A Model of Interest Group Influence and Campaign Advertising
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
We analyze a citizen–candidate model of elections between an incumbent and challenger to investigate the logic of interest group influence on election outcomes through campaign advertising. Whereas the incumbent’s position is known to voters, the challenger is relatively unknown, and groups may allocate spending (either directly through independent expenditures or indirectly through campaign donations) to advertise the challenger’s position. We prove that equilibria can feature either positive or negative advertising, but not both at the same time: ex ante evaluations of the challenger by the median voter determine which kind of advertising will arise. In a positive advertising equilibrium, only challengers located in a centrally located spending interval are advertised and win, while in a negative advertising equilibrium, challengers who are too extreme are targeted and lose. The analysis sheds light on the determinants of political advertising and voter beliefs, and it emphasizes their endogeneity with respect to the parameters of the model, e.g., the incumbent’s location, prior beliefs of voters about the challenger’s location, and the effectiveness of advertising technology. Moreover, it illuminates the preconditions for positive and negative advertising, and indicates circumstances in which one tactic is more likely to be employed than the other.
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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 | 0.001 | 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 | 0.002 |
| 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