Advantages of upper-class backgrounds: Forms of capital, school cultures and educational performance

In this article, we chart connections between class and educational performance in comparatively egalitarian Norway. While viewing various forms of capital as integral parts of class background, we assess how educational performance is differentiated across the class structure. We use survey and register data to assess differences in grades in three school subjects – mathematics and spoken and written Norwegian – at the individual and school level. We focus on the year of graduation of students at lower-secondary schools in Bergen, Norway’s second largest city by population. Lending credence to Bourdieu’s model of the social space, we find differences according to both capital volume and capital composition. Students from class backgrounds rich in overall capital perform comparatively better than those from humbler class backgrounds. There are also differences within the upper class: those from homes rich in cultural capital perform comparatively better than those from homes rich in economic capital. Although between-school differences are low within the ‘unified’ Norwegian school system, the analysis indicates that grades are associated with the class composition of schools: a high proportion of upper-class students positively correlates with higher grades. In addition, there is some evidence of a collective form of class bias: in one of the school subjects, spoken Norwegian, there is a connection between individual grades and teachers’ perceptions of the culture pervasive at the school in question; this connection is contingent upon a school’s class composition. The analysis thus draws attention to the way in which class bias in grading varies between school subjects.

Facial Emotions Recognition in Machine Learning

Facial expression recognition (FER) is a field where many researchers have tried to create a model able to recognize emotions from a face. With many applications such as interfaces between human and machine, safety or medical, this field has continued to develop with the increase of processing power. This paper contains a broad description on the psychological aspects of the FER and provides a description on the datasets and algorithms that make the neural networks possible. Then a literature review is performed on the recent studies in the facial emotion recognition detailing the methods and algorithms used to improve the capabilities of systems using machine learning. Each interesting aspect of the studies are discussed to highlight the novelty and related concepts and strategies that make the recognition attain a good accuracy. In addition, challenges related to machine learning were discussed, such as overfitting, possible causes and solutions and challenges related to the dataset such as expression unrelated discrepancy such as head orientation, illumination, dataset class bias. Those aspects are discussed in detail, as a review was performed with the difficulties that come with using deep neural networks serving as a guideline to the advancement domain. Finally, those challenges offer an insight in what possible future directions can be taken to develop better FER systems.

Postcolonial Thought and the Emergence of Global Architectural Histories

In the last quarter of the 20th century theories of the postcolonial were usually closely tied to the experience of British and French colonialism in a band of North African, Middle Eastern, and South Asian colonies stretching from Morocco to Malaysia. During this period, Edward Said’s book Orientalism and the early work in subaltern studies both challenged the supposedly dispassionate character of Western scholarship on North Africa and Asia by demonstrating the degree to which it had been skewed by racial and class bias. Although architectural historians took more than a decade to fully absorb its implications, there are few humanities or social sciences disciplines that since the 1990s have been more thoroughly transformed by this once radical shift in perspective, which has changed how the architecture of almost all parts of the world is understood. Whether or not they fully engaged with the theories articulated in scholarship whose initial focus was the analysis of literature, in the case of Said, or of history, in that of subaltern studies, 21st-century architectural historians have paid unprecedented attention to the post-1500 architecture of the Global South, to colonial architecture and its relationship to economic exploitation, to post-independence architecture especially in relation to international modernisms, and to the impact that colonialism had on the architecture of the metropole. While the second and third of these had long been addressed in relation to British settler colonies, architectural history’s global turn meant that they could no longer be considered in isolation from new comprehensive histories of imperialism.

Political Equality and Substantive Representation by Interest Groups

The interest group literature has long struggled with how to empirically approach the normative idea of a non-biased group system. While most previous attempts have focused on the descriptive representation of different types of groups, this article argues that substantive representation of citizens' attitudes is closer to the democratic principle of equal effective participation. It develops a methodological approach that captures substantive representation with respect to agenda priorities and policies by surveying interest groups on how much time they spend on lobbying in different policy areas, and in which direction they lobby on salient policy issues. The responses are compared with opinion data to estimate the level of political (in)equality. The findings from the case of Sweden – where relatively high levels of equality would be expected, but striking levels of inequality based on socio-economic status are instead found – highlight the perseverance of what Schattschneider once called the upper-class bias of the pressure system.

