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Narrative Imagination and Social Change: Instructors in Agricultural Colleges in Ethiopia Address Sexual and Gender-Based Violence

2021· article· en· W3211921821 on OpenAlex
S. M. Hani Sadati, Claudia Mitchell

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

VenueEducational Research for Social Change · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican history and culture studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsNarrativeCitizen journalismPerceptionSexual violenceNarrative inquiryPsychologyParticipatory action researchPedagogyGender studiesSociologyPolitical scienceArtCriminology

Abstract

fetched live from OpenAlex

Ethiopia has one of the highest rates of sexual and gender-based violence (SGBV) in the world, making female students particularly vulnerable in its post-secondary institutions. Although there is extensive literature that describes the problem, mainly from the students' perspectives, what remains understudied is the role of instructors, their perception of the current issues, and what they imagine they can do to address campus-based SGBV, particularly in rural settings. In this study, we used the concept of narrative imagination to work with instructors in four Ethiopian agricultural colleges to explore how they understand the SGBV issues at their colleges and what they imagine their own role could include in efforts to combat these problems. Using qualitative narrative-based methods such as interviews and an interactive storyline development workshop, as well as cellphilming (cellphone + film) as a participatory visual method, the data were collected across several fieldwork phases. We consider how we might broaden this framework of narrative imagination to include the notion of art for social change.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
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 head0.320
GPT teacher head0.471
Teacher spread0.151 · 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