Bibliographic record
Abstract
5 When I came to Life Stories of Montrealers Displaced by War, Genocide, and Other Human Rights Violations, the Community-University Research Alliance (CURA) project had not yet officially started: researchers and community groups were still finding each other and pairing up. I was representing Isangano, Montreal’s cultural group of young Rwandans. Isangano had accepted the project’s invitation because it was an opportunity to walk our talk: we were deeply involved with community building, and it was a chance to strengthen ties between Rwandans by working closely with Page-Rwanda, another community group. It was also a chance to work with scholars, both Rwandan and non-Rwandan. Rwandan scholars were a much needed and fervently wished for change from the usual colonial attitude of Western “experts” producing and disseminating the only available knowledge about our situation. Non-Rwandan scholars gave us a welcome chance to open to the larger community, especially in the context of the sharing-authority concept permeating the participants and the whole project. The wonderful texts featured in this publication were presented at CURA’s first conference, appropriately named for the core principle, “sharing authority.” Each text comes out of a very different project, and while every one has a distinct take on the concept, the articles have in common a very intimate, engaged perspective they speak from, a voice that speaks to me as a community co-applicant. Rereading these texts and writing this preface was an opportunity to clarify what I understand to be the weaknesses and the strengths of my work in the community and our larger work together. Three years ago, I started a dialogue project in Montreal’s Rwandan community. Tuganire—let’s talk—was born out of the need to shake people up and create wellness within what I perceived to be a lifeless community of inert individuals. I felt we were not addressing our needs or sharing and taking advantage of our strengths. Discrimination, exile, migration, and immigration, and finally the 1994 genocide of the Tutsi in Rwanda, had devastated us and left us reeling, surviving certainly, but not living anymore.
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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 | 0.020 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.023 | 0.092 |
| Scholarly communication | 0.029 | 0.034 |
| Open science | 0.004 | 0.036 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".