Last Word
Bibliographic record
Abstract
Media coverage of the Supreme Court of Canada has emerged as a crucial factor not only for judges and journalists but also for the public. It’s the media, after all, that decide which court rulings to cover and how. They translate highly complex judgments into concise and meaningful news stories that will appeal to, and be understood by, the general public. Thus, judges lose control of the message once they hand down decisions, and journalists have the last word. To show how the Supreme Court has fared under the media spotlight, Sauvageau, Schneiderman, and Taras examine a year in the life of the court and then focus on the media coverage of four high-profile decisions: the Marshall case, about Aboriginal rights; the Vriend case, about gay rights; the Quebec Secession Reference ; and the Sharpe child pornography case. They explore the differences between television and newspaper coverage, national and regional reporting, and the French- and English-language media. They also describe how judges and journalists understand and interact with one another amid often-clashing legal and journalistic cultures, offering a rich and detailed account of the relationship between two of the most important institutions in Canadian life.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.403 | 0.277 |
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".