Towards congruence between teachers’ intentions and practice in intercultural education

ABSTRACT

The purpose of this study is to explore the relationship between teacher beliefs pertaining to cultural diversity and their actual teaching activities. Using a model-based approach, this study looks at beliefs regarding diversity issues at both the theoretical and empirical levels. At the theoretical level, we attempt to systematise the many meanings of ‘beliefs’ found in the literature. At the empirical level, we examine the link between theory, beliefs, and teaching activities relating to diversity, using integrated analysis tools. To accomplish this, we used a qualitative methodological approach to examine the relationship between theory and practice in education. The sample consisted of 45 in-service primary teachers. The first results showed a gap between what teachers tend to say and what they actually do. We argue that future research needs to focus on the effects of teacher beliefs on teacher practice, with special attention devoted to the reflective process.     

Increased risk of emergency department presentations for bronchiolitis in infants exposed to air pollution

Air pollution has been linked to an increased risk of several respiratory diseases in children, especially respiratory tract infections. The present study aims to evaluate the association between pediatric emergency department (PED) presentations for bronchiolitis and air pollution. PED presentations due to bronchiolitis in children aged less than 1 year were retrospectively collected from 2007 to 2018 in Padova, Italy, together with daily environmental data. A conditional logistic regression based on a time-stratified case-crossover design was performed to evaluate the association between PED presentations and exposure to NO₂, PM2.5, and PM10. Models were adjusted for temperature, relative humidity, atmospheric pressure, and public holidays. Delayed effects in time were evaluated using distributed lag non-linear models. Odds ratio for lagged exposure from 0 to 14 days were obtained. Overall, 2251 children presented to the PED for bronchiolitis. Infants’ exposure to higher concentrations of PM10 and PM2.5 in the 5 days before the presentation to the PED increased the risk of accessing the PED by more than 10%, whereas high concentrations of NO₂ between 2 and 12 days before the PED presentation were associated with an increased risk of up to 30%. The association between pollutants and infants who required hospitalization was even greater. A cumulative effect of NO₂ among the 2 weeks preceding the presentation was also observed. In summary, PM and NO₂ concentrations are associated with PED presentations and hospitalizations for bronchiolitis. Exposure of infants to air pollution could damage the respiratory tract mucosa, facilitating viral infections and exacerbating symptoms.     

A unifying view on some problems in probability and statistics

Statistical Methods & Applications - Let $$L$$ be a linear space of real random variables on the measurable space $$(\varOmega ,\mathcal {A})$$ . Conditions for the existence of a probability...     

Extreme ranking analysis in robust ordinal regression

We extend the principle of robust ordinal regression with an analysis of extreme ranking results. In our proposal, we consider the whole set of instances of a preference model that is compatible with preference information provided by the DM. We refer to both, the well-known UTA^GMS method, which builds the set of general additive value functions compatible with DM's preferences, and newly introduced in this paper PROMETHEE^GKS, which constructs the set of compatible outranking models via robust ordinal regression. Then, we consider all complete rankings that follow the use of the compatible preference models, and we determine the best and the worst attained ranks for each alternative. In this way, we are able to assess its position in an overall ranking, and not only in terms of pairwise comparisons, as it is the case in original robust ordinal regression methods. Additionally, we analyze the ranges of possible comprehensive scores (values or net outranking flows). We also discuss extensions of the presented approach on other multiple criteria problems than ranking. Finally, we show how the presented methodology can be applied in practical decision support, reporting results of three illustrative studies.     

Experiments with the Traveler��s Dilemma: welfare, strategic choice and implicit collusion

This article investigates behavior in the Traveler??s Dilemma game and isolates deviations from textbook predictions caused by differences in welfare perceptions and strategic miscalculations. It presents the results of an experimental analysis based on a 2?×?2 design where the own and the other subject??s bonus?Cpenalty parameters are changed independently. We find that the change in own bonus?Cpenalty alone entirely explains the effect on claims of a simultaneous change in one??s own and the other??s bonus?Cpenalty. An increase in the other subject??s bonus?Cpenalty has a significant negative effect on claims when the own bonus?Cpenalty is low, whereas it does not have a significant effect when the own bonus?Cpenalty is high. We also find that expected claims are inconsistent with actual claims in the asymmetric treatments. Focusing on reported strategies, we document substantial heterogeneity and show that changes in choices across treatments are largely explained by risk aversion.     

