A More Complete Picture: Rural Residents’ Relative Support for Seven Forms of Natural Resource-Related Economic Development

Understanding rural resident support for various forms of natural resource-related economic development has been a common research topic in rural sociology. However, the vast majority of research has only evaluated support for one form of natural resource use at a time. The little research that has explored support for a wide variety of uses has found that residents are likely to support many of the suggested forms of development. We assessed rural resident support for seven forms of natural resource development: commercial logging, natural gas, mining, real estate, wind energy, tourism, and outdoor recreation. Using social exchange theory, this study examines the influence of perceived impacts of development, industry trust, and perceived industry power on general support for the seven forms of natural resource-related economic development using a fixed effects generalized linear model among a sample of residents of rural Pennsylvania communities. Additionally, we use mixed logit discreet choice modeling to evaluate the drivers of relative support, meaning a stated preference for one form of development over other possible options. The drivers of general support and relative support were similar, with trust in industry and impacts to quality of life emerging as the primary drivers of both.     

Unequal Opportunity: School and Neighborhood Segregation in the USA

Race and Social Problems - School and neighborhood segregation are intertwined in complex ways. Schools reflect segregated neighborhoods, and school considerations reinforce neighborhood...     

Efficient polynomial-time algorithms for the constrained LCS problem with strings exclusion

In this paper, we revisit a recent variant of the longest common subsequence (LCS) problem, the string-excluding constrained LCS (STR-EC-LCS) problem, which was first addressed by Chen and Chao (J Comb Optim 21(3):383–392, 2011). Given two sequences \(X\) and \(Y\) of lengths \(m\) and \(n,\) respectively, and a constraint string \(P\) of length \(r,\) we are to find a common subsequence \(Z\) of \(X\) and \(Y\) which excludes \(P\) as a substring and the length of \(Z\) is maximized. In fact, this problem cannot be correctly solved by the previously proposed algorithm. Thus, we give a correct algorithm with \(O(mnr)\) time to solve it. Then, we revisit the STR-EC-LCS problem with multiple constraints \(\{ P_1, P_2, \ldots , P_k \}.\) We propose a polynomial-time algorithm which runs in \(O(mnR)\) time, where \(R = \sum _{i=1}^{k} |P_i|,\) and thus it overthrows the previous claim of NP-hardness.     

Now What Do People Know About Global Climate Change? Survey Studies of Educated Laypeople

In 1992, a mental‐models‐based survey in Pittsburgh, Pennsylvania, revealed that educated laypeople often conflated global climate change and stratospheric ozone depletion, and appeared relatively unaware of the role of anthropogenic carbon dioxide emissions in global warming. This study compares those survey results with 2009 data from a sample of similarly well‐educated laypeople responding to the same survey instrument. Not surprisingly, following a decade of explosive attention to climate change in politics and in the mainstream media, survey respondents in 2009 showed higher awareness and comprehension of some climate change causes. Most notably, unlike those in 1992, 2009 respondents rarely mentioned ozone depletion as a cause of global warming. They were also far more likely to correctly volunteer energy use as a major cause of climate change; many in 2009 also cited natural processes and historical climatic cycles as key causes. When asked how to address the problem of climate change, while respondents in 1992 were unable to differentiate between general “good environmental practices” and actions specific to addressing climate change, respondents in 2009 have begun to appreciate the differences. Despite this, many individuals in 2009 still had incorrect beliefs about climate change, and still did not appear to fully appreciate key facts such as that global warming is primarily due to increased concentrations of carbon dioxide in the atmosphere, and the single most important source of this carbon dioxide is the combustion of fossil fuels.     

Nanotechnology Risk Communication Past and Prologue

Nanotechnologies operate at atomic, molecular, and macromolecular scales, at scales where matter behaves differently than at larger scales and quantum effects can dominate. Nanotechnologies have captured the imagination of science fiction writers as science, engineering, and industry have leapt to the challenge of harnessing them. Applications are proliferating. In contrast, despite recent progress the regulatory landscape is not yet coherent, and public awareness of nanotechnology remains low. This has led risk researchers and critics of current nanotechnology risk communication efforts to call for proactive strategies that do more than address facts, that include and go beyond the public participation stipulated by some government acts. A redoubling of nanotechnology risk communication efforts could enable consumer choice and informed public discourse about regulation and public investments in science and safety.     

