Editorial: ‘Urgent Care’ Needed: Healing Colonial Harms and Racism for Education to Thrive
Bibliographic record
Abstract
Colonial harms and racism cause long-term injuries.Unfortunately, they occur and exist in Canadian schools and higher education institutions in multiple forms and in various degrees.They intensify in times of increased international conflict, as we have recently witnessed with the escalating violence and war in the Middle East.Although such regions are geographically distant, Canada, as either a site of further (related) violence or as a place of refuge, is inseparable from these conflicts.At the same time, we must be mindful of the perennial undercurrent of racism that has historically permeated Canadian schooling through its structures, norms, policies, practices, and curriculum.As such, the studies in this winter issue of CJE poignantly identify when, where, how, and which students and staff in Canadian schools experience injuries from racism and colonialism.In doing so, the authors remind us of the collective ideals of education, arguing that to advance along the path toward decolonial practices and humility, educational institutions need to create more inclusive 'urgent care' spaces that focus on healing colonial harms and racist aggressions.The urgency to 'heal' the wounds of social and racial exclusion that children experience in the school system is captured in Soudeh Oladi's study of Muslim mothers about their children's experiences in Canadian schools.These children's racial injuries happen on multiple fronts and involve multiple actors, including non-Muslim peers, teachers, and administrators.Oladi details specific incidences and types of racial aggressions and exclusion that these children and their mothers have experienced in the school system in relation to their race, religion, attire, and language.The study points to where and how Editorial v
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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 | 0.008 | 0.039 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.019 | 0.023 |
| Insufficient payload (model declined to judge) | 0.022 | 0.021 |
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".