Those who conduct integrated assessments (IAs) are aware of the need to explicitly consider multiple criteria and uncertainties when evaluating policies for preventing global warming. MCDM methods are potentially useful for understanding tradeoffs and evaluating risks associated with climate policy alternatives. A difficulty facing potential MCDM users is the wide range of different techniques that have been proposed, each with distinct advantages. Methods differ in terms of validity, ease of use, and appropriateness to the problem. Alternative methods also can yield strikingly different rankings of alternatives. A workshop was held in which climate change experts and policymakers evaluated the usefulness of MCDM for IA. Participants applied several methods in the context of a hypothetical greenhouse gas policy decision. Methods compared include value and utility functions, goal programming, ELECTRE, fuzzy sets, stochastic dominance, min max regret, and several weight selection methods. Ranges, rather than point estimates, were provided for some questions to incorporate imprecision regarding weights. Additionally, several visualization methods for both deterministic and uncertain cases were used and evaluated. Analysis of method results and participant feedback through questionnaires and discussion provide the basis for conclusions regarding the use of MCDM methods for climate change policy and IA analyses. Hypotheses are examined concerning predictive and convergent validity of methods, existence of splitting bias among experts, perceived ability of methods to aid decision-making, and whether expressing imprecision can change ranking results. Because participants gained from viewing a problem from several perspectives and results from different methods often significantly differed, it appears worthwhile to apply several MCDM methods to increase user confidence and insight. The participants themselves recommended such multimethod approaches for policymaking. Yet they preferred the freedom of unaided decision-making most of all, challenging the MCDM community to create transparent methods that permit maximum user control.

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Past research has assessed the association of single community characteristics with obesity, ignoring the spatial co-occurrence of multiple community-level risk factors. We used conditional random forests (CRF), a non-parametric machine learning approach to identify the combination of community features that are most important for the prediction of obesegenic and obesoprotective environments for children. After examining 44 community characteristics, we identified 13 features of the social, food, and physical activity environment that in combination correctly classified 67% of communities as obesoprotective or obesogenic using mean BMI-z as a surrogate. Social environment characteristics emerged as most important classifiers and might provide leverage for intervention. CRF allows consideration of the neighborhood as a system of risk factors.

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An investigation of planning obligations is used to explore the political and economic dynamics associated with the interaction between the planning and development processes. A significant widening in the use and scope of planning obligations has occurred in the last ten years. Obligations are used not only to remove physical constraints on development and to mitigate direct development impacts, but also to ameliorate more diffuse social, economic, and environmental impacts, to provide community benefits, and to support wider policy objectives. This broadening of practice has been spurred on by the austere financial environment within which local authorities must operate. Planning obligations have provided a mechanism for shifting part of the immediate financial burden of the provision of off-site infrastructure, facilities, and services from government to building producers and consumers. This poses a dilemma for planning practice. On the one hand, the profile of planners is raised because they are key negotiators in delivering improvements in local infrastructure and services. On the other hand, the financial aspects of development proposals now influence planning decisions. The potential to negotiate planning obligations is influencing land-use patterns, spatially, sectorally, and in terms of local built form. Short-term planning gains are tending to override longer term planning concerns such as environmental quality. These trends challenge fundamentally our conception of the nature of planning.