Educational pathways of minority youth in Norway: intersections of gender, ethnicity and social class

Educational aspirations during lower secondary school and choice of upper secondary education are important for young people’s future trajectories into higher education and labour market positions. In line with ideas about reflexive, autonomous individuals (Giddens, 1991), choice of education is often represented as a young person’ individual decision, and educational guidance as aimed at discovering what ‘fits’ an individual’s personality, interests and abilities. Educational aspirations and choices are also social patterns that are reproduced. Some population categories represent exceptions from expected patterns of social reproduction of educational level and professions. In several countries, one such category is young people from families with migration experiences (Lauglo, 2000; Modood, 2004). In Norway, students have a legal right to non-compulsory upper secondary schooling and 96 percent of the students continue from lower to upper secondary school. In spite of positive developments regarding minority youths’ completion of upper secondary and higher education in later years, studies still persistently show lower educational attainment among minority youth, particularly among boys (Fekjaer, 2006). However, in lower secondary school, minor ity youth tend to have markedly higher educational aspirations and stronger learning motivation than their majority peers, as well as greater effort in school and strong adherence to school values (Lauglo, 2000) despite lower educational attainment or lower socio-economic backgrounds. In addition, gender differences in educational aspirations seem to be smaller among minority youth. The principal objective of the study in progress that will be presented in this paper, is to describe how processes relating to gendered, ethnic and class-based identities influence young people’s educational choices. The study is undertaken as a PhD project in social anthropology. The methodological approach is ethnographic longitudinal fieldwork in two multicultural lower secondary schools in Oslo. The study is part of a larger project that also include quantitative analyses of longitudinal data covering 9th graders in Oslo 2006 through four data collections during lower and upper secondary school.

Indigenous people's mobilization and their struggle for rights in Colombia

This text aims at showing the history of indigenous peoples’ mobilization in Colombia, the effects that it has brought about on Colombian democracy and political system, and the state’s reactions to their claims and actions. It will show how they have moved from class-based claims to a politics where identity claims have been central in their agenda and part of their strategies to negotiate with the state. It will also show the existing constitutional and legal framework that recognizes the rights of indigenous peoples, despite the context of persecution, murder, and forced displacement.

Multinationals, R&D and productivity: Evidence for UK Manufactoring firms

In this study we analyze multinationality (domestic-based firms vs. multinationals) and foreignness (foreign vs. domestic firms) effects in the returns of R&D to productivity. We follow a two-step strategy. In the first step, we consistently ''s productivity by GMM and numerically compute the sample distribution of the R&D returns. In the second step, we use stochastic dominance techniques to make inferences on the multinationality and foreignness effects. Results for a panel of UK manufacturing firms suggest that multinationality and foreignness effects operate in an opposite way: whilst the multinationality effect enhances R&D returns, the foreignness diminishes them.

Automatic Detection of Non-deverbal Event Nouns for Quick Lexicon Production

In this work we present the results of experimental work on the development of lexical class-based lexica by automatic means. Our purpose is to assess the use of linguistic lexical-class based information as a feature selection methodology for the use of classifiers in quick lexical development. The results show that the approach can help reduce the human effort required in the development of language resources significantly.

A data-dependent skeleton estimate and a scale-sensitive dimension for classification

The classical binary classification problem is investigatedwhen it is known in advance that the posterior probability function(or regression function) belongs to some class of functions. We introduceand analyze a method which effectively exploits this knowledge. The methodis based on minimizing the empirical risk over a carefully selected``skeleton'' of the class of regression functions. The skeleton is acovering of the class based on a data--dependent metric, especiallyfitted for classification. A new scale--sensitive dimension isintroduced which is more useful for the studied classification problemthan other, previously defined, dimension measures. This fact isdemonstrated by performance bounds for the skeleton estimate in termsof the new dimension.

Investor protection and income inequality: risk sharing vs risk taking

This paper studies the relationship between investor protection, entrepreneurial risk taking and income inequality. In the presence of market frictions, better protection makes investors more willing to take on entrepreneurial risk when lending to firms, thereby improving the degree of risk sharing between financiers and entrepreneurs. On the other hand, by increasing risk sharing, investor protection also induces more firms to undertake risky projects. By increasing entrepreneurial risk taking, it raises income dispersion. By reducing the risk faced by entrepreneurs, it reduces income volatility. As a result, investor protection raises income inequality to the extent that it fosters risk taking, while it reduces it for a given level of risk taking. Empirical evidence from a panel of forty-five countries spanning the period 1976-2000 supports the predictions of the model.

