Research Design Tracking and Assessment for the Social Sciences

• URL: http://arxiv.org/abs/2608.27049v1
• Date: Thu, 27 Aug 2026 12:36:17 GMT
• Title: Research Design Tracking and Assessment for the Social Sciences
• Abstract summary: We introduce Automated Research Design Tracking and Assessment (ARDTrA), a task that involves detecting the research design used in a paper and assessing the quality of its application.<n>We create an expert-annotated dataset of papers covering six families of counterfactual research designs and evaluate the task using a multi-turn RAG-based conversational pipeline.
• Score: 0.18058404137575482
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Reliable assessment of causal research designs in the social sciences is critical for evidence-based policy-making, yet has so far relied entirely on manual expert analysis. We introduce Automated Research Design Tracking and Assessment (ARDTrA), a task that involves detecting the research design used in a paper and assessing the quality of its application. We create an expert-annotated dataset of papers covering six families of counterfactual research designs and evaluate the task using a multi-turn RAG-based conversational pipeline. Across four retrieval strategies, four LLMs and six embedding models, we find that passage length is the main driver of performance, explaining 52-66% of the variance. A per-research-design analysis also shows that human and machine difficulty do not align: the designs that prove hardest for the system are not those on which expert annotators disagree most, pointing to two independent sources of task difficulty.

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