🔎 The Problem:
Scholarship on human rights norms shows persistent inconsistencies across competing interpretations of how norms diffuse and what effects they have. Part of this problem stems from treating observed behaviors as direct evidence of a single norm without examining the internal structure of those norms or how that structure should shape data collection—especially in quantitative work.
🧭 A Different Measurement Focus:
Contemporary international norms are argued to have a tripartite structure. Accurate quantitative study therefore requires collecting data on all three components of that structure so the object of study is correctly identified rather than conflated with related phenomena.
🛠️ Practical Fix: Add Value Statements to Existing Datasets:
Adding explicit value statements to coded cases provides a method for validating whether recorded behaviors truly express the target norm. This validation helps correct two distinct kinds of overcounting:
- Behaviors that actually correspond to other norms
- Behaviors that are not normative expressions at all
📌 Demonstration — Transitional Justice Norms:
The approach is illustrated using the set of norms known collectively as transitional justice, showing how augmenting datasets with value statements changes which behaviors count as expressions of the focal norms.
🔬 Why It Matters:
Improving measurement in this way reduces ambiguity about what is being counted and strengthens causal inference in quantitative studies of international norms. Better-aligned data collection makes findings about diffusion and effect more reliable and comparable across studies.