Where is the class bias attenuation? The consequences of adopting compulsory voting in Austria-Hungary in 1907

Adopting compulsory voting (CV) legislation is expected to produce near-universal turnout, which in turn is assumed to iron out class-based differences in political influence and representation. The article traces the historical process generating the sequential adoption of CV in 8 of the 17 Cisleithanian crownlands of the Austro-Hungarian empire in 1907 and 1911, and leverages a difference-in-differences (DiD) method to estimate its causal effect on turnout and voting patterns in elections to the Imperial Council. Exploiting unique data on the turnout of citizens based on their occupational categories, it further examines whether the adoption of CV attenuated class bias in turnout. Despite a large boost to turnout, CV neither increased support for parties representing the working classes, nor attenuated the class bias in turnout.

Whose News? Class-Biased Economic Reporting in the United States

There is substantial evidence that voters’ choices are shaped by assessments of the state of the economy and that these assessments, in turn, are influenced by the news. But how does the economic news track the welfare of different income groups in an era of rising inequality? Whose economy does the news cover? Drawing on a large new dataset of U.S. news content, we demonstrate that the tone of the economic news strongly and disproportionately tracks the fortunes of the richest households, with little sensitivity to income changes among the non-rich. Further, we present evidence that this “class bias” emerges not from pro-rich journalistic preferences but, rather, from the interaction of the media’s focus on economic aggregates with structural features of the relationship between economic growth and distribution. The findings yield a novel explanation of distributionally perverse electoral patterns and demonstrate how the structure of the economy conditions economic accountability.

Writing the history of women’s programming at Telifís Éireann

The history of women’s programming at the Irish television station Teilifís Éireann has long been neglected within the historiography of Irish television. Seminal studies within the field have focused quite specifically on the institutional history of the Irish station and have not paid much attention to programming. This is particularly true in regards to women’s programmes. This paper addresses this gap in the literature by demonstrating a methodological approach for reconstructing this lost segment of programming using the example of Home for Tea, a women’s magazine programme that ran on TÉ from 1964 to 1966. It was the network’s flagship women’s programme during this period but is completely absent from within the scholarship on Irish television. Drawing on the international literature on the history of women’s programmes this paper utilises press sources to reconstruct the Home for Tea’s content and discourse around it. It argues that, though Home for Tea has been neglected, a reconstruction of the programme illuminates wider themes of the everyday at Teilifís Éireann, such as a middle-class bias and the treatment of its actors. As such, its reconstruction, and that of other similar programmes, are exceptionally important in moving towards a more holistic history of the Irish station.

How ethics combine with big data: a bibliometric analysis

The term Big Data is becoming increasingly widespread throughout the world, and its use is no longer limited to the IT industry, quantitative scientific research, and entrepreneurship, but entered as well everyday media and conversations. The prevalence of Big Data is simply a result of its usefulness in searching, downloading, collecting and processing massive datasets. It is therefore not surprising that the number of scientific articles devoted to this issue is increasing. However, the vast majority of research papers deal with purely technical matters. Yet, large datasets coupled with complex analytical algorithms pose the risk of non-transparency, unfairness, e.g., racial or class bias, cherry-picking of data, or even intentional misleading of public opinion, including policymakers, for example by tampering with the electoral process in the context of ‘cyberwars’. Thus, this work implements a bibliometric analysis to investigate the development of ethical concerns in the field of Big Data. The investigation covers articles obtained from the Web of Science Core Collection Database (WoS) published between 1900 and July 2020. A sample size of 892 research papers was evaluated using HistCite and VOSviewer software. The results of this investigation shed light on the evolution of the junction of two concepts: ethics and Big Data. In particular, the study revealed the following array of findings: the topic is relatively poorly represented in the scientific literature with the relatively slow growth of interest. In addition, ethical issues in Big Data are discussed mainly in the field of health and technology.