Comment moderation strategies in Canadian news media and their principles
Bibliographic record
Abstract
This paper offers a critical examination of Canadian news guidelines and policieson user-generated content (UGC) posted on news-related comment sections andsocial media.The outline of how news-related UGC is moderated within Canadian news is achievedby looking at the online comment policies of major Canadian news organizations like .the CBC, CityNews (Halifax), CTV News, Glacier Media, Global News, The Globeand Mail, Narcity Media, Postmedia, QUB (Québecor), and Torstar.The policies highlight how Canadian news organizations have practical strategiesto manage news-related UGC but also call upon positive and negative socialprinciples, to flag ill practices, foster democracy, and fight against online hate speechand libel. The analysis shows how guidelines reflect many of the key principles highlightedin the literature review but make no reference to economic principles thatare emphasized as important in academic and journalist concerns with moderatingnews-related UGC.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".