The Perception of Political Advertising During an Election Campaign: A Measure of Cognitive and Emotional Effects
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Scientific interest in political ads has been growing in recent years and has fuelled an important body of research, focusing mostly on the United States. Yet many issues associated with the impacts and contents of electoral ads remain unexplored, especially within the Canadian context. This article investigates the immediate and simultaneous effects of positive, negative, and mixed-content electoral ads. It presents data drawn from a series of pre-tests of an experimental design carried out with 31 voters during the Canadian federal election of 2011. Participants viewed ads selected for their argumentative content and non-verbal components. The impacts of the ads were tested using an innovative multimethod approach combining physiological and cognitive measures. Among its contributions, this novel method helped generate a more nuanced and precise evaluation of the effects of negative advertising on viewers.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it