community-Engaged Research Teaching and Learning · 2024
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsSociologyCriminologyEngineering ethicsEngineering

Abstract

fetched live from OpenAlex

Literature review is a common piece of any scholarly research, but it is rare for it to be squarely at the centre of a community-based project. In this Report from the Field, the research team critically reflects upon the creation and use of a literature review on grassroots, anti-oppressive approaches to community safety in Winnipeg, Manitoba, Canada. Writing in conversation with one another, we explore the tensions of navigating and challenging safety discourse and securitization practices in our city, from our distinct experiences and positions as an academic researcher, community partner, and student research assistant. In the process, we illuminate a collaboration that offers insights for academic and community researchers alike. We reflect on creating an accessible basis for community conversation and planning while doing justice to the sources of anti-oppressive theory and practice, particularly when initially speaking to mostly white and privileged community members. The literature review has generated discussion about what it means to approach safety as a collective resource rather than an exclusive possession, and will inform practical strategies in the neighbourhood and beyond.

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)0.775
metaresearch head score (Gemma)0.252
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.739
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.7750.252
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.3970.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0000.740
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 head0.253
GPT teacher head0.518
Teacher spread0.265 · 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 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

Citations0
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueEngaged Scholar Journal Community-Engaged Research Teaching and LearningSame topicResilience and Mental HealthFrench-language works237,207