Research Design Tracking and Assessment for the Social Sciences

Marco Rovera; Sergiu Burlacu; Dominique Cappelletti; Alessio Tomelleri; Sonia Marzadro; Martina Bazzoli; Annalisa Tassi; Jessica Gagete-Miranda

arXiv · 2608.27049

Research Design Tracking and Assessment for the Social Sciences

Marco Rovera·Sergiu Burlacu·Dominique Cappelletti·Alessio Tomelleri·Sonia Marzadro·Martina Bazzoli·Annalisa Tassi·Jessica Gagete-Miranda

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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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Marco Rovera, Sergiu Burlacu, Dominique Cappelletti, Alessio Tomelleri, Sonia Marzadro, Martina Bazzoli, Annalisa Tassi, Jessica Gagete-Miranda. 2026-08-27. Research Design Tracking and Assessment for the Social Sciences. https://arxiv.org/abs/2608.27049

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