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Introduction
PE in the context of research and innovation
Demands on science are increasing constantly.1 Global social challenges call for fast solutions based on a science capable of integrating different disciplines and research communities, and to dialogue with government, industry and civil society. Science is required to be more transparent and accountable, more communicative and inclusive, more ethically oriented and socially committed. At the same time, the authority and unity of science are becoming weaker, and peopleâs trust in science is decreasing, while paradoxically their expectations about the capacity of science to have large social and economic impacts are increasing.
A âsuperman modelâ of science is emerging. Science is asked to do more, faster and better, often with fewer resources, less time and less institutional support. This is leading to higher levels of competition between research institutions and researchers in order to publish, access funds, attract talent and raise reputation. All these challenges are altering research institutions in their culture, procedures, decision processes and organisational structures. In many cases, these changes are not planned or oriented through policies and measures, but are simply borne by researchers and managers. Many factors make it difficult for research institutions to manage such developments, including internal resistance to change, lack of awareness about the benefits and costs involved, overwhelming demands for responsiveness to societal needs, insufficient skills and knowledge about effective societal engagement, paucity of funding and resources, or absence of a national policy environment supporting change (e.g. Maassen, 2017; Shoemaker, 2011; Regenberg, 2010; Hessels et al., 2009).
The question is therefore whether these changes will finally result in a drift, a largely ungoverned and uncoordinated set of processes, or in a transition, a shift from one state to another, managed and driven, as far as possible, through specific measures, institutional strategies, science policies and cultural inputs.
Public participation is loaded with high expectations in this context. Beyond specific definitions, it can be understood as being a general approach aimed at getting different actors, cultures, interests and knowledge to interact to identify and attain common objectives in terms of governance of research institutions and development of the research process. Public participation is not the unique possible approach, nor can it be applied alone, but it is one of the more relevant and consolidated approaches. Particularly in the context of the European Union (EU), public participation has been established as one of six main pillars of an emerging policy framework for the EUâs research activities â the Responsible Research and Innovation (RRI) approach â which, combining various objectives and aspects of the so-called science-society relations, including open access, gender, ethics, science education and governance, is trying to increase the alignment of science with the values, needs and expectations of society. Public engagement (PE) is mostly used interchangeably with public participation, a term that is perhaps more globally known. However, since âpublic engagementâ is the term adopted by the European Commission (n.d.a), several European research institutions, as well as the research team behind the project underlying this study, we have also adopted it as the core concept of this volume.
In the last three decades, PE has developed intensively, stimulated by the actions of some national governments and European institutions, mainly under the pressure of an increasingly wide movement â involving researchers, NGOs, and many other stakeholders â engaged to promote more advanced and democratic forms of governance of science and technology. Many facts provide evidence of this trend, including the increasing number of PE experiences in Europe and in other regions of the world; the wide diversification and specialisation of PE tools (for example, 76 different PE mechanisms applied in 256 PE processes were identified by Mejlgaard and Ravn, 2015); the shaping and consolidation of an increasingly wide community of practitioners and experts on PE approaches and techniques; and the increasing interests of researchers on PE, as shown by the growing number of papers, articles and scientific meetings devoted to it. Even though it is well-known that the field of PE is developing fast, it is less clear where the development is leading. Where is the cutting edge of this development? In order to address these issues, an analysis of the trends and characteristics of innovative PE is one of the three main tasks of this volume.
Despite active development of PE, its diffusion and impact on science has remained limited, for many reasons. The reform of formal institutions of research are out of phase with rapidly changing science in society. Often PE is merely used as a sophisticated form of science communication, not as a permanent component of science governance. Its diffusion is also limited, since â apart from a few countries â in the great majority of European member states, PE is only occasionally applied by research organisations, and national strategies in this field are still weak or missing altogether. PE practices are often not organically connected to the research organisationâs policy cycle and research processes. The risk involved with these tendencies is that they can feed disappointment and dissatisfaction with PE, at least as a potential governance tool. In order to address the potential mismatch between high expectations and reality, and support a healthy development in this field, this volume has set the study of the different performative functions of innovative PE as the second of its three main tasks. In particular, we will show how innovative PE processes have contributed to a more dynamic and responsible governance of research and innovation. These concepts (to be fully defined later) refer to the ability of policy making to handle issues effectively in a rapidly changing environment requiring continuous adjustment and dynamic interaction between multiple stakeholders, including society at large.
The third main task of this volume is to develop a synthetic model for evaluating the impacts and benefits of PE. As PE activity is becoming commonplace, and public money is increasingly being spent on it, it is critical to evaluate the appropriateness, efficiency and impacts of such investments. We will argue that an up-to-date PE evaluation framework should acknowledge not only the classic evaluation criteria just mentioned, but also take into account the multiple functions of PE, and in particular, its potential roles as a tool for dynamic and responsible governance of research and innovation. In other words, PE can result in new governance capacities, and it can induce important systemic functions that should be acknowledged in any serious evaluation of PE activities. A reader interested in relevant evaluation approaches and criteria should find the synthetic PE evaluation model particularly informative, since many of the existing models have been partial at best.