Efficacy,Action, and Support for Reducing Climate Change Risks

A growing body of research demonstrates that believing action to reduce the risks of climate change is both possible (self‐efficacy) and effective (response efficacy) is essential to motivate and sustain risk mitigation efforts. Despite this potentially critical role of efficacy beliefs, measures and their use vary wildly in climate change risk perception and communication research, making it hard to compare and learn from efficacy studies. To address this problem and advance our understanding of efficacy beliefs, this article makes three contributions. First, we present a theoretically motivated approach to measuring climate change mitigation efficacy, in light of diverse proposed, perceived, and previously researched strategies. Second, we test this in two national survey samples (Amazon's Mechanical Turk N = 405, GfK Knowledge Panel N = 1,820), demonstrating largely coherent beliefs by level of action and discrimination between types of efficacy. Four additive efficacy scales emerge: personal self‐efficacy, personal response efficacy, government and collective self‐efficacy, and government and collective response efficacy. Third, we employ the resulting efficacy scales in mediation models to test how well efficacy beliefs predict climate change policy support, controlling for specific knowledge, risk perceptions, and ideology, and allowing for mediation by concern. Concern fully mediates the relatively strong effects of perceived risk on policy support, but only partly mediates efficacy beliefs. Stronger government and collective response efficacy beliefs and personal self‐efficacy beliefs are both directly and indirectly associated with greater support for reducing the risks of climate change, even after controlling for ideology and causal beliefs about climate change.     

Efficacy Foundations for Risk Communication: How People Think About Reducing the Risks of Climate Change

Believing action to reduce the risks of climate change is both possible (self‐efficacy) and effective (response efficacy) is essential to motivate and sustain risk mitigation efforts, according to current risk communication theory. Although the public recognizes the dangers of climate change, and is deluged with lists of possible mitigative actions, little is known about public efficacy beliefs in the context of climate change. Prior efficacy studies rely on conflicting constructs and measures of efficacy, and links between efficacy and risk management actions are muddled. As a result, much remains to learn about how laypersons think about the ease and effectiveness of potential mitigative actions. To bring clarity and inform risk communication and management efforts, we investigate how people think about efficacy in the context of climate change risk management by analyzing unprompted and prompted beliefs from two national surveys (N = 405, N = 1,820). In general, respondents distinguish little between effective and ineffective climate strategies. While many respondents appreciate that reducing fossil fuel use is an effective risk mitigation strategy, overall assessments reflect persistent misconceptions about climate change causes, and uncertainties about the effectiveness of risk mitigation strategies. Our findings suggest targeting climate change risk communication and management strategies to (1) address gaps in people's existing mental models of climate action, (2) leverage existing public understanding of both potentially effective mitigation strategies and the collective action dilemma at the heart of climate change action, and (3) take into account ideologically driven reactions to behavior change and government action framed as climate action.     

Learning How and Learning What: Effects of Tacit and Codified Knowledge on Performance Improvement Following Technology Adoption

This paper examines effects of tacit and codified knowledge on performance improvement as organizations gain experience with a new technology. We draw from knowledge management and learning curve research to predict improvement rate heterogeneity across organizations. We first note that the same technology can present opportunities for improvement along more than one dimension, such as efficiency and breadth of use. We compare improvement for two dimensions: one in which the acquisition of codified knowledge leads to improvement and another in which improvement requires tacit knowledge. We hypothesize that improvement rates across organizations will be more heterogeneous for dimensions of performance that rely on tacit knowledge than for those that rely on codified knowledge (H1), and that group membership stability predicts improvement rates for dimensions relying on tacit knowledge (H2). We further hypothesize that when performance relies on codified knowledge, later adopters should improve more quickly than earlier adopters (H3). All three hypotheses are supported in a study of 15 hospitals learning to use a new surgical technology. Implications for theory and practice are discussed.