This project aims to analyse under which conditions open and collaborative scientific networks have the ability to cooperate in the effective use of the knowledge produced to attend specific social problems.
The definition of a social problem normally entails certain “legitimate,” “natural,” or “rational” solutions, and exclude others which are not. When the definition of a problem is complex or too extensive, scientists can become enrolled in order to vindicate a certain orientation in the definition of the problem and to exclude or downplay the others (Kreimer, 2011). In recent years, the traditional circumstances of worldwide knowledge production have been dramatically modified. Globalization processes taking place in science—together with the formation of larger research networks—generate, at once, risks and opportunities in peripheral regions. On the one hand, research capacities in peripheral contexts may be empowered by the formation of South-South networks. These new collaboration patterns for the south allow research in peripheral societies to do away without the direct intervention of hegemonic research centres, whose perception of social needs and demands in southern contexts is absent or distorted.
Risks, on the other hand, may still arise through a series of processes that we identified as cognitive exploitation. This concept entails a relationship by which certain knowledge outputs, originally generated from non-profit objectives, become ultimately appropriated and turned into a source of profit by a different set of stakeholders (Kreimer & Zukerfeld, 2014). In this way, open and collaborative science is particularly prone to the risks of cognitive exploitation.
The central research questions are:
- Under what conditions open collaboration networks can contribute to an effective use of knowledge in peripheral societies?
- Which consequences are associated to more or less open networks?
- What is the specific role of the technical organization of open research collaboration?
Qualitative and quantitative techniques have been used including “following the actors” (following the research groups at the different loci of knowledge production) to conduct in-depth interviews to assess motivations, facilitators, and constraints; and bibliometric tools to track the evolution of the fields (dynamics), finding shared actors that appear in consecutive periods. Whereas traditional bibliometric analysis has chiefly relied on co-citation analysis, we are working with new resources such as bibliographic and heterogeneous coupling methods that also allow us to explore the cognitive and the semantic contents of the papers being analysed. Data obtained with these methods provide a better account of “disciplinarity cohesion”. Emerging dynamics will be further understood by applying graphic analysis to the complex datasets obtained from cross analysis of shared references. This will allow us to map the spatial and temporal dynamics of the networks, to identify the participation of non-academic actors in publications, and to assess co-authorship in quantitative (intensity) and qualitative (thematic) terms. Finally, we integrate the data obtained to also observe the articulation of the networks in terms of the actors’ motivations: whether they respond to institutional policies or regulations, to the relationships with other actors to industrialize knowledge, or to other factors that operate as stimulus for the formation of networks. This will be contrasted with the analysis of (discursive) network objectives, the goals of the funding agencies or institutions that sponsor them, and the overall funding structure.
Challenges encountered thus far mostly resided on:
- “Language barriers” with scientists from natural and hard sciences.
- Reaching NGO representatives.
- Widening our empirical data (adding more different cases). During the last period, however, we could overcome this barrier, thanks to the inclusion of two new PhD students.
- Even when open and collaborative science practices are taking place, and even if open resources for knowledge are relatively widespread, taking advantage of these requires rather sophisticated competences.
- Using open knowledge may become a challenge for some stakeholders when it is “handed down” to them, as there are very different stakeholders with very different ability and resources to effectively use this knowledge. These differences sometimes lies in cognitive aspects (i.e., experts vs. “lay” stakeholders, such as biologists and groups affected by diseases), but sometimes the gap is due to more “sensitive” aspects such as political influence, institutional support and access to infrastructure (i.e., pharma companies and global NGO representatives vs. researchers at public institutions).
- These gaps turned the question on whether knowledge is open or closed into what is to be done with knowledge and how.
- In addition to this, while there are certain researchers/groups that collaborate closely with stakeholders (migrants, NGOs, decision-makers), others tend to rely on more traditional approaches to knowledge production, where stakeholders play the usual role of informants. Open or closed knowledge seems to depend more on traditions of research (more open in the Southern and Northern borders, for example) than on the utility/usefulness of knowledge itself.
What do your findings suggest about the nature/context of open science in development?
Our particular context in development (Argentina, Brazil and México) seems to be a constitutive factor in both shaping the issue and proposing solutions. In at least three of our four case studies, for instance:
- Neglected tropical diseases are, by definition, endemic in developing regions. Although they have recently spread out to developed regions or wealthy sub-areas within the context of development, biomedical research on such diseases (and especially drug development) is dominated by international NGOs and research centres from developed countries which collaborate with local stakeholders. These local stakeholders related to public research, on the other hand, accrue recognition and resources from ties with international stakeholders.
- In the case of Mexico’s migratory patterns, the collection of data is a very sensitive issue due to risks associated with human trafficking and surveillance. Migration patterns are, as one would expect, heavily influenced by economic opportunities in the United States. Local social scientists studying the phenomenon, on the other hand, draw heavily on ‘mainstream’ (or Northern) conceptual frameworks and methods. At the same time, researchers claim to be aware of both issues, and regard it as problematic only to a certain extent. Certain peripheral institutions (El Colegio de la Frontera Sur) and regions (borders) seem to work more closely with stakeholders and, perhaps as a consequence, they are more case-oriented and less concerned with mainstream theoretical contributions (from abroad).
- In the case of major mining projects in Argentina, the main stakeholders are transnational mining firms, on the one hand, and local organizations opposing their activities, on the other. Scientific knowledge is to be used and mobilised by both parties in order to back up their stance on the conflict. At the same time, however, access to scientific knowledge can be partly restricted due to conflicts of interest between the different parties and their possible influence on assessment processes.
- The case of jaguar preservation research could be even more “rare” in terms of involving international stakeholders. This particular research network, which includes collaboration from a considerable number of non-scientific and non-institutional stakeholders, seems to be entirely based in the local context. In other words, no major international stakeholder seems to take part in the production of knowledge or in the shaping of the issue. However, this local research group (dedicated to monitoring endangered jaguars) is likely to play a key role in defining the issue altogether.