1,721,252 research outputs found
University autonomy and structural constraints in the Italian system
No full textWe focus on two issues, which we believe
are at the core of the ability of the Italian system to compete in the near
future.
The first regards the relation between strategic autonomy and multiple
constraints imposed by the institutional system. We shall see how an
increasing tension is damaging the ability of universities to grow. The
second issue regards the management of academic resources, and the use
made by universities of the power to hire and promote professors. This is a
very interesting case of unexpected effects of a reform, and can give insights
into the complexity of institutional adaptation.
As in other chapters, we try to give a quantitative representation of these
effects, using data at national level
Indicators for the analysis of Higher Education Systems: some methodological reflections
No full textUntil now, what most researchers in HE have done is to choose between
aggregate data at national system level provided by statistical offices, or
detailed case-study data collected for single individual higher education
institutions (HEIs).
An important innovation of the Aquameth project has been the collection
of meso-level data – that is, data at the level of whole HEIs – on a part of the
European university system (six countries) in a systematic way, by applying
broad common definitions of data categories across countries and collecting
information already available at national level.
Nevertheless, the Aquameth database which per se represents a very
important result of the project has to be handled with care. It cannot be used
in a ‘data mining’ way, but its exploitation needs a profound understanding of the meaning of the contained data and of their limitations, due both to
conceptual problems and to the data collection procedures. This chapter
deals with these kinds of issues with two major aims: to serve as a guide for
those interested in further exploiting the database and to point out some
major improvements in data which are urgently needed
Universities as strategic knowledge creators. Some preliminary evidence
No full textwe propose
a quantitative approach to university strategy based on internationally
comparable microdata. Comparability issues are discussed at length in
Bonaccorsi, Daraio and Lepori (Chapter 12). This chapter offers a preliminary
sample of potential outcomes that can be derived from the available
Aquameth dataset on six European countries: Italy, Norway, Portugal,
Spain, Switzerland and the UK.While the presented evidence still requires
lot of refinements and qualitative comment, it provides a few quantitative
elements able to support public policy debates. we try to build up an operationalization of the
notion of university strategy capitalizing on the available data.We are able
to track the position and evolution of universities with respect to some
structural elements:
● research orientation, as measured by the share of PhD recipients over
the total population of undergraduate students;
● research intensity, as measured by the average number of publications
per unit of academic staff;
● offering profile, introducing a distinction between generalist and
specialist universities;
● rate of growth in total number of undergraduate students; and
● degree of autonomy, as measured by the ratio between nongovernment
funding sources and total funding.
This is a preliminary effort to identify relevant dimensions and to capture
emergent phenomena. We are very far from a complete characterization,
but the results are encouraging. A detailed descriptive evidence is reported,
while a tentative interpretation in the light of a theory of university strategy
is proposed. The final section discusses some policy implications
Theoretical perspectives on university strategy
No full textThe main purpose of this chapter is to set the theoretical stage for developing
the notion of university strategy using a quantitative approach.
The notion of strategy has been applied repeatedly to universities in the
literature, but the efforts for operationalizing it have so far been very
limited. As a result, many claims about the centrality of universities
as knowledge production and diffusion actors have a poor empirical
foundation.
As the chapter will show, developing an operational notion of strategy
requires a lot of conceptual and methodological clarification, if one wants
to build up reliable quantitative indicators.
We shall discuss some streams of literature that have addressed the issue
of strategy from various perspectives, namely institutional theory, political
science, the sociology of higher education, the economics of higher education
and of science, and public management. The purpose is clearly not one
of comprehensive survey, but rather of mapping the field of potential contributions,
mainly with a focus on appropriate interpretation in terms of
quantitative indicators at the micro level
Understanding scientific success: A macintyrean virtue ethics approach
No full textThe analysis of the success in science has been a
subject of interest and study for a long time.
“Success breeds success” or the so called Mattheu
effect, as it was named by Merton (1973), was used
to explain the cumulative effects observed in the
sociology of science, analysing nobel prize winners.
But what are the determinants of scientific success?
What makes a tiny proportion of scholars
successful? Why a few scholars rise far above the
rest, or using the terms of de Solla Price (1963, p.
59), why there are a “few giants and a mass of
pygmies” and “neither man nor nature pushes us
toward egalitarian uniformit
Assessing research and its impacts: The generalized implementation problem and a doubly-conditional performance evaluation model
No full textThis paper addresses the issue of designing relevant models of indicators to assess research and its impacts. The evaluation of research activities is a complex task for many reasons. There are no perfect indicators or metrics which fit for all purposes. In order to understand the appropriateness of the indicators to be used, we need to frame the problem taking into account the systemic nature of the phenomena and to develop models of metrics that are as close as possible to the reality being assessed. We show some examples of the usefulness of such a framework by discussing university rankings, the complexity of the assessment of research through the generalized implementation problem and presenting a doubly conditional performance evaluation model
Challenges, approaches and solutions in data integration for research and innovation
No full textIn order to be implemented by policy makers, science, technology, and innovation (science, technology, and innovation (STI)) policies and indicator building need data. Whenever we need data, we need a method for data management, and in the era of big data big data, a crucial role is played by data integration big dataintegration. Therefore, STI policies and indicator development need data integration. Two main approaches to data integration exist, namely procedural and declarative. In this chapter, we follow the latter approach and focus our attention on the ontology-based data integration (ontology-based dataintegration (OBDI)) paradigm. The main principles of OBDI are: (i)Leave the data where they are.(ii)Build a conceptual specification of the domain of interest (ontology), in terms of knowledge structures.(iii)Map such knowledge structures to concrete data sources.(iv)Express all services over the abstract representation.(v)Automatically translate knowledge services to data services. We introduce the main challenges of data integration for research and innovation (researchand innovation (R&I)) and show that reasoning over an ontology connected to data may be very helpful for the study of R&I. We also provide examples by using Sapientia, an ontology specifically defined for multidimensional research assessment
The organization of science. Size, age and turnover effect in the Italian National Research Council
No full textUsing normative ethics for building a good evaluation of research practices: towards the assessment of researcher’s virtues
Full text linkIn this paper, we propose the adoption of moral philosophy and in particular normative ethics, to clarify the concept of “good” evaluation of “research practices”. Using MacIntyre (1985)’s notion of a practice we argue that research is a form of social practice. As a result of this characterization, we claim that research practice typically requires three typologies of researcher: the leader, the good researcher and the honest researcher. Reflecting on what is a “good” research practice and on what is the role of researchers in it provides insight into some aspects of both the self-assessment process and how this promotes individual improvement. Moreover, this kind of reflection helps us to describe the functions (missions) of the research practices. A “good” evaluation should take into account all the building constituents of a “good” research practice and should be able to discriminate between good and bad research practices, while enforcing the functions of good research practices. We believe that these reflections may be the starting point for a paradigm shift in the evaluation of research practices which replaces an evaluation centred on products with an evaluation focused on the functions of these practices. In the last sections of the paper, we introduce and discuss an important aspect for the implementation of the proposed framework. This relates to the assessment of the virtues of researchers involved in a good research practice. Some examples of questions and preliminary items to include in a questionnaire for the assessment of Virtues in Research Practices are also provided
Age effects in the organisation of science. The case on the Italian National Research Council
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