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Controversies as Informal Technology A ssessment

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Abstract

Controversies, especially those that surround "early warnings" about impacts of a technology or a large project, may be welcomed as an informal way of technology assessment. This is not always recognized, because of ideals of consensus and context-free rationality. An alternative, rhetorical perspective is presented on controversies and their sociocognitive dynamics, in which interests and actor-strategies play an integral role besides arguments and evidence. Because of such interactions, articulation of insights and positions occurs, that is, social learning. Improvement of social learning has to take the sociocognitive dynamics into account. Absolute standards and methods are impossible, but one can take robustness of views as a realistic goal.
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... In essence, this interactional work comprises clustering, i.e., establishing coherence between these heterogeneous elements [18][19][20]. These heterogeneous elements would (ideally) be contributed by a diverse set of actors and combined into what Science and Technology Studies (STS) scholars have called a 'robust' decision [21][22][23][24][25][26][27]. ...
... Rip [21,22,25] advocates focusing on the production of 'robustness' . Generally, STS scholars define robustness as 'surviving' public pressure or incorporating 'non-certified' expertise [23,39]. ...
... The difference between an only fashionable and a robust view is a matter of degree, and perhaps also a matter of actual effort that actors are prepared to exert. " [22] Robust decisions thus contain heterogeneous elements, and actors need to exert substantial effort to identify these elements. Thus, the first step of our model is: identifying potentially relevant elements. ...
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Background Health care coverage decisions deal with health care technology provision or reimbursement at a national level. The coverage decision report, i.e., the publicly available document giving reasons for the decision, may contain various elements: quantitative calculations like cost and clinical effectiveness analyses and formalised and non-formalised qualitative considerations. We know little about the process of combining these heterogeneous elements into robust decisions. Methods This study describes a model for combining different elements in coverage decisions. We build on two qualitative cases of coverage appraisals at the Dutch National Health Care Institute, for which we analysed observations at committee meetings ( n = 2, with field notes taken) and the corresponding audio files ( n = 3), interviews with appraisal committee members ( n = 10 in seven interviews) and with Institute employees ( n = 5 in three interviews), and relevant documents ( n = 4). Results We conceptualise decisions as combinations of elements , specifically (quantitative) findings and (qualitative) arguments and values. Our model contains three steps: 1) identifying elements; 2) designing the combinations of elements, which entails articulating links, broadening the scope of designed combinations, and black-boxing links; and 3) testing these combinations and choosing one as the final decision. Conclusions Based on the proposed model, we suggest actively identifying a wider variety of elements and stepping up in terms of engaging patients and the public, including facilitating appeals. Future research could explore how different actors perceive the robustness of decisions and how this relates to their perceived legitimacy.
... In essence, this interactional work comprises clustering, i.e., establishing coherence between these heterogeneous elements (14)(15)(16). These heterogeneous elements would (ideally) be contributed by a diverse set of actors and combined into what Science and Technology Studies scholars have previously called a 'robust' decision (17)(18)(19)(20)(21)(22)(23). ...
... Rip (20)(21)(22) advocates focusing on the production of robustness. Generally, STS scholars de ne robustness as 'surviving' public pressure or incorporating 'non-certi ed' expertise (23,32). ...
... The difference between an only fashionable and a robust view is a matter of degree, and perhaps also a matter of actual effort that actors are prepared to exert." (21) Robust decisions thus contain heterogeneous elements, and actors need to exert substantial effort to identify these elements. Thus, the rst step of our model is: identifying potentially relevant elements. ...
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Background: Health care coverage decisions deal with health care technology provision or reimbursement on a national level. The coverage decision outcome, i.e., the publicly available document with reasons for the decision, may contain various elements: quantitative calculations like cost and clinical effectiveness analyses and formalised and non-formalised qualitative considerations. We know little about the process of combining these heterogeneous elements into robust decision outcomes. Methods: In this study, we describe a model for combining different elements into coverage decision outcomes. We build on two qualitative cases of coverage appraisals at the Dutch National Health Care Institute, for which we analysed observations at committee meetings (n=2, with field notes taken) and analysis of audio files (n=3), interviews with appraisal committee members (n=10 in seven interviews) and with Institute employees (n=5 in three interviews). Results: We conceptualise decision outcomes as combinations of elements, specifically (quantitative) findings and (qualitative) arguments and values. Our model contains three steps: 1) identifying elements; 2) designing the combinations of elements, which entails articulating links, broadening the scope of designed combinations, and black-boxing links; and 3) testing these combinations and choosing one as the final decision outcome. Conclusions: The proposed model highlights decision makers’ expertise in composing both elements and combinations. It also provides additional rationales for facilitating appeals and engaging patients and the public. Future research efforts could further explore the relationship between robustness and decision combination strength.
... Whereas the rationales of institutions and the fluid, networked assemblages of civic movements around matters of concern can be difficult to reconcile (de Waal and de Lange 2019), the citizen science initiatives described here open opportunities for enduring transformation, as various stakeholders negotiate their knowledges, expectations, and values. As evidenced by research on sociotechnical controversies, these interactions need not always be agreeable, as conflicts oblige various sides in a dispute to accommodate the relevance of contending views if they wish to remain influential and credible (Rip 1986). As we highlight in this article, innovative, resourceful, and collaborative grassroots citizen initiatives can be successful at gaining credibility and legitimacy among a wider array of societal stakeholders. ...
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