Serious Game Design as Research-Creation to Address Sexual and Gender-Based Violence
Bibliographic record
Abstract
Research-creation is a growing practice in humanities that tries to balance the pace of socio-cultural inquiries with modern media advancements and qualitative knowledge construction methods. It refers to various conjunctions of “research” and “creation” (i.e., research-for-creation; research-from-creation; creative presentations of research; and creation-as-research) around an artistic component. Drawing from fieldwork with instructors in four agricultural colleges in rural Ethiopia, this article explores how a participatory arts-based serious game design process is explicable within the context of research-creation. This work’s change-oriented agenda led to developing Mela, a serious game, to educate and empower instructors in agriculture colleges to tackle sexual and gender-based violence issues in their institutions. Here, we articulate Mela’s design process, its artistic composition, and how we understand it from different angles of research-creation practices. We also offer our introspective accounts during and after the design stages, referencing culture and gender as critical concepts. Serious games are pedagogical products that are designed for a meaningful learning experience. This work deepens the understanding of how research-creation practice can benefit the serious game design field by ensuring the attention to both process and production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".