205 resultados para Ethnicity homosexuality homophobia discrimination Sri Lanka Shyam Selvadurai Funny Boy diaspora alienation


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Interpreting the unexplained component of the gender wage gap as indicative of discrimination, the empirical literature to date has tended to ignore the potential impact wage discrimination may have on employment. Clearly, employment effects will arise if discrimination lowers the female offered wage and the labour supply curve is upward sloping. The empirical analysis employs the ABS Income Distribution Survey 1994–95 and finds evidence of both wage and associated employment effects. The analysis is replicated for the earlier period 1989–90. A comparison across time is of interest given the substantial deregulation of the Australian labour market over the period.

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Interpreting the unexplained component of the gender wage gap as indicative of discrimination, the empirical literature to date has tended to ignore the potential impact wage discrimination may have on employment. Employment effects may arise if discrimination lowers the female offered wage and the labour supply curve is upward sloping. The empirical analysis employs the British Household Panel Study and finds evidence of both wage and associated employment effects.

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This work aims to contribute to reliability and integrity in perceptual systems of autonomous ground vehicles. Information theoretic based metrics to evaluate the quality of sensor data are proposed and applied to visual and infrared camera images. The contribution of the proposed metrics to the discrimination of challenging conditions is discussed and illustrated with the presence of airborne dust and smoke.

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In this paper we present a unified sequential Monte Carlo (SMC) framework for performing sequential experimental design for discriminating between a set of models. The model discrimination utility that we advocate is fully Bayesian and based upon the mutual information. SMC provides a convenient way to estimate the mutual information. Our experience suggests that the approach works well on either a set of discrete or continuous models and outperforms other model discrimination approaches.

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Australia has been populated for more than 40,000 years with Indigenous Australians joined by European settlers only 230 years ago. The first settlers consisted of convicts from more than 28 countries and members of the British army who arrived in 1788 to establish a British penal colony. Mass migration in the nineteenth century with one and a half million immigrants from Europe, principally from the United Kingdom and Ireland (Haines and Shlomowitz, 1992), established the continent as an Anglo society in the Pacific. In the twentieth century immigrants came from many European countries and in the latter decades from many parts of Asia and the Middle East (Collins, 1991, pp.10-13). In the 21st century Australia has an ethnically and culturally diverse population. The original Indigenous population of Australia accounts for approximately 460,000 or 2.5 per cent of the total population (ABS, 2006a). Estimates are that around 4.5m. persons in the population (close to 20 per cent), were born outside Australia with the majority of these arriving from Europe, principally the United Kingdom, and New Zealand (ABS, 2006b). Like many other countries, Australia has a legacy of discrimination and inequality in employment. Propelled by racist ideologies and the male breadwinner ideology, Indigenous Australians, and non-European immigrants, and women were barred from certain jobs and paid less for their work than any white male counterpart. These conditions were legally sanctioned through the industrial relations system and other laws in the nineteenth and first half of the twentieth century. Since the 1960s a dramatic change has occurred in social policy and national legislation and Australia today has an extensive array of laws which forbid employment discrimination on race, ethnicity, gender and many other characteristics, and other approaches which promote proactive organizational plans and actions to achieve equity in employment. This chapter outlines these developments.

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Measurement of discrimination against 18O during dark respiration in plants is currently accepted as the only reliable method of estimating the partitioning of electrons between the cytochrome and alternative pathways. In this paper, we review the theory of the technique and its application to a gas-phase system. We extend it to include sampling effects and show that the isotope discrimination factor, D, is calculated as –dln(1 + δ)/dlnO*, where δ is isotopic composition of the substrate oxygen and O*=[O2]/[N2] in a closed chamber containing tissue respiring in the dark. It is not necessary to integrate the expression but, if the integrated form is used, the resultant regression should not be constrained through the origin. This is important since any error in D will have significant effects on the estimation of the flux of electrons through the two pathways.

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As many other chapters in this book have noted, until recently labour lawyers have tended not to draaw on regulatory scholarship. In this chapter we look at certain areas of labour law through a particular kind of regulatory lens - regulation that requires firms to reconstitute their management processes and procedures, perhaps even their organisational cultures. In particular, we examine the kinds of regulatory demands made on firms by legal rules in four areas of labour law: (i) occupational health and safety (OHS)regulation; unfair dismissal law; equal opportunity (EO) and (iv) sexual harassment law.

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The purpose of this study was to investigate the nature and prevalence of discrimination against people living with HIV/AIDS in West Bengal, India, and how discrimination is associated with depression, suicidal ideation and suicidal attempts. Semi-structured interviews and the Beck Depression Inventory were administered to 105 HIV infected persons recruited by incidental sampling, at an Integrated Counseling and Testing Center (ICTC) and through Networks of People Living with HIV/AIDS, in the West Bengal area. Findings showed that 40.8% of the sample has experienced discrimination at least in one social setting – such as family (29.1%), health centers (18.4%), community (17.5%) and workplace (6.8%). About two-fifths (40.8%) reported experiencing discrimination in multiple social settings. Demographic factors associated with discrimination were gender, age, occupation, education, and current residence. More than half of the sample was suffering from severe depression while 8.7% had attempted suicide. Discrimination in most areas was significantly associated with suicidal ideation and suicidal attempts. Prevalence of discrimination associated with HIV/AIDS is high in our sample from West Bengal. While discrimination was not associated with depressive symptomatology, discrimination was associated with suicidal ideation and attempts. These findings suggest that there is an urgent need for interventions to reduce discrimination of HIV/AIDS in the West Bengal region.

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Selection of features that will permit accurate pattern classification is a difficult task. However, if a particular data set is represented by discrete valued features, it becomes possible to determine empirically the contribution that each feature makes to the discrimination between classes. This paper extends the discrimination bound method so that both the maximum and average discrimination expected on unseen test data can be estimated. These estimation techniques are the basis of a backwards elimination algorithm that can be use to rank features in order of their discriminative power. Two problems are used to demonstrate this feature selection process: classification of the Mushroom Database, and a real-world, pregnancy related medical risk prediction task - assessment of risk of perinatal death.

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We propose expected attainable discrimination (EAD) as a measure to select discrete valued features for reliable discrimination between two classes of data. EAD is an average of the area under the ROC curves obtained when a simple histogram probability density model is trained and tested on many random partitions of a data set. EAD can be incorporated into various stepwise search methods to determine promising subsets of features, particularly when misclassification costs are difficult or impossible to specify. Experimental application to the problem of risk prediction in pregnancy is described.