Issue Attributes and Agenda-Setting by Media, the Public, and Policymakers in Canada
Bibliographic record
Abstract
Agenda‐setting hypotheses inform research on both media influence and policy making. The study draws from these two literatures, building a more accurate and comprehensive model of the expanded agenda‐setting process. Evidence is derived from a longitudinal dataset, including a content analysis of Canadian newspapers, results from public opinion polls, and measures of attention to issues in Question Period, committees, Throne Speeches, and legislative initiatives from 1985 to 1995. A model is estimated that accommodates dynamic, multi‐directional effects. Findings are presented for three issues—inflation, environment, and debt/deficit—with an eye on examining different agenda‐setting dynamics, and the degree to which these dynamics are linked to issue attributes. The results (1) demonstrate the value of an agenda‐setting framework and a means of modelling media effects and the policy making process, and (2) indicate the importance of taking issue attributes into account in predicting or accounting for agenda‐setting effects.
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".