The Simplest Shortcut of All: Sociodemographic Characteristics and Electoral Choice
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
Voters' decision criterion of last resort is their similarity to candidates or party leaders. Most normative theories would denigrate this form of reasoning. But the recent argument that voters can make up for information shortfalls by employing heuristics seems to require that the most poorly informed respond to these characteristics if they are to make anything other than a random decision. In this article I test the hypothesis that increasing dissimilarity of sociodemographic characteristics from a political figure (e.g., party leader) decreases a voter's expected utility from the election of that person. Secondarily, I ask whether decreases in a voter's store of policy information will necessitate greater reliance-a tendency to "fall back"-on this similarity/dissimilarity criterion. I draw on survey data from two Canadian federal elections with adequate variation in party leader characteristics. A model of vote choice is estimated by conditional logit. All voters are found to respond negatively to increasing sociodemographic distance from party leaders, net of partisanship, economic retrospections, policy, and uncertainty. Voters equipped for policy voting do not ignore these characteristics, and voters without policy information do not respond more strongly to their similarity or dissimilarity to party leaders.
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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 | 0.001 |
| 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 | 0.001 |
| 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