A multilevel approach to building and leading learning organizations

A multilevel model is offered proposing that organizational learning is an interdependent system where effective leaders enact intervention strategies at the individual (micro), network (meso), and systems (macro) levels. We suggest that leaders approach organizational learning by setting the conditions and structure for learning to occur, while limiting direct interference in the actual creative processes. First, leaders may increase the level of developmental readiness of individual followers, thereby increasing their motivation and ability to approach learning experiences and adapt their mental models. These individuals then serve as catalysts of learning within and between social networks. Second, leaders may promote the diffusion of knowledge between these knowledge catalysts within and across social networks through influencing both the structure and functioning of knowledge networks. Finally, leaders may target actions at the systems level to improve the diffusion to, and institutionalization of, knowledge to the larger organization.     

Valuation of road safety effects in cost–benefit analysis

Cost–benefit analysis is a common method for evaluating the social economic impact of transport projects, and in many of these projects the saving of human lives is an issue. This implies, within the framework of cost–benefit analysis, that a monetary value should be attached to saving human lives. This paper discusses the ‘Value of a Statistical Life’ (VoSL), a concept that is often used for monetising safety effects, in the context of road safety. Firstly, the concept of ‘willingness to pay’ for road safety and its relation to the VoSL are explained. The VoSL approach will be compared to other approaches to monetise safety effects, in particular the human capital approach and ‘quality adjusted life years’. Secondly, methods to estimate the VoSL and their applicability to road safety will be discussed. Thirdly, the paper reviews the VoSL estimates that have been found in scientific research and compares them with the values that are used in policy evaluations. Finally, a VoSL study in the Netherlands will be presented as a case study, and its applicability in policy evaluation will be illustrated.     

Designing a Programme to Support Smallholder Agriculture in Mexico: Lessons from PROCAMPO and Oportunidades

This article argues that there is a gap in current Mexican rural development policy that could be filled by a smallholder‐targeted programme. The gap exists because agricultural programmes tend to benefit better‐off farmers, while social programmes tend to focus on long‐term investment in human capital, specifically for the children of today's poor. Drawing on lessons from PROCAMPO and Oportunidades, it offers a specific design for such a programme at a time when the government is considering how to reform PROCAMPO, given that, after 15 years, it is due to come to an end.     

The Impact of Immigrant Status on Home Ownership in Australia

This paper examines the impact of immigrant status on home ownership in Australia. It shows that the rate of home ownership for most groups of immigrants is comparable to that of the Australian born. As expected, recently arrived immigrants have relatively low probabilities of owning their own home. These results hold for both analyses pooled across movers and non‐movers, and for analyses restricted to those, both immigrants and the native born, who moved residence in the previous five years. A decomposition of the estimated coefficients of the model of tenure choice is developed. This is shown to enhance understanding of variations in rates of home ownership across birthplace groups.     

Immediate and Longer-Term Connections Between Support and Stress in Pregnant/Parenting and Non-Pregnant/Non-Parenting Adolescents

Despite the substantial amount of literature focusing on social support for pregnant and parenting adolescents, few studies have directly examined the relationships among stress and social support across their transition to parenting. The present study investigates the nature of the relationship between stress and support both before and after the birth of the baby. Two groups of adolescent females (one group facing parenthood and one not) completed measures of support and stress across a 7-month period (N = 231) to coincide with the transition to parenthood. In general, support and stress were negatively related when measured concurrently and positively related over time for parenting adolescents but not the non-parenting group. Understanding how long social support impacts stress will enable practitioners to identify when best to provide interventions for pregnant and parenting adolescents.     

Adaptable Careers: Maximizing Less and Exploring More

Today, young adults are expected to decide between educational, vocational, and job options and to make the best choice possible. Career literatures emphasize the importance of young adults' career decision making but also acknowledge the problems related to making these decisions. The authors argue that career counselors could support clients' intuitive processing of career information and help their clients to develop a positive and flexible view of the self and the environment while diminishing concerns about accountability for and irreversibility of career decisions. The authors argue that career adaptability rather than decision making should become the focal concept of career theory and practice.     

Applying Social Learning Theory of Career Decision Making to Gay,Lesbian, Bisexual,Transgender, and Questioning Young Adults

Incorporating J. D. Krumboltz's (1979) social learning theory of career decision making, the author explores career development issues for gay, lesbian, bisexual, transgender, and questioning (GLBTQ) adolescents and young adults. Unique challenges for the GLBTQ population are discussed, specific recommendations for effective career counseling with this population are outlined, and suggestions for future research are presented.     

Attenuating Initial Beliefs: Increasing the Acceptance of Anthropogenic Climate Change Information by Reflecting on Values

Anthropogenic climate change information tends to be interpreted against the backdrop of initial environmental beliefs, which can lead to some people being resistant toward the information. In this article (N = 88), we examined whether self‐affirmation via reflection on personally important values could attenuate the impact of initial beliefs on the acceptance of anthropogenic climate change evidence. Our findings showed that initial beliefs about the human impact on ecological stability influenced the acceptance of information only among nonaffirmed participants. Self‐affirmed participants who were initially resistant toward the information showed stronger beliefs in the existence of climate change risks and greater acknowledgment that individual efficacy has a role to play in reducing climate change risks than did their nonaffirmed counterparts.     

A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.