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With the rise of the impact assessment revolution, governments and public opinion have started to ask researchers to give evidence of their impact outside the traditional audiences, i.e. students and researchers. There is a mismatch between the request to demonstrate the impact and the current methodologies for impact assessment. This mismatch is particularly worrisome for the research in Social Sciences and Humanities. This paper gives a contribution by examining systematically a key element of impact, i.e. the social groups that are directly or indirectly affected by the results of research. We use a Text mining approach applied to the Research Excellence Framework (REF) collection of 6,637 impact case studies in order to identify social groups mentioned by researchers. Differently from previous studies, we employ a lexicon of user groups that includes 76,857 entries, which saturates the semantic field, permits the identification of all users and opens the way to normalization. We then develop three new metrics measuring Frequency, Diversity and Specificity of user expressions. We find that Social Sciences and Humanities exhibit a distinctive structure with respect to frequency and specificity of users.
With the rise of the impact assessment revolution, governments and public opinion have started to ask researchers to give evidence of their impact outside the traditional audiences, i.e. students and researchers. There is a mismatch between the request to demonstrate the impact and the current methodologies for impact assessment. This mismatch is particularly worrisome for the research in Social Sciences and Humanities. This paper gives a contribution by examining systematically a key element of impact, i.e. the social groups that are directly or indirectly affected by the results of research. We use a Text mining approach applied to the Research Excellence Framework (REF) collection of 6,637 impact case studies in order to identify social groups mentioned by researchers. Differently from previous studies, we employ a lexicon of user groups that includes 76,857 entries, which saturates the semantic field, permits the identification of all users and opens the way to normalization. We then develop three new metrics measuring Frequency, Diversity and Specificity of user expressions. We find that Social Sciences and Humanities exhibit a distinctive structure with respect to frequency and specificity of users.
Aim. This paper elucidates how the emergent impact agenda is slowly but surely changing the normative framework of modern Western science. Method. The paper investigates conceptually the implications of the impact agenda for the research process. We outline a chronology around the evaluation regime of research impact and identify the causal mechanisms that change the disciplinary structure of the research ecosystem. We draw upon a sociological model of scientific knowledge production to contrast and discuss how impact facts mimic the process of scientific knowledge production but are geared towards a different end. Results. Our findings indicate that an explicit emphasis on societal contribution not only propositions a different purpose of research, but also changes the logic of research along its entire construction. The impact logic mimics the creation of scientific facts; nevertheless, as it is geared towards a different end, it hermetically seals itself from criticism as any form of scrutiny would otherwise undermine its own legitimacy. Conclusion. We conclude that only explicit acknowledgement of the adverse potential of the impact agenda can maintain science’s benefit to society. We argue that an emphasis on the advancement of knowledge, as opposed to impact, can maintain innovation and preempt social tension. The contribution of this paper lies in identifying the societal influence of the scientific ideal of truth, and articulating the unintended consequences of the impact agenda as the emerging impact or starve paradigm.
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