Perceptions of Electoral Integrity (PEI) Survey for the 2016 U.S. Election
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Description
The Perceptions of Electoral Integrity (PEI) dataset provides expert evaluations of elections based on 49 indicators grouped into 11 categories reflecting the entire electoral cycle. It was created by Pippa Norris, Alessandro Nai, and Max Grmping for Harvard University's Electoral Integrity Project. The dataset includes disaggregated scores for individual indicators, summary indices for dimensions of electoral integrity, and an overall PEI index score out of 100.
Use Cases
Benchmarking electoral integrity based on expert perceptions of 49 indicators.
Analyzing the relationship between different stages of the electoral cycle based on the 11 categorical indices.
Modeling the drivers of overall electoral integrity using the composite PEI index score.
Comparing expert evaluations of the 2016 U.S. election against other elections in the PEI series.
Strengths
Based on a structured expert survey covering 49 specific indicators.
Provides a composite index score and disaggregated scores across 11 dimensions of the electoral cycle.
Created by researchers affiliated with Harvard University's Electoral Integrity Project.
Limitations
Row count and sample size are unknown, limiting suitability assessment.
Column-level documentation is absent; field semantics must be inferred after download.
Last update date is unknown; freshness unverified.
Provenance
Source
Harvard University's Electoral Integrity Project.
Collection Method
Expert survey (Perceptions of Electoral Integrity - PEI).