How do Canadian racialized sport media personalities influence conversations within digital spaces?
Bibliographic record
Abstract
Biography of Sabrina Razack Sabrina Razack is an Educator for the TDSB, with NCCP certifications in basketball, track and field and has coached multiple sports for over 7 years. She recently finished a three and a half year contract with the Pan Am/Parapan Am Games Organizing Committee (TO2015). Her role included developing sport for development programs, curriculum and large-scale events that promoted a fusion of sport and culture. Sabrina has also worked with the Canadian Association for the Advancement of Women and Sport and Physical Activity where she designed programs and resources for newcomer and racialized females. At the University of Toronto Sabrina completed her master’s thesis examining the player experiences of National Women’s Cricketers in Canada. She currently sits on the Advisory Board of the Canadian Sport Film Festival and holds the position of Program Development and Research Chair of ONABSE. She is also individual board member of the Commonwealth Games of Canada. As a scholar and sport sociologist, Sabrina is fascinated by the intersections of race, gender, class and culture.
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 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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.030 | 0.013 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".