The Histories We Inherit: Concordia's Reckoning with the Pasts of Its Founding Institutions
Bibliographic record
Abstract
A University of Maine alumnus, Professor Graham Carr is president and vice-chancellor of Concordia University in Montreal, Canada. A historian by training and a long-time leader in higher education in Canada, Carr returns to his alma mater to explore the role universities can and should play in addressing the legacy of colonialism and anti-Black racism on campuses and in greater society. He will explore two case studies from Concordia’s recent history: a formal apology it issued for the role systemic racism played in student protests and their aftermath in 1969 as well as its response to the role two religious orders with ties to Concordia played in Canada’s infamous residential school system. In both examples, Concordia has had to come terms with the actions of its founding institutions. Please join us as we hear firsthand how Concordia’s university leadership is charting a course forward through two of the most important cultural topics of our day.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.046 | 0.047 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".