Towards a real-time vision-based navigation system for a small-class UUV

This paper deals with the problem of navigation for an unmanned underwater vehicle (UUV) through image mosaicking. It represents a first step towards a real-time vision-based navigation system for a small-class low-cost UUV. We propose a navigation system composed by: (i) an image mosaicking module which provides velocity estimates; and (ii) an extended Kalman filter based on the hydrodynamic equation of motion, previously identified for this particular UUV. The obtained system is able to estimate the position and velocity of the robot. Moreover, it is able to deal with visual occlusions that usually appear when the sea bottom does not have enough visual features to solve the correspondence problem in a certain area of the trajectory

Are rules-based government programs shielded from special-interest politics? Evidence from revenue-sharing transfers in Brazil

Manipulation of government finances for the benefit of narrowly defined groups is usuallythought to be limited to the part of the budget over which politicians exercise discretion inthe short run, such as earmarks. Analyzing a revenue-sharing program between the centraland local governments in Brazil that uses an allocation formula based on local population estimates,I document two main results: first, that the population estimates entering the formulawere manipulated and second, that this manipulation was political in nature. Consistent withswing-voter targeting by the right-wing central government, I find that municipalities withroughly equal right-wing and non-right-wing vote shares benefited relative to opposition orconservative core support municipalities. These findings suggest that the exclusive focus ondiscretionary transfers in the extant empirical literature on special-interest politics may understatethe true scope of tactical redistribution that is going on under programmatic disguise.

Community structure in mediterranean shallow lentic ecosystems: size-based vs. taxon-based approaches

The main environmental variables determining the community structure and the functioning of Mediterranean shallow lentic ecosystems are described. These ecosystems are characterized by the unpredictability of their water inputs and the high variability in their water level and physical and chemical composition. Variations in flooding, salinity, and water turnover are determinant in species composition and nutrient dynamics. Taxon-based and size-based approaches to the study of the community structure of aquatic organisms that colonise these ecosystems are also compared. The conventional taxonomic approach, based on the determination of species composition, has been used for the identification of patterns in species richness, distribution and temporal dynamics, and for ecological requirements of species and their potential use as ecological indicators. This taxonbased approach has been compared with a size-based approach, where individuals are classified by their size. Size-based approach gives complementary information about community structure and dynamics, especially when communities are dominated by a single species. The use of size diversity combined with species diversity is suggested for a more complete understanding of community structuring in this type of ecosystem. Detailed examples of two Mediterranean shallow lentic ecosystems, the salt marshes of the Empordà wetlands and the Espolla temporary karstic pond, which differ in hydrology and water origin, are used to discuss the suitability of these different approaches

Spontaneous Speech and Emotional Response modeling based on One-class classifier oriented to Alzheimer Disease diagnosis

The purpose of our project is to contribute to earlier diagnosis of AD and better estimates of its severity by using automatic analysis performed through new biomarkers extracted from non-invasive intelligent methods. The methods selected in this case are speech biomarkers oriented to Sponta-neous Speech and Emotional Response Analysis. Thus the main goal of the present work is feature search in Spontaneous Speech oriented to pre-clinical evaluation for the definition of test for AD diagnosis by One-class classifier. One-class classifi-cation problem differs from multi-class classifier in one essen-tial aspect. In one-class classification it is assumed that only information of one of the classes, the target class, is available. In this work we explore the problem of imbalanced datasets that is particularly crucial in applications where the goal is to maximize recognition of the minority class as in medical diag-nosis. The use of information about outlier and Fractal Dimen-sion features improves the system performance.

Accuracy vs. simplicity: a complex trade-off

Inductive learning aims at finding general rules that hold true in a database. Targeted learning seeks rules for the predictions of the value of a variable based on the values of others, as in the case of linear or non-parametric regression analysis. Non-targeted learning finds regularities without a specific prediction goal. We model the product of non-targeted learning as rules that state that a certain phenomenon never happens, or that certain conditions necessitate another. For all types of rules, there is a trade-off between the rule's accuracy and its simplicity. Thus rule selection can be viewed as a choice problem, among pairs of degree of accuracy and degree of complexity. However, one cannot in general tell what is the feasible set in the accuracy-complexity space. Formally, we show that finding out whether a point belongs to this set is computationally hard. In particular, in the context of linear regression, finding a small set of variables that obtain a certain value of R2 is computationally hard. Computational complexity may explain why a person is not always aware of rules that, if asked, she would find valid. This, in turn, may explain why one can change other people's minds (opinions, beliefs) without providing new information.

