Bibliographic record
Abstract
This paper investigates the determinants of political polarization, a phenomenon of increasing relevance in Western democracies. How much of polarization is driven by divergence in the ideologies of politicians? How much is instead the result of changes in the capacity of parties to control their members? We use detailed internal information on party discipline in the context of the U.S. Congress—whip count data for 1977–1986—to identify and structurally estimate an economic model of legislative activity in which agenda selection, party discipline, and member votes are endogenous. The model delivers estimates of the ideological preferences of politicians, the extent of party control, and allows us to assess the effects of polarization through agenda setting (i.e., which alternatives to a status quo are strategically pursued). We find that parties account for approximately 40% of the political polarization in legislative voting over this time period, a critical inflection point in U.S. polarization. We also show that, absent party control, historically significant economic policies would have not passed or lost substantial support. Counterfactual exercises establish that party control is highly relevant for the probability of success of a given bill and that polarization in ideological preferences is more consequential for policy selection, resulting in different bills being pursued.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".