Bibliographic record
Abstract
This study examines publicly voiced resistance by a Canada-wide community of scientists and citizen supporters against what they perceived as the Canadian government's efforts to undermine publicly supported science, with its concern for empirical evidence, in order to facilitate a narrowly pro-industry orientation in its policy-making. Using Hajer's argumentative discourse analysis (ADA) to interpret a corpus of some 700 Web-published texts, the author identified a macro-argument collectively produced and publicly communicated by the Canadian scientific community. The study also showed how this macro-argument served as a vehicle for two ideological representations: a virtuous self-representation of the scientific community itself and a negative representation of the motives and actions of the Canadian government. The findings of the research contribute to our understanding of how collective argumentative positions emerge within the discourse of a major scientific controversy. At the same time, the study offers policymakers insights in how they might communicate more effectively with communities of scientific experts.
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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 | 0.069 | 0.177 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.021 |
| Science and technology studies | 0.059 | 0.062 |
| Scholarly communication | 0.044 | 0.013 |
| Open science | 0.006 | 0.013 |
| Research integrity | 0.013 | 0.015 |
| 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".