Reflective Photobooth – a way to visualise,and challenge perceptions and representations of distanced social groups

Taken-for-granted knowledge about people from other social groups is a key challenge for overcoming stereotypes. This article describes a novel arts-based research method to visualise participants’ frames of distanced social groups and aims to trigger reflections among them. The Reflective Photobooth invites participants to dress up as members of distanced social groups, stage a scene, produce pictures, answer prompting questions, and discuss their visualisations. We argue that the artistic re-enactment that underlies the visualisation process can attract diverse groups of participants to engage with research topics, create places for the articulation of critical statements against existing societal clichés and stereotypical media representations, and trigger reflections among participants about taken-for-granted knowledge. The method was tested within the Frame-a-Farmer project, in which the social distance between consumers and food producers in modern agrifood systems was addressed. Results indicate that despite the method bearing some risks and facing some challenges, three promising areas of future application could be identified: (i) raising awareness among large groups of people, (ii) collecting stories or topical vignettes, and (iii) deconstructing taken-for-granted knowledge and societal clichés.     

A Critical View of the Institutional Solution in Economics

Institutionalism is the solution at hand when the expected correlations fail to work. The analytical framework is henceforth enriched with institutional pillars such as stable political structures, lack of corrupt practices, well-specified property rights, low-cost enforcement of contracts, etc. This paper’s thesis is that institutionalism has its own limits circumscribed by the original view of the logic of economic inquiry based on causation. Ignoring the external circumstances of the social whole by virtue of ceteris paribus postulation creates an epistemic vacuum as regards the most part of our understanding of economic evolutions. In guise of a practical corollary, the paper ends with a casuistic illustration from Eastern European transition economies and concludes that the uncertainties of transition, neither more obscured, nor more difficult than of any other historical system, are left as much puzzling in orthodox as in institutional recipes.     

E-optimal designs for three treatments

E-optimality is studied for three treatments in an arbitrary n-way heterogeneity setting. In some cases maximal trace designs cannot be E-optimal. When there is more than one E-optimal design for a given setting, the best with respect to all reasonable criteria is determined.     

Interval censored and truncated data: Rate of convergence of NPMLE of the density

We consider survival data that are both interval censored and truncated. Under appropriate assumptions on the involved distributions, the censoring, truncation and survival, we prove the consistency of the NPMLE of the density of the survival, and give the rate of convergence. Finally, we give an example where the joint law of the censoring and truncation can be explicitly computed.     

The Stuff of Life

The musings of Valentin Kurbatov, a literary critic from Pskov, on books he has read in the past year spill over into a tightly focused, self-contained piece on contemporary literature and contemporary readers, on life ("a greedy now and a vague tomorrow") and the yearning to feel the earth firm beneath one's feet.     

On Large Deviations of Sums of Independent Random Variables

Extensions of some limit theorems are proved for tail probabilities of sums of independent identically distributed random variables satisfying the one-sided or two-sided Cramér's condition. The large deviation x-region under consideration is broader than in the classical Cramér's theorem, and the estimate of the remainder is uniform with respect to x. The corresponding asymptotic expansion with arbitrarily many summands is also obtained.     

Bootstrap confidence intervals in mixtures of discrete distributions

The problem of building bootstrap confidence intervals for small probabilities with count data is addressed. The law of the independent observations is assumed to be a mixture of a given family of power series distributions. The mixing distribution is estimated by nonparametric maximum likelihood and the corresponding mixture is used for resampling. We build percentile-t and Efron percentile bootstrap confidence intervals for the probabilities and we prove their consistency in probability. The new theoretical results are supported by simulation experiments for Poisson and geometric mixtures. We compare percentile-t and Efron percentile bootstrap intervals with eight other bootstrap or asymptotic theory based intervals. It appears that Efron percentile bootstrap intervals outperform the competitors in terms of coverage probability and length.     

On residual approximation in solution extension problems

The solution extension variant of a problem consists in, being given an instance and a partial solution, finding the best solution comprising the given partial solution. Many problems have been studied with a similar approach. For instance the Pre-Coloring Extension problem, the clustered variant of the Travelling Salesman problem, or the General Routing Problem are in a way typical examples of solution extension variant problems. Motivated by practical applications of such variants, this work aims to explore different aspects around extension on classical optimization problems. We define residue-approximations as algorithms whose performance ratio on the non-prescribed part can be bounded, and corresponding complexity classes. Using residue-approximation, we classify problems according to their residue-approximability, exhibit distinct behaviors and give several examples and first interesting results.     

Confidence Intervals for Intraclass Correlation in Inter-Rater Reliability

Abstract Calculation of a confidence interval for intraclass correlation to assess inter‐rater reliability is problematic when the number of raters is small and the rater effect is not negligible. Intervals produced by existing methods are uninformative: the lower bound is often close to zero, even in cases where the reliability is good and the sample size is large. In this paper, we show that this problem is unavoidable without extra assumptions and we propose two new approaches. The first approach assumes that the raters are sufficiently trained and is related to a sensitivity analysis. The second approach is based on a model with fixed rater effect. Using either approach, we obtain conservative and informative confidence intervals even from samples with only two raters. We illustrate our point with data on the development of neuromotor functions in children and adolescents.