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Commentary: Four ways in which data-free papers on animal personality fail to be impactful. In a recent Frontiers in Ecology and Evolution paper, DiRienzo and Montiglio (2015) suggest that " the literature on animal personality is dominated by papers lacking any data " and that additional data-free papers do little to move the field forward. Here, we present our quantitative analysis of data-free papers in the animal personality and behavioral ecology literature, as well as discuss the value of such articles. We found that data-free papers composed 20% of all publications on animal personalities in the last decade. We further determined the prevalence of data-free papers within the top-ten most cited papers in other behavioral ecology fields, showing that animal personality did not have an unusual excess of highly cited data-free papers when compared to other subfields of animal behavior. Regarding the impact of data-free papers, we argue that impactful data-free papers provide coherent syntheses and reviews of current knowledge, integrate different fields of thought in novel ways, or identify important future directions within a framework beyond the scope typical of empirical papers. Ultimately, we suggest that a combination of robust empirical studies and effectual data-free papers is vital to advance a field. To quantify the frequency of data-free papers in the animal personality literature, we conducted a web search using Web of Science (BIOSIS Previews). Specifically, we used the search terms " behavio * syndrome * " OR " animal personalit * " for the period 2005–2014, which follows Sih et al.'s influential papers in 2004 (Sih et al., 2004a,b). Our search differed from DiRienzo and Montiglio's (" individual behavioral variation ") because we felt that ours more accurately assessed the overall animal personality literature; however, searches using any combination of these terms yielded the same conclusions. By reading the title and abstract for each paper, we determined whether it contained data. We classified data-free papers into sub-categories: literature reviews, hypothetical ideas/concepts, and general methods. Maintaining consistency with DiRienzo and Montiglio's definition of data-free, all statistical methods, meta-analyses, simulations, or mathematical modeling papers were not considered data-free as they generate quantitative analyses. We excluded papers not explicitly related to behavioral ecology and animal personality (e.g., human studies). We obtained 473 papers, of which 20% were data-free. Of these data-free papers, 70% were literature reviews, and 19% were hypothetical ideas/conceptual papers. Many of these reviews and idea papers sought to: …