Political elite cues and attitude formation in post-conflict contexts
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
Abstract Civil conflicts typically end with negotiated settlements, but many settlements fail, often during the implementation stage when average citizens have increasing influence. Citizens sometimes evaluate peace agreements by voting on referendums or the negotiating leaders, and, almost always, they decide whether to cooperate. Yet, despite their role, we do not know much about how citizens form attitudes toward peace agreements. In this article, we assess how citizens form attitudes toward settlements, specifically the policy provisions that emerge from them, which are central in shaping the post-conflict context. These are complex policy changes, involving deeply factionalized actors, and the citizens evaluating them are often focused on rebuilding their lives. We therefore theorize that citizens use stark cues from political elites with whom they have affinity to form their attitudes. We test our theory using survey experiments in Colombia. We find that citizens rely on political elites’ cues to decide their stance on the settlement’s provisions. These cues appear to supply easily-accessible information that respondents use over other information. In contrast to work positing that peace agreements are exceptional and weary citizens are stabilizing forces, our results suggest that even these decisions are politics as usual, where divisions among political elites drive the outcome.
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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 | 0.005 | 0.002 |
| 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 | 0.000 |
| 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