Expanding sites for peacebuilding: Decolonizing education and research to retrieve cultural and critical sources of knowledge
Bibliographic record
Abstract
This panel considers the ideological, intellectual, personal, and practical dimensions of peacebuilding. It explores how various educational spaces, self-inquiry, and theory can bring attention to cultural predicaments and communities that are frequently neglected, omitted, or misunderstood in peacebuilding. In settler-colonial states, schooling is a process of naturalizing inequality which can be exposed and potentially interrupted through the application of peace and conflict studies methods and theories. As academic institutions seek to address gender-based violence taking place both on campuses and online, approaches may fall short in considering the institution’s continued entrenchment in colonialism. Further decolonization is needed to better address this violence and support victims. As the joint pandemics of Covid-19 and anti-black racism glaringly unfolded in 2020, many American museums began using digital interfaces to make these crises more legible to the broader public. In the process, they began to redefine the social function of contemporary American museums. As a peace and conflict practitioner, the spaces we look to heal and to fix are endless, and as we look to explore peace building pathways in the world around us, we can also look inward to the peace we build within our own self. Dr. Marc Benjamin Kuly – Assistant Professor, Education, University of Winnipeg Seeing the system: Adapting peace and conflict studies to the task of school system critique Heidi Lamb – Doctoral Student, Peace and Conflict Studies, University of Manitoba Unsettling violence in academic online spaces: An exploration into decolonizing university’s approaches to GBV Anya Russian – M.A., Peace and Conflict Studies, University of Manitoba/Winnipeg Transforming racial conflict into critical opportunities: How two North Carolina museums are redefining their civic role Jennifer Tesoro – Doctoral Student, Peace and Conflict Studies, University of Manitoba Storytelling my way to a more peaceful self
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.067 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.024 | 0.014 |
| Science and technology studies | 0.015 | 0.024 |
| Scholarly communication | 0.030 | 0.043 |
| Open science | 0.004 | 0.040 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.026 | 0.008 |
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 source (direct Gemma or distilled Codex), 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".