A mathematical model for resource allocation in population programs

The reduction of population growth rates through family planning programs is being attempted in many of the developing nations of the world. This activity lends itself aptly to mathematical modeling. Building from the well-known difference equation model of population growth, a model is constructed which integrates population dynamics, program activities, and resource consumption. The model may be used predictively to assess the outcome of various program activities. Alternatively, it may be used to determine the pattern of activities which yields the greatest reduction in births under the projected resource constraints. A further use of the model is the identification of the parameters to which predictions are most sensitive; such information provides valuable insights to those gathering the input data. The model is here applied to a family planning program currently in progress. An evaluation of the feasibility of that program’s goals is provided, as well as information on limiting resources, data sensitivity, and the most important ages for contraceptive acceptance.     

A Framework for Monte Carlo based Multiple Testing

We are concerned with a situation in which we would like to test multiple hypotheses with tests whose p‐values cannot be computed explicitly but can be approximated using Monte Carlo simulation. This scenario occurs widely in practice. We are interested in obtaining the same rejections and non‐rejections as the ones obtained if the p‐values for all hypotheses had been available. The present article introduces a framework for this scenario by providing a generic algorithm for a general multiple testing procedure. We establish conditions that guarantee that the rejections and non‐rejections obtained through Monte Carlo simulations are identical to the ones obtained with the p‐values. Our framework is applicable to a general class of step‐up and step‐down procedures, which includes many established multiple testing corrections such as the ones of Bonferroni, Holm, Sidak, Hochberg or Benjamini–Hochberg. Moreover, we show how to use our framework to improve algorithms available in the literature in such a way as to yield theoretical guarantees on their results. These modifications can easily be implemented in practice and lead to a particular way of reporting multiple testing results as three sets together with an error bound on their correctness, demonstrated exemplarily using a real biological dataset.     

Varieties of legitimacy: a configurational institutional design analysis of eco-labels

Certification is becoming an important global governance instrument. Several authors have discussed the legitimacy of these systems. This paper uses eco-labels as a specific case of certification systems and analyzes more than 400 eco-labels on three components related to legitimacy. It aims to expand current research in two ways: conceptually and empirically. Conceptually, the paper proposes a configurational approach to assessing legitimacy on the basis of the institutional design of certification systems. It is argued that, so far, most attention has gone to the decision-making processes in certification systems with regard to standard-setting and the processes of granting certificates and verification via conformity assessment. While important in assessing legitimacy, these elements should be complemented by accountability mechanisms that allow interested parties to hold organizations to account after a decision has been reached and to raise a dispute. Empirically, the paper makes use of the Ecolabel Index database, which contains data on more than 400 eco-labels operating worldwide. The paper uses the population of eco-labels as a case study to empirically explore and analyze the diversity of more than 400 eco-labels on different institutional components related to legitimacy. The paper shows that there is significant variation between eco-labels with regard to their institutional design, resulting in systems with a strong institutional design and systems with a weak institutional design.     

NATIONAL POLITICS ON TWITTER

The increasing use of Twitter by politicians, journalists, political strategists and citizens has made it an important part of the networked sphere in which political issues are publicly negotiated. The growing number of studies investigating the relationship between Twitter and politics supports this claim. To the knowledge of the authors, this is the first study that examines the interrelation of individuals on the basis of their professions, their topics and their connection to mass media. Taking the example of Austria, they developed a user-centred method that overcomes the limitations inherent to other approaches in this field. The different types of data they gathered – Twitter user data, 1,375 newspaper articles and manually coded 145,356 tweets – allowed them to perform several analyses which provided insights into the structure and topics of a national public Twittersphere. Their results show that the network formed by Austria's most relevant political Twitter users is dominated by an elite of political professionals but open to outside participation. The topic analysis reveals the emergence of niche authorities and the periodic divergence of the political discourse on Twitter with that of mass media. The article concludes with a summary of how these phenomena relate to political participation.     

POLITICAL NETWORKS ON TWITTER

This paper examines patterns of political activity and campaigning on Twitter in the context of the 2012 election in the Australian state of Queensland. Social media have been a visible component of political campaigning in Australia at least since the 2007 federal election, with Twitter, in particular, rising to greater prominence in the 2010 federal election. At state level, however, they have remained comparatively less important thus far. In this paper, uses of Twitter in the Queensland campaign from its unofficial start in February through to the election day of 24 March 2012 are tracked. Using innovative methodologies for analysing Twitter activities, developed by the research team, this study examines the overall patterns of activity in the relevant hashtag #qldvotes, and tracks specific interactions between politicians and other users by following some 80 Twitter accounts of sitting members of parliament and alternative candidates. Such analysis provides new insights into the different approaches to social media campaigning which were embraced by specific candidates and party organizations, as well as an indication of the relative importance of social media activities, at present, for state-level election campaigns.     

