
This Element will overview research using models to understand scientific practice. Models are useful for reasoning about groups and processes that are complicated and distributed across time and space, i.e., those that are difficult to study using empirical methods alone. Science fits this picture. For this reason, it is no surprise that researchers have turned to models over the last few decades to study various features of science. The different sections of the element are mostly organized around different modeling approaches. The models described in this element sometimes yield take-aways that are straightforward, and at other times more nuanced. The Element ultimately argues that while these models are epistemically useful, the best way to employ most of them to understand and improve science is in combination with empirical methods and other sorts of theorizing.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 12 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
