Disrupting a Canadian Prairie Fantasy and Constructing Racial Otherness: An Analysis of News Media Coverage of Trevis Smith’s Criminal HIV Non-Disclosure Case
Bibliographic record
Abstract
This paper studies how HIV criminalization is portrayed in the mainstream Canadian press by examining news representations of Trevis Smith. Smith’s case is the most reported case of criminal HIV non-disclosure in Canadian history. Our analysis is based on a corpus of 271 articles written about Smith between 2005 and 2012. Our analysis shows that coverage of Smith’s case is distinct from reportage of other criminal HIV non-disclosure cases because he was a well-known Black athlete playing for the Saskatchewan Roughriders at the time of his criminal charge. We argue that news articles represent Smith as a particular kind of threatening racialized “other” through forms of writing that link crime reporting with sports reporting. Our analysis of headlines and quotation patterns emphasizes how news articles construct Smith as a blameworthy outsider and produce Canada as an imagined white settler nation.
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 | 0.002 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.016 | 0.020 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".