Some issues related to the topological aggregation of preferences

This paper deals with the topological approach to social choice theory initiated by Chichilnisky. We study several issues concerning the existence and uniqueness of Chichilnisky rules defined on preference spaces. We show that on topological vector spaces the only additive, anonymous, and unanimous aggregation n-rule is the convex mean. We study the case of infinite agents and show that an infinite Chichilnisky rule might be considered as the limit of rules for finitely many agents. Finally, we show that under some restrictions on the preference space, the existence of a Chichilnisky rule for every finite case implies the existence of a weak Chichilnisky rule for the infinite case.     

Identidad de género, ética protestante y atribución de causalidad

Resumen

El artículo analiza una doble problemática en tomo a la identidad de género: (a) los determinantes sociales de la identidad de género y (b) los sesgos preceptivos-cognitivos en la evaluación y explicación de acciones desarrolladas por un actor según su pertenencia sexual.

Se concluye que la génesis de las diferencias en las identidades sociales de hombres y mujeres esta ligada a la distribución social del trabajo en función del sexo. Igualmente se confirma la existencia de sesgos perceptivo-cognitivos en la evaluación de acciones sociales.     

Monitoring Progress in Child Poverty Reduction: Methodological Insights and Illustration to the Case Study of Bangladesh

Important steps have been taken at international summits to set up goals and targets to improve the wellbeing of children worldwide. Now the world also has more and better data to monitor progress. This paper presents a new approach to monitoring progress in child poverty reduction based on the Alkire and Foster adjusted headcount ratio and an array of complementary techniques. A theoretical discussion is accompanied by an assessment of child poverty reduction in Bangladesh based on four rounds of the demographic household survey (1997–2007). Emphasis is given to dimensional monotonicity and decomposability as desirable properties of multidimensional poverty measures. Complementary techniques for analysing changes over time are also illustrated, including the Shapley decomposition of changes in overall poverty, as well as a range of robustness tests and statistical significance tests. The results from Bangladesh illustrate the value added of these new tools and the information they provide for policy. The analysis reveals two paths to multidimensional poverty reduction by either decreasing the incidence of poverty or its intensity, and exposes an uneven distribution of national gains across geographical divisions. The methodology allows an integrated analysis of overall changes yet simultaneously examines progress in each region and in each dimension, retaining the positive features of dashboard approaches. The empirical evidence highlights the need to move beyond the headcount ratio towards new measures of child poverty that reflect the intensity of poverty and multiple deprivations that affect poor children at the same time.     

Optimal Method for Realizing Two-Sided Inferences About a Linear Combination of Two Proportions

In order to reach the inference about a linear combination of two independent binomial proportions, various procedures exist (Wald's classic method, the exact, approximate, or maximized score methods, and the Newcombe-Zou method). This article defines and evaluates 25 different methods of inference, and selects the ones with the best behavior. In general terms, the optimal method is the classic Wald method applied to the data to which z ² _α/2/4 successes and z ² _α/2/4 failures are added (≈1 if α = 5%) if no sample proportion has a value of 0 or 1 (otherwise the added increase may be different).

Supplemental materials are available for this article. Go to the publisher's online edition of Communications in Statistics - Simulation and Computation to view the free supplemental file.     

Advancing careers through ‘merit’: a rationalized-sensemaking narrative in hierarchical organizations

ABSTRACT

This contribution provides an in-context exploration of how middle-managers make sense of their career progress, and particularly focuses on ‘merit’ to understand how careers are driven in a hierarchical organization. The study exposes ‘merit’ as a fragmented and individualized construction that links back to the participants’ broader life ambitions and identity footprint. It also shows a tendency for maintaining trust in ‘merit’ above other circumstantial and opportunity factors, even in face of events which undermine the application of the merit-based principle. ‘Merit’ is hence portrayed to be a rationalized narrative in careers’ trajectory; a marker used by participants to make sense of events in a coherent manner, consequently experiencing self-efficacy and reducing uncertainty. The findings add complexity to the ‘meritocracy’ debate, calling for new critiques which address its underlying inequality dimension while also contemplating the individual psychological purpose driving ‘merit’ beliefs.     

Replacement of semi-natural cover with artificial substrates in urban parks causes a decline of house sparrows Passer domesticus in Mediterranean towns

Urban Ecosystems - Many European towns and cities have undergone reurbanisation processes in recent decades. However, their effects on urban biodiversity have been poorly studied. Currently...     

Imputation of repeatedly observed multinomial variables in longitudinal surveys

It is now a standard practice to replace missing data in longitudinal surveys with imputed values, but there is still much uncertainty about the best approach to adopt. Using data from a real survey, we compared different strategies combining multiple imputation and the chained equations method, the two main objectives being (1) to explore the impact of the explanatory variables in the chained regression equations and (2) to study the effect of imputation on causality between successive waves of the survey. Results were very stable from one simulation to another, and no systematic bias did appear. The critical points of the method lied in the proper choice of covariates and in the respect of the temporal relation between variables.