Vertrauensunterstützung für sozio-technische ubiquitäre Systeme

Trust has been shown as a crucial factor for the adoption of new technologies. Surprisingly, trust literature offers very little guidance for systematically integrating the vast amount of behavioral trust results into the development of computing systems. The aim of this article is to develop a method for deriving trust supporting components for ubiquitous computing systems. The method is used to derive four trust supporting components for a ubiquitous restaurant recommendation system. Afterwards, the system is evaluated using a laboratory experiment with 166 undergraduate students. The results show that the users’ trust as well as their intention to use the system could be significantly increased. To the best of our knowledge, this is the first article developing and evaluating a method for systematically integrating the behavioral trust results into the development of a computing system and its value.     

Impaired Self-Awareness in Pathological Gamblers

Lack of self-awareness of one’s decisions remains an understudied and elusive topic in the addiction literature. The present study aimed at taking a first step towards addressing this difficult subject through the use of a combination of behavioral procedures. Here, we explored the association between a metacognitive process (the ability to reflect and evaluate the awareness of one’s own decision) and poor performance on the Iowa Gambling Task (IGT) in a group of pathological gamblers (PG; n = 30), and in a comparison group (n = 35). This metacognitive process was assessed during the IGT with the post-decision wagering procedure, while a number of potential confounds (i.e., reward/loss sensitivity, dual-tasking) were controlled for. Results showed that: (1) Initial performance enhancement of the control group on IGT occurred without explicit knowledge of the task, thus confirming its implicit character; (2) compared to controls, performance of PG on the IGT failed to increase during the task; (3) taking into account increased reward sensitivity and decreased loss sensitivity as well as poorer dual-tasking in pathological gamblers, PG tended to exhibit a bias in evaluating their own performance on the IGT by maximizing their wagers independently of selecting advantageous decks. Our findings suggest that biased metacognition may affect pathological gamblers, leading to disadvantageous post-decision wagering, which is in turn linked to impaired decision making under ambiguity. Perhaps this deficit reflects the impaired insight and self-awareness that many addicts suffer from, thus providing a novel approach for capturing and measuring this impairment, and for investigating its possible causes.     

On difference-based variance estimation in nonparametric regression when the covariate is high dimensional

Summary.  We consider the problem of estimating the noise variance in homoscedastic nonparametric regression models. For low dimensional covariates t  ∈  R ^d ,  d =1, 2, difference-based estimators have been investigated in a series of papers. For a given length of such an estimator, difference schemes which minimize the asymptotic mean-squared error can be computed for d =1 and d =2. However, from numerical studies it is known that for finite sample sizes the performance of these estimators may be deficient owing to a large finite sample bias. We provide theoretical support for these findings. In particular, we show that with increasing dimension d this becomes more drastic. If d 4, these estimators even fail to be consistent. A different class of estimators is discussed which allow better control of the bias and remain consistent when d 4. These estimators are compared numerically with kernel-type estimators (which are asymptotically efficient), and some guidance is given about when their use becomes necessary.     

Studienmotivation, Erwerbspartizipation und der Einstieg in den Arbeitsmarkt

Increased student enrollment in public universities has led to a debate on curricula reform with a view to limiting the length of study, particularly by introducing tuition fees for long-time students. It is implicitly assumed in this debate that all students are full-time students. We investigate why and to what extent students participate in the labor market. Furthermore, we study the effects of part-time work on the time it takes to graduate, to find employment and on the level of earnings. We analyze two data sets, first, a survey among students enrolled at the University of Bern conducted during summer 2001 (N = 3360) and secondly, a survey of all university graduates in Switzerland conducted in 2001 (N = 7005). The results show that labor market participation increases the time it takes students to reach graduation. However, labor market experience reduces the time it takes graduates to find employment and increases their earnings by 4 percent if their experience was related to the subject being studied. Labor market participation bearing no relation to university studies has no negative effects on graduate entrance into the labor market. Thus, the study suggests that student participation in the labor market has more beneficial effects than disadvantages. In light of these results curricula reforms should take into account the possibility of gaining labor market experience.