(Pix (c) Larry Catá Backer 2015)
These are meant to serve a useful purpose--as an important contribution to informational transparency. This transparency, in turn is meant to paint a picture of the state of faculty earning that can be used, as an authoritative data set, to further positions and negotiating strategies, of university administrators, faculty, legislators and the like. It is also a valuable mechanism for managing public opinion about the state of the university and the privilege (or lack thereof) of a key university stakeholder.
All of this is well and good, and fair game, in the context of the politics of university administration, public policy development, and the operation of wage labor markets for university faculty labor talent. Yet, data is a relational as well as an objective measure. For policymakers, and especially for engagement, the choice of relational elements--the way data is packaged and the choice of data types to place in relationship to each other--will have a profound impact on the way on which the data is read and understood. More importantly, if done with some calculation, the careful presentation of relationships among data (including some excluding others) can be used to manage conclusions as well. This no doubt is usually inadvertent, but perhaps not always so.
This semiotic insight is both powerful and so deeply embedded in our
culture that it tends to go unnoticed. This post considers how the way
in which these relational markers work affect the presentation and
utility of faculty salary surveys. It also suggests the ways in which they might be managed and exploited.