Prediction : science, decision making, and the future of nature

2000

186 citations recorded by the source corpus.

Subfields: Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/8c90eb65a4c4d991b4918a588396d768673707f1

Citations in the corpus

• Environmental Impacts of Sand Exploitation. Analysis of Sand Market (2017, unknown): “Pilkey asserts that: “the natural sources of beach sand are decreasing, and the natural causes of sand removal are increasing” [145].”
• Does climate policy need probabilities (2003, unknown): “Since the 1970s, predictive tools in the form of GCMs have played a central and sometimes controversial role in climate policy (Shackley et al., 1998; Rayner, 2000).”
• Reconciling the supply of scientific information with user demands: an analysis of the problem and review of the literature (2007, unknown): “…findings stems from a variety of sources, such as spatial and temporal sensitivity (Owens et al., 1997); the complexity and interdependence of Earth systems (Mitchell and Lankao, 2004); attempts at predicting the future (Sarewitz et al., 2000); measurement, sampling, or human errors; and others.”
• Impacts, adaptation and vulnerability to global environmental change: challenges and pathways for an action-oriented research agenda for middle-income and low-income countries (2010, unknown): “This assumption is not borne out by studies [7,86,87], suggesting that a deep understanding of MLICs’ strategy choices in the area of climate-related research and action requires consideration also of the subjective, political, historical and cultural factors that shape the interpretive frameworks o”
• The role of scientists in the environmental policy process: a case study from the American west (2004, unknown): “In recent years, there has been an increasing emphasis among decision makers, interest groups, and citizens alike on the importance of more science-based environmental policy at local, regional, national, and international levels of governance (Johnson et al., 1999; Sarewitz et al., 2000).”
• Assessing Future Ecosystem Services: a Case Study of the Northern Highlands Lake District, Wisconsin (2003, unknown): “Ecologists rarely, if ever, have enough information to provide accurate predictions of the future (Sherden 1998, Ludwig 2002, Sarewitz et al. 2000).”
• The rationale behind the success of multi-model ensembles in seasonal forecasting — II. Calibration and combination (2005, unknown): “…the context of the application to end-user models (e.g. Cantelaube and Terres 2005; Challinor et al., 2005; Marletto et al., 2005; Morse et al., 2005) and of the decision-making process of users (Sarewitz et al., 2000; Jochec et al., 2001; Hartmann et al., 2002; Murnane et al., 2002; Archer, 2003).”
• When scientists politicize science: making sense of controversy over The Skeptical Environmentalist (2004, unknown): “The usual caveats apply.”
• The neglected heart of science policy: reconciling supply of and demand for science (2007, unknown): “…(i.e., in the relations between science policy decisions and societal outcomes) are obstacles to accurate predictions, but they need not prevent improved decision-making (e.g., Lasswell, 1971; Lindblom, 1959; Sarewitz et al., 2000), where ''improved'' means more likely to achieve desired outcomes.”
• Does climate adaptation policy need probabilities? (2004, unknown): “These types of probabilities are called frequentist (or classical) because they are determined by long-run observations of the occurrence of an event (Stewart, 2000).”