Citizen science
Participatory knowledge production modes that allow the integration of perspectives and forms of knowledge can help better understand our complex socio-environmental systems (Alvarado et al., 2020). Several studies have shown that society can meaningfully engage in discussions about science and technology, and that this win-win interaction can contribute to strengthening democracies and decision-making (Reen et al., 2003; Marzuki, 2015). The current global challenges, such as the COVID-19 pandemic, demand thoughtful responses and solutions that cannot be managed with a scientific approach alone. As a result, public participation and societal engagement initiatives through so called ‘quintipule helix’ have gained wider political, institutional and public attention increasingly broad. These actions have been focal points of the Framework Programmes in the European Commission (FP7 Science in Society and Horizon 2020 SwafS programmes). In the Canadian framework, Canada’s Citizen Science Portal of the Government or the different initiatives in Universities (e.g. University of Guelph, Université Laval, Simon Fraser University, University of Waterloo) or organizations such as Community-based research Canadian organization or the Institute for Knowledge Mobilization are examples of this interest. The term citizen science (hereafter CS) is related to the general public engagement in the scientific knowledge production in which the citizens participate in different ways (e.g. intellectual, knowledge, tools or resources). The main aim is to co-create a new scientific culture and exchange of understanding (Silverstown, 2009) able to improve upon the interaction between science and society. CS is a rapidly expanding field in open science and open innovation (Hecker et al., 2018), which is linked with the democratization of science, scientific literacy, social capital, citizen inclusion in local issues, and benefits to government. The origin of the term can be traced to Irwin who defined it as a ‘form of science developed and enacted by citizens themselves’ (Irwin, 1995). Later, many other definitions arise (see Haklay 2013; Kullenberg & Kasperowski, 2016). A more recent definition stated that is ‘general public engagement in scientific research activities where citizens actively contribute to science either with their intellectual effort, or surrounding knowledge, or their tools and resource’ (European Commission, 2013). In terms of implementation of those methodologies, Living Labs are spaces where collaborative projects applying citizen science methodologies can take place. This concept was firstly introduced by Prof. Mitchell of the Massachusetts Institute of Technology (Schuurman et al., 2011) and refers to user-centred, open innovation ecosystems based on co-creation approaches, integrating research and innovation processes in real life communities and settings (European Network of Living Labs ENoLL, 2021). At the universities, they can connect education, research, and innovation with local issues through the design of specific activities that require the involvement of citizens. In the Canadian framework, there are different initiatives at the universities such as Concordia University . One of the main unknowns with CS initiatives’ (and by extension, in the Living Labs) is the level and nature of the citizens’ involvement in the research process with a wide variety of methodologies (e.g., action research, community-based participatory research). The tasks in which the citizens can be involved are diverse and can range from data collection and tagging images to participation in the planning and design. For measuring this contribution, different participation scales have been proposed. The eight levels of Arnstein’s (1969) ‘ladder of citizen participation’ was the first and goes from ‘non-participation’ to ‘citizen power’. More recently, Haklay (2013) classified it into four levels, showing an evolution from data collectors to the full involvement of volunteers. It implies also a fundamental shift from top-down approaches to bottom-up where volunteers and scientists interact. From a bibliometric perspective, some studies analyzed the CS research output (Kullenberg & Kasperowski, 2016; Bautista-Puig et al., 2019; Pelacho et al., 2020) but to the best of our knowledge, none analyzed the level of participation of the citizens within the research. Research questions and overall objectives Despite ongoing research on the topic, there remain gaps in our understanding of the nature and extent of the citizens’ contributions to CS projects and the contribution of those projects to the advancement of knowledge. This project aims to gain a better understanding of the nature and outcomes of CS projects and also to test a real case study with the Living Lab by answering the following research questions: How are CS projects distributed across fields? What is the nature and degree of citizen involvement in these CS projects? What kind of knowledge is produced from these projects and how does it relate to non-CS research in the same discipline? Could a living lab structure identify and solve societal issues?
The role of journals in structuring knowledge
Since they first appeared in 1665, scholarly journals have grown to be the dominant mode of dissemination of research outputs (Csiszar, 2018). The first journals were generalists and covered all areas of science, but the growing number of increasingly specialized researchers led to a segmentation process and the creation of new disciplines and specialized journals (Gingras, 2013). This specialization is usually made explicit by the declared scope of a journal. The scope of a journal signals to the potential users (within and beyond academia) where to look for knowledge that may be valuable to them, which highlights the crucial role of journals in ensuring that knowledge can be found and mobilized in further research, policies, and innovations. The fundamental role academic research is to advance knowledge, the fundamental role of journals is to disseminate it, and the fundamental role of the journal scope is to structure knowledge to optimize its dissemination. The proposed research addresses the potential erosion of these functions of journals brought about by the political economy of knowledge dissemination in which the interests of individual agents participating in the field (Bourdieu, 1999, 2001) may not align with the ideals (Armstrong, 2010) and where the question “how well does this paper fit the scope of the journal?” potentially becomes secondary. What happens to the scope of journals when they are increasingly owned by corporation (Larivière et al., 2015) whose fundamental role is the generation of profit? When publishers (commercial or not) use pay-to-publish business models in which revenues are coupled with the number of papers they publish? When editors’ focus on increasing the Impact Factor of their journal? Or when researchers are pressured to publish or perish? When the journal’s Impact Factor is more important for researchers than the fit of the work for the journal? The project has three main objectives: Use natural language processing and text-mining to measure the scope of all journals in the Web of Science and the fit of all papers in the journals where they are published (Mongeon et al., 2019). Investigate the relationship between the journal scope and other journal characteristics o the journals (business model, ownership, impact factor, etc.) Model the relationship between the fit of a paper in a journal and the impact of that paper on research, policy and technology to test the hypothesis that publishing papers where they best fit increases their likelihood of being found and used. Note: the project is currently recruiting students interested in writing a grant supported Master or PhD thesis as part of this project.