Farmers,the Practice of Farming and the Future of Agroforestry: An Application of Bourdieu's Concepts of Field and Habitus

Abstract Agroforestry, the practice of raising crops and trees together in ways that are mutually beneficial, provides farmers with an alternative to more conventional farming practices. In this paper, we apply Bourdieu's concepts of “field” and “habitus” in an attempt to better understand the practice of farming and the role that agroforestry may have in farming systems. Analysis is based on qualitative and quantitative interviews of farmers and other key informants in two regions, Fox‐Wyaconda Watershed in northeast Missouri and Scott County in southeast Missouri. Within the field of farming, farmers emphasized the importance of economic, family and rental relations. Important habitus considerations include different interpretations of what constitutes farming and what constitutes forestry. Based on Bourdieu's theoretical framework, we offer three alternative paths of social change that may lead to more widespread utilization of agroforestry.     

What Do Grandmothers Think about Self‐esteem? American and Taiwanese Folk Theories Revisited

The study investigates European American and Taiwanese grandmothers’ folk theories of childrearing and self‐esteem, building on an earlier comparison of mothers from the same families. Adopting methods that privilege local meanings, we bring grandmothers’ voices into the conversation about childrearing, thereby contributing to a deeper understanding of intergenerational nuances in folk theories. In each cultural case, 16 grandmothers of 3‐year‐olds participated in in‐depth interviews that were customized according to local communicative norms. Although self‐esteem emerged as a central organizing concept in the folk theories of European American mothers, grandmothers spoke in two voices, either echoing their daughters or invoking a counter‐discourse of wariness towards self‐esteem. By contrast, Taiwanese mothers and grandmothers resembled one another—but differed from their American counterparts—in treating self‐esteem as peripheral in childrearing. Results contribute to the growing consensus that self‐esteem is a culture‐specific childrearing goal and suggest that the European American tendency to valorize self‐esteem varies by generation.     

Semi-parametric estimation of ROC curves based on binomial regression modelling

This paper presents a method of estimating a receiver operating characteristic (ROC) curve when the underlying diagnostic variable X is continuous and fully observed. The new method is based on modelling the probability of response given X , rather than the distribution of X given response. The method offers advantages in modelling flexibility and computational simplicity. The resulting ROC curve estimates are semi-parametric and can, in principle, take an infinite variety of shapes. Moreover, model selection can be based on standard methods within the binomial regression framework. Statistical accuracy of the curve estimate is provided by a simply implemented bootstrap approach.     

Residual analysis for spatial point processes (with discussion)

Summary.  We define residuals for point process models fitted to spatial point pattern data, and we propose diagnostic plots based on them. The residuals apply to any point process model that has a conditional intensity; the model may exhibit spatial heterogeneity, interpoint interaction and dependence on spatial covariates. Some existing ad hoc methods for model checking (quadrat counts, scan statistic, kernel smoothed intensity and Berman's diagnostic) are recovered as special cases. Diagnostic tools are developed systematically, by using an analogy between our spatial residuals and the usual residuals for (non-spatial) generalized linear models. The conditional intensity λ plays the role of the mean response. This makes it possible to adapt existing knowledge about model validation for generalized linear models to the spatial point process context, giving recommendations for diagnostic plots. A plot of smoothed residuals against spatial location, or against a spatial covariate, is effective in diagnosing spatial trend or co-variate effects. Q – Q -plots of the residuals are effective in diagnosing interpoint interaction.     

On pooling data summaries in the absence of interactions “response-by-study”

The standard hypothesis testing procedure in meta-analysis (or multi-center clinical trials) in the absence of treatment-by-center interaction relies on approximating the null distribution of the standard test statistic by a standard normal distribution. For relatively small sample sizes, the standard procedure has been shown by various authors to have poor control of the type I error probability, leading to too many liberal decisions. In this article, two test procedures are proposed, which rely on thet—distribution as the reference distribution. A simulation study indicates that the proposed procedures attain significance levels closer to the nominal level compared with the standard procedure.     

Modelling data from single-photon emission computerized tomography

The completely random character of radioactive disintegration provides the basis of a strong justification for a Poisson linear model for single-photon emission computed tomography data, which can be used to produce reconstructions of isotope densities, whether by maximum likelihood or Bayesian methods. However, such a model requires the construction of a matrix of weights, which represent the mean rates of arrival at each detector of photons originating from each point within the body space. Two methods of constructing these weights are discussed, and reconstructions resulting from phantom and real data are presented.