Can Canadians Take a Hint? The (In)Effectiveness of Party Labels as Information Shortcuts in Canada
Bibliographic record
Abstract
Abstract.This paper examines the usefulness of Canadian political party labels as information shortcuts. We supplement survey data analysis with the results of an experiment that tested whether knowing a party's position on an issue influenced opinion expression. We find that, contrary to findings in other countries, among our subject pool, Canadian political parties are not consistently useful as information cues. The Liberal party cue is hardly useful, and while the Conservative party cue can be effective, it appears to push partisans toward a more liberal stance on selected opinions. Only the NDP cue appears to influence opinions in the expected direction. These mixed findings run counter to foundational works on party labels as information shortcuts (mostly focused on US politics) and, instead, are consistent with previous scholarship on Canadian politics. Résumé.Cet article examine l'utilité des étiquettes politiques des partis canadiens comme sources d'information sommaire. Nous analysons des données d'enquête ainsi que les résultats d'un sondage visant à déterminer si le fait de connaître la position d'un parti sur une question donnée influençait l'expression des opinions. Contrairement aux résultats obtenus dans d'autres pays, nous constatons chez les sujets observés que les étiquettes des partis politiques canadiens ne sont pas uniformément utiles comme sources d'information sommaire. L'étiquette du Parti libéral s'avère à peine utile, tandis que l'étiquette du Parti conservateur, peut-être plus efficace, semble inciter les partisans à une position plus libérale. Seule l'étiquette du NPD semble influencer les avis dans la direction prévue. Ces conclusions mixtes contredisent des travaux fondamentaux sur le même sujet (portant pour la plupart sur la politique aux États-Unis) et confirment plutôt les études antérieures sur la politique canadienne.
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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 | 0.008 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".