Problem: Ensuring Protocols in In-Person Surveys

Large, in-person public opinion surveys face a persistent challenge: getting enumerators to follow fieldwork protocols. Quality control procedures—like audio capture and geo-tracking—can boost data quality and protect the representativeness of the final sample, but little research compares which tools matter most.

📊 What Was Tested: AmericasBarometer 2016/17

Data come from the 2016/17 wave of the AmericasBarometer study. The evaluation used a large classification task to test whether a limited set of routine indicators can identify the same final set of interviews produced when a full suite of quality control procedures is applied.

Key features of the test:

• Focus on variables that are both automated and human-coded and that are commonly available across popular survey platforms
• Comparison between a small subset of indicators and the outcome of a comprehensive quality-control protocol
• Use of classification techniques to evaluate how well the smaller set recovers the final sample

🔎 Key Findings

• A compact set of automated and human-coded variables can recover the final sample of interviews that results when a full suite of quality control procedures is implemented.
• These variables are widely available across popular survey platforms, suggesting practical adoptability.
• Implementing and automating only a few procedures can both streamline quality-control workflows and substantially improve data quality.

⚖️ Why It Matters

• Practical implication: Survey teams can achieve most of the benefits of extensive quality control with far fewer measures, lowering operational costs and complexity.
• Methodological implication: Prioritizing a small, automatable set of indicators offers a replicable approach for improving representativeness and data integrity in large, face-to-face public opinion surveys.