Transdisciplinary co-production of knowledge in the development of organic agriculture in Switzerland

The present study analyses transdisciplinary co-production of knowledge in the development of organic farming in Switzerland by using Fleck's theory of thought styles and thought collectives. Three different phases can be identified throughout the historical development. The initial phase lasting from the beginning of the 1920s to the early 1970s contains numerous characteristics of diverse well-established definitions and concepts of transdisciplinarity and represents a successful transdisciplinary process, which has not been perceived as such in the past and present scientific discussion. The second and third phases show an increasing segregation of thought collectives, caused by internal changes such as the establishment of specialised research institutions and external processes like agriculture policy and market development. These developments led to a decreasing degree of transdisciplinarity. We observe an ambiguous trend: the continuously growing and today well-established positive societal recognition of an initially rather little accepted newcomer movement is associated with the gradual loss of its very valuable forms of knowledge co-production and the related philosophical background. In order to maintain the various forms of transdisciplinary co-production of knowledge, one has to reflect not only their results or outcome but also the whole cooperation process, which has led to these results. The understanding of the historical development and characteristic features of knowledge co-production as presented in this study will help to reinforce transdisciplinary research in organic agriculture and research on transdisciplinarity in general.

Increasing Scientific Confidence in Adverse Outcome Pathways: Application of Tailored Bradford-Hill Considerations for Evaluating Weight of Evidence.

Systematic consideration of scientific support is a critical element in developing and, ultimately, using adverse outcome pathways (AOPs) for various regulatory applications. Though weight of evidence (WoE) analysis has been proposed as a basis for assessment of the maturity and level of confidence in an AOP, methodologies and tools are still being formalized. The Organization for Economic Co-operation and Development (OECD) Users' Handbook Supplement to the Guidance Document for Developing and Assessing AOPs (OECD 2014a; hereafter referred to as the OECD AOP Handbook) provides tailored Bradford-Hill (BH) considerations for systematic assessment of confidence in a given AOP. These considerations include (1) biological plausibility and (2) empirical support (dose-response, temporality, and incidence) for Key Event Relationships (KERs), and (3) essentiality of key events (KEs). Here, we test the application of these tailored BH considerations and the guidance outlined in the OECD AOP Handbook using a number of case examples to increase experience in more transparently documenting rationales for assigned levels of confidence to KEs and KERs, and to promote consistency in evaluation within and across AOPs. The major lessons learned from experience are documented, and taken together with the case examples, should contribute to better common understanding of the nature and form of documentation required to increase confidence in the application of AOPs for specific uses. Based on the tailored BH considerations and defining questions, a prototype quantitative model for assessing the WoE of an AOP using tools of multi-criteria decision analysis (MCDA) is described. The applicability of the approach is also demonstrated using the case example aromatase inhibition leading to reproductive dysfunction in fish. Following the acquisition of additional experience in the development and assessment of AOPs, further refinement of parameterization of the model through expert elicitation is recommended. Overall, the application of quantitative WoE approaches hold promise to enhance the rigor, transparency and reproducibility for AOP WoE determinations and may play an important role in delineating areas where research would have the greatest impact on improving the overall confidence in the AOP.