Opinion Discourse and Canadian Newspapers: The Case of the Chinese “Boat People”
Bibliographic record
Abstract
“Opinion” discourse — editorials, op-ed articles, and guest columns — assumes an important communicative function by offering newsreaders a distinctive and authoritative voice that will speak to them directly, in the face of troubling or problematic circumstances. Opinion discourse addresses newsreaders embraced in a consensual relationship by taking a particular stance in relation to the persons and topics referred. Nevertheless, despite its communicative importance, opinion discourse has received less sustained theoretical and empirical attention from scholars than “hard” news. Where “hard” news purports to be balanced and fair, “opinion” discourse problematizes the world by taking up the normative dimension of issues and events as the justification and rationale for taking sides. Taking the arrivals to Canada of four boatloads of “illegal” Chinese migrants in 1999 as a case study, this article aims to contribute theoretical understanding about the import of opinion discourse to the critical study of news, whilst offering a contribution to scholarship on the social construction of the Other.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.053 | 0.021 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".