Translating the epidemic of fear-based rhetoric in Canadian press: A case study and framework
Bibliographic record
Abstract
News, as we know, saturates our lives: from the morning newspaper to televised late-night reports there is no denying the influence and impact media can have on our daily lives. In the context of a post September the 11th world, one of the dominant trends in press media is the use of fear-based rhetoric. This research paper is concerned with how the Canadian press media constructs fear, particularly the fear of disease, and how this fear is further disseminated through translation. As well, it explores some of the dominant discourses concerning translation in the press and in general. The main hypothesis is that translation acts as a space of contagion with the power to disseminate certain emotions that develop in response to current events. Observations include a case study of French and English-Canadian press articles on the avian flu and the discursive strategies used to convey fear of the disease, as well as a potential framework for translators of the press.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".