Using parallel content analysis to measure mediatization of politics: The televised leaders’ debates in Canada, 1968–2008
Bibliographic record
Abstract
Owing to their focus solely on media content, most empirical studies on mediatization of politics fail to consider the dynamic relationship between politics and journalism, even though this relationship would provide ideal data for assessing the mediatization hypothesis. This study aims to measure the mediatization of politics using a research design that tracks parallel trends in political and media content over several decades, with televised Canadian leaders’ debates and their coverage by newspapers as a case study. Our specific hypotheses target the discursive style of journalists (factual, analytical, judgmental), agenda building (the range of areas of activity), and framing (strategic or governing). Our findings support the hypothesis which states that reports on leaders’ debates have become less factual as journalists have increased the share of analytical and judgmental styles in their stories. Also, use of the strategic frame in news stories has grown, and it has been incorporated by party leaders into their own discourse during debates. Evidence is mixed regarding the impact of mediatization on agenda building.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".