Are We the Ones to Blame?: Ideological Polarization and Voter Choice
Bibliographic record
Abstract
Political polarization is the social process by which the ideas and values of a politically moderate majority are slowly replaced by an uncompromising political ideology. In the American context, the term ‘polarization’ is meant to conjure an image of Americans moving from the moderate center to the uncompromising ideologies of modern conservatism or liberalism. This study examined whether a group’s level of political polarization can be a reliable predictor for its voting patterns. To do so, a two-part questionnaire was disseminated to a sample of undergraduate students at the University of Southern Mississippi (USM). The first section determined if a participant possessed strong ideological convictions and the second part was a hypothetical election that had five political candidates running for a Congressional seat. Unbeknownst to the participant, however, each nominee represented a particular position on the political ideological spectrum. The survey results showed that the sample did not hold a polarizing stance on any of the political issues outlined in the first section and the two candidates that possessed strong ideological convictions received the least number of votes in the Congressional election. The survey data was run through SPSS software to create a political summary index that could rank survey takers on the degree of their ideological convictions. A difference in proportions test was then used to compare these rankings to the corresponding votes. The outcome showed that there is a statistically significant correlation between a group’s level of political polarization and its preferred voting choice.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".