  Citations in science are being studied from several perspectives. On the one
hand, there are approaches such as scientometrics and the science of science,
which take a more quantitative perspective. In this chapter I briefly review
some of the literature on citations, citation distributions and models of
citations. These citations feature prominently in another part of the
literature which is dealing with research evaluation and the role of metrics
and indicators in that process. Here I briefly review part of the discussion in
research evaluation. This also touches on the subject of how citations relate
to peer review. Finally, I try to integrate the two literatures with the aim of
clarifying what I believe the two can learn from each other. The fundamental
problem in research evaluation is that research quality is unobservable. This
has consequences for conclusions that we can draw from quantitative studies of
citations and citation models. The term "indicators" is a relevant concept in
this context, which I try to clarify. Causality is important for properly
understanding indicators, especially when indicators are used in practice: when
we act on indicators, we enter causal territory. Even when an indicator might
have been valid, through its very use, the consequences of its use may
invalidate it. By combining citation models with proper causal reasoning and
acknowledging the fundamental problem about unobservable research quality, we
may hope to make progress.
