Playground Accessibility and Neighbourhood Social Interaction Among Parents

While the positive association between social interaction and access to green space is well accepted, little research has sought to understand the role of children??s playgrounds in facilitating social interaction within a community. Playgrounds are spaces designed to facilitate play and the interaction of children, but may also be important places of interaction between parents. In this paper we examine how access to playground spaces is related to social interaction between parents. We use two measures of accessibility (1) walking distance to the closest playground and (2) playground service area, a measure of the number of potential users of a playground based on population density. We use generalized estimating equations, an extension of generalized linear models, to control for the confounding effects of socio-economic status (income, education), neighbourhood dynamics (neighbourhood location, years in neighbourhood) and free time (daily outdoor activity, marital status, number of children) on the independent relationship between social interaction and access to playground spaces. Our results suggest that while accessibility to playgrounds is associated with social interaction among parents, the direction of the effect is opposite to existing literature on green space and social interaction; parents with low accessibility to playgrounds are more likely to interact socially with their neighbours than parents with high accessibility. Our results suggest a pattern of spatial behaviour in which the burden of poor access to some resources may actually encourage greater neighbourhood engagement. Future research studying the relationship between health and green space may benefit from studying the specific role of playground spaces.     

Introductory Statistics Textbooks and the GAISE Recommendations

The six recommendations made by the Guidelines for Assessment and Instruction in Statistics Education (GAISE) committee were first communicated in 2005 and more formally in 2010. In this article, 25 introductory statistics textbooks are examined to assess how well these textbooks have incorporated the three GAISE recommendations most relevant to implementation in textbooks (statistical literacy and thinking; use of real data; stress concepts over procedures). The implementation of another recommendation (using technology) is described but not assessed. In general, most textbooks appear to be adopting the GAISE recommendations reasonably well in both exposition and exercises. The textbooks are particularly adept at using real data, using real data well, and promoting statistical literacy. Textbooks are less adept—but still rated reasonably well, in general—at explaining concepts over procedures and promoting statistical thinking. In contrast, few textbooks have easy-usable glossaries of statistical terms to assist with understanding of statistical language and literacy development. Supplementary materials for this article are available online.     

Dynamic reasoning and time pressure: Transition from analytical operations to experiential responses

Based upon the Decision Field Theory (Busemeyer and Townsend 1993), we tested a model of dynamic reasoning to predict the effect of time pressure on analytical and experiential processing during decision-making. Forty-six participants were required to make investment decisions under four levels of time pressure. In each decision, participants were presented with experiential cues which were either congruent or incongruent with the analytical information. The congruent/incongruent conditions allowed us to examine how many decisions were based upon the experiential versus the analytical information, and to see if this was affected by the varying degrees of time pressure. As expected, the overall accuracy was reduced with greater time pressure and accuracy was higher when the experiential and analytical cues were congruent than when they were incongruent. Of great interest was the data showing that under high time pressure participants used more experiential cues than at other time pressures. We suggest that the dynamic reasoning paradigm has some future potential for predicting the effects of experiential biases in general, and specifically under time pressure.     

MEASURING THE INTERDEPENDENCE OF MULTINATIONAL FIRMS' FOREIGN INVESTMENTS

Earlier work found evidence for geographic linkages of aggregate foreign direct investment across countries and country‐pairs. From a theoretical point of view, such linkages at the macroeconomic level may root in between‐firm as well as within‐firm linkages and originate from information spillovers across or within firms in exploring unknown markets, and vertical linkages between production plants across different locations within the firm. We use data on the universe of German multinational enterprises (MNEs) to empirically explore how marginal investments at one foreign affiliate depend on investments at other affiliates within the same MNE. The empirical approach employs two channels or modes of cross‐affiliate interdependence: mere geography (capturing horizontal linkages through correlated learning and horizontal competition within the firm) and input–output relationships within or across industries (which capture vertical linkages). Adding to earlier findings at the aggregate level, we find evidence of a significant interdependence of investments within the firm. In the firm‐level data at hand, vertical linkages appear to be more important than horizontal ones. Investments at one location tend to stimulate investments at other locations of the same MNE, particularly if input linkages are strong. The opposite seems to be true for output linkages. Beyond vertical linkages, mere geographic proximity matters only to a minor extent. This suggests that evidence of linkages through geographic closeness at aggregate data levels accrue mainly to reasons of vertical linkages within networks of affiliates. (JEL C31, D22, F21, F23, F68, G31, H32)     

Sampling schemes for price index construction: a performance comparison across the classification of individual consumption by purpose food groups

Five sampling schemes (SS) for price index construction – one cut-off sampling technique and four probability-proportional-to-size (pps) methods – are evaluated by comparing their performance on a homescan market research data set across 21 months for each of the 13 classification of individual consumption by purpose (COICOP) food groups. Classifications are derived for each of the food groups and the population index value is used as a reference to derive performance error measures, such as root mean squared error, bias and standard deviation for each food type. Repeated samples are taken for each of the pps schemes and the resulting performance error measures analysed using regression of three of the pps schemes to assess the overall effect of SS and COICOP group whilst controlling for sample size, month and population index value. Cut-off sampling appears to perform less well than pps methods and multistage pps seems to have no advantage over its single-stage counterpart. The jackknife resampling technique is also explored as a means of estimating the standard error of the index and compared with the actual results from repeated sampling.     

Statement of Withdrawal: Statistical analysis of an endemic disease from a capture–recapture experiment

There are a number of statistical techniques for analysing epidemic outbreaks. However, many diseases are endemic within populations and the analysis of such diseases are complicated by changing population demography. Motivated by the spread of cowpox among rodent populations, a combined mathematical model for population and disease dynamics is introduced. An MCMC algorithm is then constructed to make statistical inference for the model based on data being obtained from a capture–recapture experiment. The statistical analysis is used to identify the key elements in the spread of the cowpox virus.     

Bayesian analysis of a multiple-recapture model

In the Bayesian analysis of a multiple-recapture census, different diffuse prior distributions can lead to markedly different inferences about the population size N. Through consideration of the Fisher information matrix it is shown that the number of captures in each sample typically provides little information about N. This suggests that if there is no prior information about capture probabilities, then knowledge of just the sample sizes and not the number of recaptures should leave the distribution of Nunchanged. A prior model that has this property is identified and the posterior distribution is examined. In particular, asymptotic estimates of the posterior mean and variance are derived. Differences between Bayesian and classical point and interval estimators are illustrated through examples.     

Diversity without difference: modelling ‘the real’ in the social aesthetic of a London multicultural school

This article analyses the social aesthetic of the visual displays of a multicultural London primary school. It shows that the social aesthetic of the school models the school as a site of the ‘real’ in Baudrillard's sense of a ‘real’ that is a simulacra of the real, one from which the violence that is produced within and is constitutive of capitalism is expelled. In this view ‘race’ is not a division of humanity caused by racism, it is simply a cultural sign marking diversity. Difference, in the sense of racialised inequalities or racism, can be expelled from the system without ‘race’ itself being expelled. By the same logic, nationalism, as an exclusionary ideology, is separated out from national identity, which becomes simply one of a range of cultural resources that children can draw on in assembling the self.