Phony Populism: The Misuse of Opinion Polls in the <i>National Post</i>
Bibliographic record
Abstract
This paper describes how the National Post regularly excludes polling details that are essential to an accurate reading of the data. It then looks at how business and labour issues are covered in the paper and shows that opinion polls are manipulated to confer popular legitimacy upon the economic conservatism of the Post’s editors. It concludes by arguing that while polls may be presented as a form of direct democracy, they are more aptly regarded as promoting a phony populism: the use of popular idioms to mask an elite project. Although opinion-poll results are presented as the unfiltered expressions of popular sentiment, they are in fact regularly manipulated by media outlets. I find that rather than giving voice to the general population, polls in the National Post are routinely used to “manufacture consent” for the viewpoints of the corporate and political elite, while misrepresenting popular opinion.
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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 | 0.074 | 0.201 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".