Reliable Professionals,Sensitive Dads and Tough Fighters

The significance and complexity of mostly male-dominated military peacekeeping forces continues to grow globally, as does the complexity of the masculinities performed in them. This article discusses the discourses and performances of peacekeeper masculinities, drawing on a qualitative case study of Finnish peacekeeping forces. The self-image of Finland as a provider of ideal peacekeepers and practising progressive gender policy is critically analysed. Taking the notion of multiple masculinities as a starting point, three indicative categories of Finnish peacekeeper masculinities are examined. Discourses of ‘amateur professionals’ and ‘peacekeeper fathers’ create space for military peacekeepers to show aspects of masculinity not associated with traditional military masculinities. The third discourse of ‘tough fighters’, however, harks back to more traditional ‘warrior’ concepts. Official gender mainstreaming efforts and assumptions that these attitudes are internalized ‘naturally’ by Finns are put into question by deprecatory or ambiguous attitudes towards gender equity and sexual exploitation. Despite being part of multi-national forces, peacekeeper masculinities are defined based on presumed notions of ‘national character’.     

Living Differences: Ethnicity and Fearless Girls in Public Spaces

Its strength (of the book of Jules Verne, Snr) comes precisely from knowing never to invent, but paying acute, almost hypnotic, attention to the real, so as to get it to yield up its secret and reveal its possibilities.(Writings on the City)     

Sequential Monte Carlo on large binary sampling spaces

A Monte Carlo algorithm is said to be adaptive if it automatically calibrates its current proposal distribution using past simulations. The choice of the parametric family that defines the set of proposal distributions is critical for good performance. In this paper, we present such a parametric family for adaptive sampling on high dimensional binary spaces. A practical motivation for this problem is variable selection in a linear regression context. We want to sample from a Bayesian posterior distribution on the model space using an appropriate version of Sequential Monte Carlo. Raw versions of Sequential Monte Carlo are easily implemented using binary vectors with independent components. For high dimensional problems, however, these simple proposals do not yield satisfactory results. The key to an efficient adaptive algorithm are binary parametric families which take correlations into account, analogously to the multivariate normal distribution on continuous spaces. We provide a review of models for binary data and make one of them work in the context of Sequential Monte Carlo sampling. Computational studies on real life data with about a hundred covariates suggest that, on difficult instances, our Sequential Monte Carlo approach clearly outperforms standard techniques based on Markov chain exploration.     

Cooperation governance mode: an extended transaction cost approach

This paper analyses the cooperation governance mode and possible factors affecting the choice between an equity joint venture and a contractual agreement. Although transaction cost economics (TCE) provides a workable and well-used framework within which to analyse this choice, it only captures the static transaction costs related to the two modes. This has lead to a discussion about dynamic governance costs and possible benefits related to the governance mode. The objective of this paper is to show how this extended framework differs from TCE when determining the appropriate governance mode. We use four factors related to nature of cooperation to contrast these two approaches. We collected empirical data about cooperation in the information and communications technology (ICT) sector in order to find support for these arguments. Estimates based on logistic regression analysis suggest that our dynamic governance cost and benefit perspective really provides valuable complementary insights into the traditional static transaction-cost framework when it is a question of the choice of alliance form.     

A method for consideration of conditional dependencies in the Fellegi and Sunter model of record linkage

An objective of Record Linkage is to link two data files by identifying common elements. A popular model for doing the separation is the probabilistic one from Fellegi and Sunter. To estimate the parameters needed for the model usually a mixture model is constructed and the EM algorithm is applied. For simplification, the assumption of conditional independence is often made. This assumption says that if several attributes of elements in the data are compared, then the results of the comparisons regarding the several attributes are independent within the mixture classes. A mixture model constructed with this assumption has been often used. Within this article a straightforward extension of the model is introduced which allows for conditional dependencies but is heavily dependent on the choice of the starting value. Therefore also an estimation procedure for the EM algorithm starting value is proposed. The two models are compared empirically in a simulation study based on telephone book entries. Particularly the effect of different starting values and conditional dependencies on the matching results is investigated.     

The impact of macroeconomic conditions on income inequality

This paper analyzes the relationship between macroeconomic factors and the income distribution using data on equivalized disposable household income from the United Kingdom for 1961–99. We argue in favour of fitting a parametric functional form to the income distribution for each year, and then modeling the time series of model parameters in terms of the macroeconomic factors, as this better allows us to take into account non-stationarity in the time series. Estimates from models that relate income distribution parameters to cyclical variables in first differences (to account for non-stationarity) suggest that neither inflation nor unemployment have significant effects on income inequality. Compared to the commonly-used method of modelling the income shares directly, our approach indicates that there was no clear cut relationship between macroeconomic factors and the UK income distribution during the last third of the twentieth century.     

Assessing goodness-of-fit for evaluation of dose-proportionality

For the clinical development of a new drug, the determination of dose-proportionality is an essential part of the pharmacokinetic evaluations, which may provide early indications of non-linear pharmacokinetics and may help to identify sub-populations with divergent clearances. Prior to making any conclusions regarding dose-proportionality, the goodness-of-fit of the model must be assessed to evaluate the model performance. We propose the use of simulation-based visual predictive checks to improve the validity of dose-proportionality conclusions for complex designs. We provide an illustrative example and include a table to facilitate review by regulatory authorities.