Collaborative action research for the governance of climate adaptation - foundations, conditions and pitfalls

This position paper serves as an introductory guide to designing and facilitating an action research process with stakeholders in the context of climate adaptation. Specifically, this is aimed at action researchers who are targeting at involving stakeholders and their expert knowledge in generating knowledge about their own condition and how it can be changed. The core philosophy of our research approach can be described as developing a powerful combination between practice-driven collaborative action research and theoretically-informed scientific research. Collaborative action research means that we take guidance from the hotspots as the primary source of questions, dilemmas and empirical data regarding the governance of adaptation, but also collaborate with them in testing insights and strategies, and evaluating their usefulness. The purpose is to develop effective, legitimate and resilient governance arrangements for climate adaptation. Scientific quality will be achieved by placing this co-production of knowledge in a well-founded and innovative theoretical framework, and through the involvement of the international consortium partners. This position paper provides a methodological starting point of the research program ‘Governance of Climate Adaptation’ and aims: · To clarify the theoretical foundation of collaborative action research and the underlying ontological and epistemological principles · To give an historical overview of the development of action research and its different forms · To enhance the theoretical foundation of collaborative action research in the specific context of governance of climate adaptation. · To translate the philosophy of collaborative action research into practical methods; · To give an overview of the main conditions and pitfalls for action research in complex governance settings Finally, this position paper provides three key instruminstruments developed to support Action Research in the hotspots: 1) Toolbox for AR in hotspots (chapter 6); 2) Set-up of a research design and action plan for AR in hotspots (chapter 7); 3) Quality checklist or guidance for AR in hotspots (chapter 8)

User-driven design of decision support systems for polycentric environmental resources management

Open and decentralized technologies such as the Internet provide increasing opportunities to create knowledge and deliver computer-based decision support for multiple types of users across scales. However, environmental decision support systems/tools (henceforth EDSS) are often strongly science-driven and assuming single types of decision makers, and hence poorly suited for more decentralized and polycentric decision making contexts. In such contexts, EDSS need to be tailored to meet diverse user requirements to ensure that it provides useful (relevant), usable (intuitive), and exchangeable (institutionally unobstructed) information for decision support for different types of actors. To address these issues, we present a participatory framework for designing EDSS that emphasizes a more complete understanding of the decision making structures and iterative design of the user interface. We illustrate the application of the framework through a case study within the context of water-stressed upstream/downstream communities in Lima, Peru

Exploiting Sample Uncertainty for Domain Adaptive Person Re-Identification

Many unsupervised domain adaptive (UDA) person re-identification (ReID) approaches combine clustering-based pseudo-label prediction with feature fine-tuning. However, because of domain gap, the pseudo-labels are not always reliable and there are noisy/incorrect labels. This would mislead the feature representation learning and deteriorate the performance. In this paper, we propose to estimate and exploit the credibility of the assigned pseudo-label of each sample to alleviate the influence of noisy labels, by suppressing the contribution of noisy samples. We build our baseline framework using the mean teacher method together with an additional contrastive loss. We have observed that a sample with a wrong pseudo-label through clustering in general has a weaker consistency between the output of the mean teacher model and the student model. Based on this finding, we propose to exploit the uncertainty (measured by consistency levels) to evaluate the reliability of the pseudo-label of a sample and incorporate the uncertainty to re-weight its contribution within various ReID losses, including the identity (ID) classification loss per sample, the triplet loss, and the contrastive loss. Our uncertainty-guided optimization brings significant improvement and achieves the state-of-the-art performance on benchmark datasets.Comment: 9 pages. Accepted to 35th AAAI Conference on Artificial Intelligence (AAAI 2021

Interactive Planning: An Applied Systems Thinking Approach from the Perspective of a Participant-Observer

The systems approach to thinking is at a precipice. Our world is composed of systems and sub-systems so intrinsically linked that any attempt to make changes can upset system interdependencies. Systems thinking is a mindset and method of thinking and seeing things as “wholes,” patterns, interconnections, and interdependencies rather than analyzed parts and sub-parts. The systems approach and the methodologies informed by this approach offer an improved understanding of organizational performance. The systems methodology of interactive planning involves organizational stakeholders as the key ingredient to idealize creative outcomes for organizational problems. The interactive planning process involves carrying out a mess formulation to understand a problematic situation’s current reality and an idealized design to create an innovative reality that dissolves problems and promotes sustainable growth and development (Ackoff, 1981). This proposed study examined the interactive planning process’s effectiveness from the perspectives of a participant-observer. The areas of opportunity included integration into interactive planning with other complementary methodologies and theoretical frameworks that aid in its execution. Another area of investigation in this study was identifying the facilitator skill sets needed for improved idealized design engagement. The experiential knowledge from the researcher as a participant-observer with design session participants provided insight into this methodological approach, adding to the body of knowledge of interactive planning and idealized design creations. The researcher concludes that an effective idealized design outcome results from the effectiveness of a facilitator and facilitation. The effectiveness is contingent on a consistent and delicate balance of mindset, adeptness, experience, understanding of the interactive planning methodology’s application, and skill sets that hinge on coaching tenets, brainstorming techniques, and virtual technology platforms. vi

Using scenarios to forecast outcomes of a refugee crisis

The Syrian civil war has led to millions of Syrians fleeing the country, and has resulted in a humanitarian crisis. By considering how such socio-political events may unfold, scenarios can lead to informed forecasts that can be used for decision-making. We examined the relationship between scenarios and forecasts in the context of the Syrian refugee crisis. Forty Turkish students trained to use a brainstorming technique generated scenarios that might follow within six months of the Turkish government banning Syrian refugees from entering the country. Participants generated from 3-6 scenarios. Over half were rated as ‘high’ quality in terms of completeness, relevance/pertinence, plausibility, coherence, and transparency (order effects). Scenario quality was unaffected by scenario quantity. Even though no forecasts were requested, participants’ first scenarios contained from 0-17 forecasts. Mean forecast accuracy was 45% and this was unaffected by forecast quantity. Therefore, brainstorming can offer a simple and quick way of generating scenarios and forecasts that can potentially help decision-makers tackle humanitarian crises