1.1 Evolution of science in society
Public engagement with science has been enjoying unprecedented development in recent decades. It has become a recurrent issue in the public debate on research and innovation. In some national contexts, specific policies aimed at stimulating PE initiatives have been devised. Over time, a wide scientific literature has developed, addressing PE from a range of perspectives.
To grasp the actual and potential role of PE today, it is necessary to widen the interpretive framework to encompass some broader sociological perspectives: How has the relationship between science and society changed in recent decades? How has the governance of science in society changed respectively? What types of PE paradigm can be discerned?
From a sociological perspective, the changes affecting science are part of a wider array of transformations touching contemporary societies as a whole. Usually such transformations are represented as a shift from modern society to a new society, to which many names have been given, including, for example, âpost-industrial societyâ (Bell, 1974), âinformation societyâ, âknowledge societyâ, ârisk societyâ (Beck, 1992), âreflexive modernityâ (Giddens, 1991), âliquid societyâ (Baumann, 2000), ânetwork societyâ (Castells, 2000), âpost-modern societyâ (e.g. Lyotard, 1984), and âhigh-speed societyâ (Rosa, 2013). Most of these models concern the changing relationship between social structures and individual actors. In the context of modern society, social structures (e.g. social norms, behavioural models, social roles and values) and the institutions of modernity supporting and reproducing them (e.g. political institutions, religious institutions, economic institutions, trade unions and public administrations) were strong enough to exert a certain control over individuals and groups (in terms of behaviours, expectations, cultural orientations, worldviews and so forth). Now â under the pressure of a range of factors â such structures and institutions are weakening while the autonomy of individuals (e.g. to make their own choice, to shape their own identity, to develop their own worldview) and the groups they are part of is increasing. These complex dynamics are resulting in accelerated transformations of the society, the impacts of which to science-society relations are difficult to anticipate (see, e.g. Bijker and dâAndrea, 2009).
Various theoretical models have been developed to capture the many changes affecting scientific production. These include, among others, the âMode1/Mode2â (Gibbons et al., 1994; Nowotny et al., 2003), âPost-Academic Scienceâ (Ziman, 1996), âPost-Normal Scienceâ (Funtowicz and Ravetz, 2003), âTriple Helixâ (Leydesdorff and Etzkowitz, 1998), âQuadruple Helixâ (Carayannis and Campbell, 2009) and âScientific Agencyâ (Miah, 2017) models that allow shedding light on some of the main trends of change affecting science as a social institution. To provide an overview, ten common trends emerging from these models are summarised below.
Diffusion of cooperative practices in scientific production
Research is increasingly a collective enterprise made up of programmes involving the coordination of an increasing number of scientists and research institutions. This is also due to the fact that in some areas of research costly and sophisticated equipment are increasingly required, which cannot be provided by single research institutions, and where their use is more efficient and economic, when shared among institutions. Moreover, interaction among research institutions is practically unconstrained, for example thanks to ICTs. Knowledge production is therefore lesser and lesser made within hierarchically organised academic institutions but more and more through horizontal research networks.
Contextualisation
Research is increasingly âcontext-drivenâ, in other words, carried out in a context of application, arising from the very work of problem solving and not only governed by the paradigms of traditional disciplines. Consequently, research tends to be âproblem-focusedâ: it is no longer initiated only by the interest of the scientist, but it is aimed at coping with specific problems or seizing a given opportunity.
Socially diffused research
There is a much greater diversity of the sites at which knowledge is produced as well as of the types of knowledge produced. The university is no longer the unique environment for research production.
Transdisciplinarity
Research is increasingly transdisciplinary in nature, while in the past it was carried out narrowly in specific disciplinary domains. Another aspect of the same process is that relationships between universities, governments and industries are increasingly closer and coordinated. This results in the creation of âhybridâ structures and institutions, such as academic spin-offs, high-tech incubators, and science and technology parks.
Quality control enlargement
Quality control systems are changing, involving actors other than peers (for example, knowledge brokers, final users, citizens) and applying multiple assessment criteria.
Accountability
There is an increasing need to make science accountable to a wide range of actors, with effects such as the proliferation of evaluation exercises and modification of research procedures (for example, disaggregation of transdisciplinary research in order to allow disciplinary-based evaluation).
Utilitarianism
Research results are often expected to have economic impacts. This does not only mean favouring applied research but adopting the potential economic impact as a parameter for assessing any kind...
