Deepanshu Malhotra's Preliminary Exam

Abstract: Author contributor statements assign credit, rights, and responsibilities, and reflect the distribution of labor to produce papers, and as such, have the potential to enable equity and accountability in collaborative research teams. This dissertation proposal is centered around three interconnected research studies that collectively investigate the division of labor in biomedical research teams. The first study aims to explain the distribution of labor based on author and paper-level characteristics in a large-scale bibliometric dataset with disambiguated author names. First, I built a predictive statistical model for each of the 14 Contributor Role Taxonomy (CRediT) roles, including explanatory features such as author age, ethnicity, gender, discipline, byline position, and team size. The model measures the relative importance and resolves the confounding effects of the explanatory variables. The second study explores the robustness and generalizability of the statistical models. While the first study establishes which author and paper-level characteristics most strongly predict the assignment of contributor roles, the second study advances this work by conducting exploratory analysis, re-estimating models using different subsets of variables, and extending the data to incorporate journals that include free-text author contribution statements. The third study expands the statistical model by including a new set of explanatory variables based on the co-authorship and citation networks. I hypothesize that the social position of a researcher (in the research community) and the article's impact play important roles in determining their contribution in a research team. The findings and the data of this research work should help contribute to the science of science and policy broadly and help individual scientists and research teams in decision-making.

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