Improving the measurement of child welfare in the context of intra-household inequality

This study aims to illustrate how to improve the evaluation of child economic well-being and child poverty using the collective approach. International organisations such as the World Bank, OECD and UNICEF have made important efforts in recent years to produce reliable data and to measure poverty according to the most relevant items of household consumption baskets. However, when measuring poverty, it is common practice to assume either that resources are distributed equally within the household or that there are fixed equivalence scales (for example, a child can be counted as 0.5 adults). The methodology based on collective models of consumption overcomes this rigidity by allowing inequality within each household to be taken into account. The method assumes that each household devotes a fraction of resources to children, which can be estimated using the observed expenditure on child-exclusive goods. An example of how child poverty measures can be inaccurately estimated is illustrated through the case of young children in Albania.     

Beyond Markowitz with multiple criteria decision aiding

The paper is about portfolio selection in a non-Markowitz way, involving uncertainty modeling in terms of a series of meaningful quantiles of probabilistic distributions. Considering the quantiles as evaluation criteria of the portfolios leads to a multiobjective optimization problem which needs to be solved using a Multiple Criteria Decision Aiding (MCDA) method. The primary method we propose for solving this problem is an Interactive Multiobjective Optimization (IMO) method based on so-called Dominance-based Rough Set Approach (DRSA). IMO-DRSA is composed of two phases: computation phase, and dialogue phase. In the computation phase, a sample of feasible portfolio solutions is calculated and presented to the Decision Maker (DM). In the dialogue phase, the DM indicates portfolio solutions which are relatively attractive in a given sample; this binary classification of sample portfolios into ‘good’ and ‘others’ is an input preference information to be analyzed using DRSA; DRSA is producing decision rules relating conditions on particular quantiles with the qualification of supporting portfolios as ‘good’; a rule that best fits the current DM’s preferences is chosen to constrain the previous multiobjective optimization in order to compute a new sample in the next computation phase; in this way, the computation phase yields a new sample including better portfolios, and the procedure loops a necessary number of times to end with the most preferred portfolio. We compare IMO-DRSA with two representative MCDA methods based on traditional preference models: value function (UTA method) and outranking relation (ELECTRE IS method). The comparison, which is of methodological nature, is illustrated by a didactic example.     

Modified quasi-profile likelihoods from estimating functions

We discuss higher-order adjustments for a quasi-profile likelihood for a scalar parameter of interest, in order to alleviate some of the problems inherent to the presence of nuisance parameters, such as bias and inconsistency. Indeed, quasi-profile score functions for the parameter of interest have bias of order O(1)$\mathrm{O}(1)$, and such bias can lead to poor inference on the parameter of interest. The higher-order adjustments are obtained so that the adjusted quasi-profile score estimating function is unbiased and its variance is the negative expected derivative matrix of the adjusted profile estimating equation. The modified quasi-profile likelihood is then obtained as the integral of the adjusted profile estimating function. We discuss two methods for the computation of the modified quasi-profile likelihoods: a bootstrap simulation method and a first-order asymptotic expression, which can be simplified under an orthogonality assumption. Examples in the context of generalized linear models and of robust inference are provided, showing that the use of a modified quasi-profile likelihood ratio statistic may lead to coverage probabilities more accurate than those pertaining to first-order Wald-type confidence intervals.     

Chain graph models: topological sorting of meta-arrows and efficient construction of $${\mathcal{B}}$$ -essential graphs

Essential graphs and largest chain graphs are well-established graphical representations of equivalence classes of directed acyclic graphs and chain graphs respectively, especially useful in the context of model selection. Recently, the notion of a labelled block ordering of vertices was introduced as a flexible tool for specifying subfamilies of chain graphs. In particular, both the family of directed acyclic graphs and the family of “unconstrained” chain graphs can be specified in this way, for the appropriate choice of . The family of chain graphs identified by a labelled block ordering of vertices is partitioned into equivalence classes each represented by means of a -essential graph. In this paper, we introduce a topological ordering of meta-arrows and use this concept to devise an efficient procedure for the construction of -essential graphs. In this way we also provide an efficient procedure for the construction of both largest chain graphs and essential graphs. The key feature of the proposed procedure is that every meta-arrow needs to be processed only once.     

Shaping Dimensions of Urban Complexity: The Role of Economic Structure and Socio-Demographic Local Contexts

Social Indicators Research - Diversification in urban functions—a key component of urban complexity—was analysed using Pielou’s evenness indexes for 12 socioeconomic dimensions...