Exploring Canadian News Media’s Portrayal of Federal Penitentiaries and Prisoners During COVID-19
Bibliographic record
Abstract
The media have often portrayed prisons and prisoners in a distorted manner. Prisoners are often portrayed as more dangerous and violent than they typically are, and prisons as necessary institutions that function effectively. Using a qualitative content analysis of 84 newspaper articles published online by Canadian news outlets, this study explores how the news media portrayed Correctional Service Canada (CSC) federal penitentiaries and prisoners detained in these institutions during the first 11-months of the COVID-19 pandemic. The results reveal that the media portrayed prisoners as human beings that are entitled to exercise their rights until they were prioritized for vaccinations, at which point there was a shift towards their portrayal as an undeserving dangerous underclass. CSC was portrayed as having failed to address and protect prisoners’ needs and rights during the pandemic. The media ultimately portrayed federal imprisonment as a system that is broken and incarceration as an ineffective response to criminal behaviour. The implications of these findings – including the need for a “radical rethink” of federal imprisonment – and suggestions for future research are discussed.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".