The focus of this study is how intended users of the built environment are categorized in strategies, policies, and guidelines for the planning and building process. The image of the intended user reflects a disabling society that also is in conflict with established policies on a society for all. Patterns of inequality are found in the materials, both within and across groups of users. With youth, health, and mobility in the foreground, older persons and persons with disabilities are almost never evident. Disability is made visible only through its mirror: the ability norm.In the review of planning documents from a medium-sized Swedish municipality, the study sought to identify if and how users are described and to analyse which users are included in or excluded from the urban environment during planning stages. The article argues that new ways of thinking, to include a diversity perspective in planning, are needed.

Mixture models occur in numerous settings including random and fixed effects models, clustering, deconvolution, empirical Bayes problems and many others. They are often used to model data originating from a heterogeneous population, consisting of several homogeneous subpopulations, and the problem of finding a good estimator for the number of components in the mixture arises naturally. Estimation of the order of a finite mixture model is a hard statistical task, and multiple techniques have been suggested for solving it. We will concentrate on several methods that have not gained much popularity yet deserve the attention of practitioners. These can be categorized into three groups: tools built upon the determinant of the Hankel matrix of moments of the mixing distribution, minimum distance estimators, likelihood ratio tests. We will address theoretical pillars underlying each of the methods, provide some useful modifications for enhancing their performance and present the results of the comparative numerical study that has been conducted under various scenarios. According to the results, none of the methods proves to be a “magic pill”. The results uncover limitations of the techniques and provide practical hints for choosing the best-suited tool under specific conditions.