Methods Abstract

Selection

We analyzed abstracts instead of the full text of selected papers because the abstract typically is the first section of the paper viewed by readers; moreover, the abstract is the only section of the paper immediately available on databases such as PubMed [22]. Hence, abstracts provide a relatively consistent point of entry to scientific publications. To select focal abstracts for the dataset, we first used the PubMed database to select the journals that published the largest number of articles featuring the phrase “climate change” in the abstract or title between 2009 and 2010. Our reasoning for choosing the set of papers that we did was as follows: First, we limited the scope by the field of inquiry (climate change), hoping to minimize the statistical variance (or “noise”) that would probably have resulted from an analysis that included many fields (which in turn likely differ in citation frequencies and writing conventions, among other relevant factors). Next, we reasoned that it takes a number of years for papers to accrue a number of citations—and consequently for a set of papers to develop a distribution of citation counts—that would allow us to test our core hypothesis. We began this study in 2015, and chose 5-to-6 years as a reasonable window, allowing for citations to accrue, but not letting the papers become outdated. Finally, knowing that citations accrue to individual papers nonlinearly over time, we recognized the difficulty in using the available data (total citations, rather than citations-by-year for each paper) to derive time-correction factors for each paper in the dataset. Consequently, we featured only papers from a narrow time window, minimizing the effect of time-since-publication on the distribution of citations in our dataset.

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