Symposium: Driving Black Student Success on a System-Wide Level
Bibliographic record
Abstract
Qualitative and quantitative data indicators from the Toronto District School Board (TDSB) and York University highlight the crucial need for a holistic Black Student Success and Excellence (BSSE) strategy to address systemic racism that Black students face in all aspects of their schooling. To this end, TDSB developed a program to foster critical consciousness in educators. The initiative partnered educators, school administrators, central support staff, associated researchers and initiative leaders in an inquiry-based journey relevant to their role(s), space(s) and experience. The study took place in 17 secondary and elementary schools. Results demonstrate that participants fostered their own critical consciousness and that of their students’ through the research or inquiry process. The symposium details experiences from across this work. It also explores the direct and indirect effects of the initiative on participants related to the conditions and mechanisms for entry, implementation, mobilization and sustainability, and processes within the initiative at micro and macro levels. As an extension of this work, TDSB and York University also piloted a Black Student Summer Leadership Institute to provide Black secondary students with opportunities to understand and develop leadership and agency in challenging anti-Black racism through principles of Youth Participatory Action Research. As part of their inquiry, students in the summer program also identified the following key themes to describe the Black student experience: sense of belonging, stress, engagement, body/self-image, neglect, student voice and safety. Overall, this panel highlights the different components, challenges and successes with this initiative and implications for expanding this work.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".