Examining Experiences of Racialized Students in Southern Ontario Catholic Schools
Bibliographic record
Abstract
There are Catholic high schools in Ontario where more than 50 percent of students are not Catholic. Research has shown that half of Ontario parents chose to send their children to Catholic high schools even when they and their children are not Catholic. In the shadow of the historical legacy of residential schools, which for over 100 years in partnership with Christian denominations like the Catholic Church, facilitated cultural genocide, and the abuse and death of thousands of Indigenous people, this study considers present day conditions for racialized students in Southern Ontario Catholic schools. The dismal academic outcomes for those who identify as Black and Indigenous Canadian are contemplated in their Catholic context. Using a mixed methods explanatory sequential model, this study examined the experiences of racially marginalized students in Catholic schools in Southern Ontario in an attempt to determine how effectively the Equity and Inclusive Policy, implemented across the province, support their culture and identity. Culturally Responsive Pedagogy and the Christian Philosophy of Education serve as the theoretical lens through which the experiences of these students are examined. Participants in this study included students who attended Catholic school between 2014 and 2018, and teachers and administrators from the Catholic school system. Participants were engaged through surveys and semi-structured interviews. Document analysis served as a source of data in order to establish what programs, activities and policies inform the day-to-day life of students in Catholic schools. As will be seen from the findings of this study, both policy and philosophy have failed to trickle down sufficiently to Catholic schools and classrooms. As such, the equity and inclusive policies implemented by Catholic schools in Ontario are failing to accomplish the intended outcome of every single student having all the opportunity to reach their full potential and experience personal and academic success. Racialized students still experience racial, cultural, and religious discrimination, and often find it challenging to be their authentic selves. Yet, despite these experiences, most students still manage to achieve positive academic outcomes and maintain strong ties to their community, a triumph they attribute to a network of family and friends.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".