A Model-to-model analysis of the repeated Prisoners' Dilemma: genetic algorithms vs. evolutionary dynamics

We study the properties of the well known Replicator Dynamics when applied to a finitely repeated version of the Prisoners' Dilemma game. We characterize the behavior of such dynamics under strongly simplifying assumptions (i.e. only 3 strategies are available) and show that the basin of attraction of defection shrinks as the number of repetitions increases. After discussing the difficulties involved in trying to relax the 'strongly simplifying assumptions' above, we approach the same model by means of simulations based on genetic algorithms. The resulting simulations describe a behavior of the system very close to the one predicted by the replicator dynamics without imposing any of the assumptions of the analytical model. Our main conclusion is that analytical and computational models are good complements for research in social sciences. Indeed, while on the one hand computational models are extremely useful to extend the scope of the analysis to complex scenar

Estudi comparatiu sobre competències parentals de famílies amb dinàmiques violentes vs. famílies amb dinàmiques no violentes ateses al SATAF

A partir de la recerca pilot "Estudi descriptiu de famílies amb dinàmiques de violència domèstica en un context judicial d'ordre civil" es constatà que la valoració tècnica prioritza de forma clara la consideració de les competències i habilitats parentals d'ambdós progenitors quant a formular propostes relacionals. Tenint en compte l'escassa literatura especialitzada quant a les competències parentals de les famílies sotmeses a dinàmiques de violència a la llar, aquest estudi pretén establir una comparativa entre les competències parentals de les famílies ateses al SATAF de Barcelona durant l'any 2008, que presenten dinàmiques amb continguts violents, vs. d'altres famílies que no queden contextualitzades en la violència relacional. Això respon a l'objectiu de constatar l'existència o no de diferències en els estils de criança d'ambdós tipus de famílies, així com si existeixen divergències associades al gènere. A tal fi s'han emprat el test CUIDA i una graella tècnica heteroaplicada per obtenir una mesura de les competències d'aquestes famílies. Els principals resultats obtinguts han partit d'una anàlisi estadística no-paramètrica, considerant el petit tamany de la mostra. A partir d'aquesta anàlisi es copsen diferències entre ambdós tipus de famílies quant a llurs capacitats parentals, així com s'observen dèficits en les mares i pares provinents de dinàmiques violentes. Així mateix, es conclou la dificultat de mesura de les competències parentals a partir de proves d'autoinforme. Finalment, es suggereix el desenvolupament de programes de recuperació i/o millora específics de la parentalitat orientats a aquests progenitors, per tal d'augmentar els nivells de benestar dels seus fills.

Accounting for Big City Growth in Low Paid Occupations: Immigration and/or Service Class Consumption

Growth of 'global cities' in the 1980s was supposed to have involved an occupational polarisation, including growth of low paid service jobs. Though held to be untrue for European cities, at the time, some such growth did emerge in London a decade later than first reported for New York. The question is whether there was simply a delay before London conformed to the global city model, or whether another distinct cause was at work in both cases. This paper proposes that the critical factor in both cases was actually an upsurge of immigration from poor countries providing an elastic supply of cheap labour. This hypothesis and its counterpart based on growth in elite jobs are tested econometrically for the British case with regional data spanning 1975-2008, finding some support for both effects, but with immigration from poor countries as the crucial influence in late 1990s London. Keywords: regional labour markets; wages; employment; international migration; consumer demand JEL Codes: J21, J23, F22, R12

Hierarchical conditional random fields for parts based models matching

A parts based model is a parametrization of an object class using a collection of landmarks following the object structure. The matching of parts based models is one of the problems where pairwise Conditional Random Fields have been successfully applied. The main reason of their effectiveness is tractable inference and learning due to the simplicity of involved graphs, usually trees. However, these models do not consider possible patterns of statistics among sets of landmarks, and thus they sufffer from using too myopic information. To overcome this limitation, we propoese a novel structure based on a hierarchical Conditional Random Fields, which we explain in the first part of this memory. We build a hierarchy of combinations of landmarks, where matching is performed taking into account the whole hierarchy. To preserve tractable inference we effectively sample the label set. We test our method on facial feature selection and human pose estimation on two challenging datasets: Buffy and MultiPIE. In the second part of this memory, we present a novel approach to multiple kernel combination that relies on stacked classification. This method can be used to evaluate the landmarks of the parts-based model approach. Our method is based on combining responses of a set of independent classifiers for each individual kernel. Unlike earlier approaches that linearly combine kernel responses, our approach uses them as inputs to another set of classifiers. We will show that we outperform state-of-the-art methods on most of the standard benchmark datasets.