The Mediated Horserace: Campaign Polls and Poll Reporting
Bibliographic record
Abstract
Abstract. Although “horserace journalism” is thought to be central to contemporary election news coverage and has generated a great deal of criticism, there is no general model of the nature and dynamics of horserace journalism or “poll reporting.” This paper proposes and empirically evaluates such a model. The model builds on and extends John Zaller's “theory of media politics” to consider specifically what citizens demand from polls and what journalists supply. Aside from the generic motivations of politicians, citizens and journalists, the model emphasizes the unique features of polls as objects of news coverage. The paper finds considerable support for the model in an analysis of newspaper coverage of horserace polls (that is, vote intention polls) in the Canadian general election of 2006. Our findings from this one case have potentially broad implications for our understanding of the relationship between polls and electoral democracy both empirically and normatively. Résumé. Même si le journalisme de course (“horserace journalism”) est vu comme étant une composante centrale de la couverture électorale et qu'il a généré sa part de critiques, il n'existe pas de modèle général de la nature et de la dynamique de ce type de journalisme. Cet article propose, et évalue empiriquement, un tel modèle. Prenant comme point de départ la « Theory of Media Politics » de John Zaller, ce modèle considère plus spécifiquement ce que les citoyens demandent des sondages et ce que les journalistes leurs procurent. Au-delà des motivations génériques des politiciens, citoyens et journalistes, le modèle met l'accent sur les caractéristiques uniques des sondages en tant qu'objet de couverture journalistique. L'article présente des résultats supportant considérablement le modèle à travers une analyse de la couverture des sondages par les journaux (c'est-à-dire des sondages sur les intentions de vote) durant l'élection générale canadienne de 2006. Nos résultats émanant de ce cas ont potentiellement des implications beaucoup plus grandes pour notre compréhension de la relation entre les sondages et la démocratie électorale, à la fois sur le plan empirique et sur le plan normatif.
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How this classification was reachedexpand
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 | 0.005 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".