This paper proposes the establishment of a systematic framework for measuring dimensions of democracy within a university. It is shown that certain indicators internationally established and validated for the measurement of the institutional characteristics of democracy can, through appropriate adaptation, be transferred to the university field. A new model of mapping these characteristics to the university field was built using all available knowledge from international surveys, valid databases and researches conducted using questionnaires and structured interviews, specifically for the purposes of this paper. Chord diagrams, capable of providing meaningful dynamic graphical representations, were employed as a novel evaluative tool that highlights the existence and degree of significant interrelations between democracy indicators and democratic characteristics of the university. As a case study, we have chosen to analyze, compare and contrast the three most representative laws governing the operation of Greek universities for the last 35 years using the proposed model. Its operation, validity and capabilities were verified, after encapsulating the complex interdependencies among its variables, for a large time period, influenced by adverse social and economic changes. Thus, it can be used as an effective tool for comparisons among different universities, with respect to their democratic constitution.

The purpose of the proposed research is the application of suitable indicators, which measure the state of democracy, to the university field. Initially, an in-depth analysis of the features presented in six international organizations measuring democracy worldwide was performed. This revealed a sizeable set of significant and complementary indicators that constructed a conceptual framework for democratic institutions. Then, a model of the ‘democratic’ university was established with respect to its mission, operations and interactions, comprising a set of democratic characteristics. Interviews with academics from several European countries helped select those primary democracy indicators that can be best associated with the university characteristics. Interviews were analyzed using a Text Network Analysis algorithm, which represents texts as network graphs. Results show that monitoring these associations can reveal discrepancies and flaws that may degrade the university’s democratic operation and, also, helps to resolve conflicting demands when interacting with societal actors and the state. The size and variety of the examined datasets overcomes data bias, and the novelty of our approach lies in the fact that the graphical representations of the texts does not impose external semantic structures, thus avoiding subjectivity. This can have significant implications in assisting the complex policy formation processes within the university.