Adolescent Sibling Relationship Quality and Adjustment: Sibling Trustworthiness and Modeling,as Factors Directly and Indirectly Influencing These Associations

The main goal of this study was to examine the direct and moderating effects of trustworthiness and modeling on adolescent siblings' adjustment. Data were collected from 438 families including a mother, a younger sibling in fifth, sixth, or seventh grade (M = 11.6 years), and an older sibling (M = 14.3 years). Respondents completed Web‐based surveys describing sibling conflict and warmth. Siblings reported on trustworthiness and modeling, and mothers described adjustment. Sibling conflict was directly associated with internalizing and externalizing behaviors for both siblings. The older siblings' reports of trustworthiness were directly associated with the outcome measures. The younger siblings' reports of trustworthiness were less directly associated, but a possible salutary effect was most evident under the highest levels of sibling conflict or warmth. Higher sibling modeling was a risk factor for adjustment problems in relations characterized by high conflict. Results support exploring trustworthiness as a key dimension of sibling relations.     

Preschoolers' Bistrategic Resource Control,Reconciliation, and Peer Regard

Bistrategic resource control entails using both coercive and prosocial strategies in competition for resources. The present study sought to clarify whether bistrategic involves more than simply using both strategies some of the time. Examining 88 preschoolers' coercion and prosociality over an entire school year, results showed that coercive resource control was used most frequently at the start of the school year, presumably to access resources and establish social dominance. Rates of prosocial resource control increased over the school year, and socially dominant preschoolers showed higher rates compared with peers, presumably to maintain resource control while keeping peers as allies. Socially dominant preschoolers also used reconciliation more often than peers, resulting in higher rates of affiliation between former competitors and more positive peer regard from fall to spring. Findings are discussed in terms of resource control theory and the importance of situating social behaviors within the behavioral and relationship context in which they are embedded.     

Improving confidence in tree species selection for challenging urban sites: a role for leaf turgor loss

High species diversity is argued to be the most important requisite for a resilient urban forest. In spite of this, there are many cities in the northern hemisphere that have very limited species diversity within their tree population. Consequently, there is an immense risk to urban canopy cover, if these over-used species succumb to serious pests or pathogens. Recognition of this should motivate the use of less commonly used species. Analysis of plant traits, such as the leaf water potential at turgor loss (Ψ_P0), can provide useful insights into a species’ capacity to grow in warm and dry urban environments. Therefore, the aim of this study was to evaluate Ψ_P0 of 45 tree species, the majority of which are rare in urban environments. To help evaluate the potential for using Ψ_P0 data to support future decision-making, a survey of professionals engaged with establishing trees in urban environments was also used to assess the relationship between the measured Ψ_P0 and the perceived drought tolerance of selected species. This study demonstrates that Ψ_P0 gives strong evidence for a species’ capacity to tolerate dry growing conditions and is a trait that varies substantially across species. Furthermore, Ψ_P0 was shown to closely relate to the experience of professionals involved in establishing trees in urban environments, thus providing evidence of its practical significance. Use of plant traits, such as Ψ_P0, should, therefore, give those specifying trees confidence to recommend non-traditional species for challenging urban environments.     

Why are social sciences and humanities needed in the works of IPBES? A systematic review of the literature

Despite the increased attention, which has been given to the issue of involving knowledge and experts from the social sciences and humanities (SSH) into the products and works of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), little is known on what the expectations towards the involvement of SSH in IPBES actually are. The aim of this paper is to close this gap by identifying the range of possible SSH contributions to IPBES that are expected in the literature, and discuss the inherent challenges of and concrete ways to realize these contributions in the particular institutional setting of IPBES. We address these two points by: firstly, assessing the literature dealing with IPBES and building a typology describing the main ways in which contributions from SSH to IPBES have been conceived between 2006 and 2017. We discuss these expected contributions in light of broader debates on the role of SSH in nature conservation and analyse some of the blind spots and selectivities in the perception of how SSH could substantially contribute to the works of IPBES. Then, secondly, by looking at one particular example, economics and its use in the first thematic assessment on pollinators, pollination and food production, we will concretely illustrate how works in a given discipline could contribute in many different and unprecedented ways to the works of IPBES and help identify paths for enhancing the conservation of biodiversity. Finally, we propose a range of practical recommendations as to how to increase the contribution of SSH in the works of IPBES.     

Mixtures of modified t-factor analyzers for model-based clustering,classification, and discriminant analysis

A novel family of mixture models is introduced based on modified t-factor analyzers. Modified factor analyzers were recently introduced within the Gaussian context and our work presents a more flexible and robust alternative. We introduce a family of mixtures of modified t-factor analyzers that uses this generalized version of the factor analysis covariance structure. We apply this family within three paradigms: model-based clustering; model-based classification; and model-based discriminant analysis. In addition, we apply the recently published Gaussian analogue to this family under the model-based classification and discriminant analysis paradigms for the first time. Parameter estimation is carried out within the alternating expectation-conditional maximization framework and the Bayesian information criterion is used for model selection. Two real data sets are used to compare our approach to other popular model-based approaches; in these comparisons, the chosen mixtures of modified t-factor analyzers model performs favourably. We conclude with a summary and suggestions for future work.     

Diffusive nested sampling

We introduce a general Monte Carlo method based on Nested Sampling (NS), for sampling complex probability distributions and estimating the normalising constant. The method uses one or more particles, which explore a mixture of nested probability distributions, each successive distribution occupying ∼e ⁻¹ times the enclosed prior mass of the previous distribution. While NS technically requires independent generation of particles, Markov Chain Monte Carlo (MCMC) exploration fits naturally into this technique. We illustrate the new method on a test problem and find that it can achieve four times the accuracy of classic MCMC-based Nested Sampling, for the same computational effort; equivalent to a factor of 16 speedup. An additional benefit is that more samples and a more accurate evidence value can be obtained simply by continuing the run for longer, as in standard MCMC.     

The Personal Costs of Subprime Lending and the Foreclosure Crisis: A Matter of Trust,Insecurity, and Institutional Deception*

Objective. Research on widespread loan failures suggests that many of the mortgage loans that were made since 2000 were of a deceptive or predatory nature. This study explores the experiences and sentiments of those who are at risk of foreclosure within a broader framework of trust, individualization, and ontological security. Methods. Interviews examine families' lending experience and how they have coped with their personal troubles that resulted from their housing crisis. Results. As many of these loans were of a deceptive or predatory nature, individuals are likely to reflect on the psychological consequences of their predicament. Although these findings suggest that these individuals have lost trust in the housing market, many have internalized their situation as a personal failure. In addition, feelings of anxiety, stress, insecurity, and uncertainty have come to characterize their experiences. Conclusions. This research calls for policy recommendations that seek to restore confidence and to ensure greater consumer protection in financial markets.     

Bayesian variable selection with spherically symmetric priors

We propose that Bayesian variable selection for linear parametrizations with Gaussian iid likelihoods should be based on the spherical symmetry of the diagonalized parameter space. Our r-prior results in closed forms for the evidence for four examples, including the hyper-g prior and the Zellner–Siow prior, which are shown to be special cases. Scenarios of a single-variable dispersion parameter and of fixed dispersion are studied, and asymptotic forms comparable to the traditional information criteria are derived. A simulation exercise shows that model comparison based on our r-prior gives good results comparable to or better than current model comparison schemes.