Telling stories of 21st Century welfare: the UK Coalition Government and the neo-liberal discourse of worklessness and dependency’ Critical Social Policy

Policy documents are a useful source for understanding the privileging of particular ideological and policy preferences (Scrase and Ockwell, 2010) and how the language and imagery may help to construct society’s assumptions, values and beliefs. This article examines how the UK Coalition government’s 2010 Green Paper, 21st Century Welfare, and the White Paper, Universal Credit: Welfare that Works, assist in constructing a discourse about social security that favours a renewal and deepening of neo-liberalization in the context of threats to its hegemony. The documents marginalize the structural aspects of persistent unemployment and poverty by transforming these into individual pathologies of benefit dependency and worklessness. The consequence is that familiar neo-liberal policy measures favouring the intensification of punitive conditionality and economic rationality can be portrayed as new and innovative solutions to address Britain’s supposedly broken society and restore economic competitiveness.

‘Government(ality) By Experts: Human Rights as Governance’

The suggestion that the general economy of power in our societies is becoming a domain of security was made by Michel Foucault in the late 1970s. This paper takes inspiration from Foucault?s work to interpret human rights as technologies of governmentality, which make possible the safe and secure society. I examine, by way of illustration, the site of the European Union and its use of new modes of governance to regulate rights discourse – in particular via the emergence of a new Fundamental Rights Agency. „Governance? in the EU is constructed in an apolitical way, as a departure from traditional legal and juridical methods of governing. I argue, however, that the features of governance represent technologies of government(ality), a new form of both being governed through rights and of governing rights. The governance feature that this article is most interested in is experts. The article aims to show, first and foremost, how rights operate as technologies of governmentality via a new relation to expertise. Second, it considers the significant implications that this reading of rights has for rights as a regulatory and normalising discourse. Finally, it highlights how the overlap between rights and governance discourses can be problematic because (as the EU model illustrates) governance conceals the power relations of governmentality, allowing, for instance, the unproblematic representation of the EU as an international human rights actor

‘Towards a Concrete Utopian Model of Green Political Economy’

Much of the thinking about the appropriate ‘political economy’ to underpin sustainable development has been either utopian (as in some ‘green’ political views) or ‘business as usual’ approaches. This article suggests that ‘ecological modernisation’ is the dominant conceptualisation of ‘sustainable development’ within the UK and other ‘developed’ Northern polities and most corporate/business interests, and illustrates this by looking at some key ‘sustainable development’ policy documents from the UK Government. While critical of the reformist ‘policy telos’ of ecological modernisation, supporters of a more radical version of sustainable development need to also be aware of the strategic opportunities of this policy discourse. In particular, the article suggests that the discourse of ‘economic security’, which can be attached to a radicalised notion of ecological modernisation, ought to be used as a way of articulating a radical, robust and principled understanding of sustainable development, which offers a normatively compelling and policy-relevant path to outlining aspects of a ‘green political economy’ to underpin sustainable development.

The Government – Voluntary Sector Compacts: Governance, Governmentality and Civil Society

In 1998 government and the main representatives of the voluntary sector in each of the four countries in the United Kingdom published "compacts" on relations between government and the voluntary sector. These were joint documents, carrying forward ideas expressed by the Labor Party when in opposition, and directed at developing a new relationship for partnership with those "not-for-profit organizations" that are involved primarily in the areas of policy and service delivery. This article seeks to use an examination of the compacts, and the processes that produced them and that they have now set in train, to explore some of the wider issues about the changing role of government and its developing relationships with civil society. In particular, it argues that the new partnership builds upon a movement from welfarism to economism which is being developed further through the compact process. Drawing upon a governmentality approach, and illustrating the account with interview material obtained from some of those involved in compact issues from within both government and those umbrella groups which represent the voluntary sector, an argument is made that this overall process represents the beginning of a new reconfiguration of the state that is of considerable constitutional significance.

Gender Classification via Lips: Static and Dynamic Features

Automatic gender classification has many security and commercial applications. Various modalities have been investigated for gender classification with face-based classification being the most popular. In some real-world scenarios the face may be partially occluded. In these circumstances a classification based on individual parts of the face known as local features must be adopted. We investigate gender classification using lip movements. We show for the first time that important gender specific information can be obtained from the way in which a person moves their lips during speech. Furthermore our study indicates that the lip dynamics during speech provide greater gender discriminative information than simply lip appearance. We also show that the lip dynamics and appearance contain complementary gender information such that a model which captures both traits gives the highest overall classification result. We use Discrete Cosine Transform based features and Gaussian Mixture Modelling to model lip appearance and dynamics and employ the XM2VTS database for our experiments. Our experiments show that a model which captures lip dynamics along with appearance can improve gender classification rates by between 16-21% compared to models of only lip appearance.

The Disrupted Space: Safety and Security in traditional contexts

One of the core elements of successful planning is the individuals’ experience of their shared open spaces. This paper attributes to the relationship between safety and urban design by means of natural surveillance and security in the city’s shared spaces. It examines how political claims over space reassembled alternative definitions of security in one of Cairo’s oldest quarters, and how ambitious planning schemes were mostly driven by problems of insecurity, chaos and disorder. The main crux to this account is based on original documents, interviews and maps which reveals considerable insights and accounts of how this vision affected the quarter’s spatial quality and the user’s reactions to his new spatial formula. It also reveals conflicting conceptions of safety and security between the planning ambitions and the users experiences, which not only lacked reliable visions for securing the quarter, but also resulted further disruption to their everyday living spaces.

Analysis of Bayesian classification-based approaches for Android malware detection

Mobile malware has been growing in scale and complexity spurred by the unabated uptake of smartphones worldwide. Android is fast becoming the most popular mobile platform resulting in sharp increase in malware targeting the platform. Additionally, Android malware is evolving rapidly to evade detection by traditional signature-based scanning. Despite current detection measures in place, timely discovery of new malware is still a critical issue. This calls for novel approaches to mitigate the growing threat of zero-day Android malware. Hence, the authors develop and analyse proactive machine-learning approaches based on Bayesian classification aimed at uncovering unknown Android malware via static analysis. The study, which is based on a large malware sample set of majority of the existing families, demonstrates detection capabilities with high accuracy. Empirical results and comparative analysis are presented offering useful insight towards development of effective static-analytic Bayesian classification-based solutions for detecting unknown Android malware.

Classification the geographical origin of corn distillers dried grains with solubles by near infrared reflectance spectroscopy combined with chemometrics: A feasibility study

In this study, 137 corn distillers dried grains with solubles (DDGS) samples from a range of different geographical origins (Jilin Province of China, Heilongjiang Province of China, USA and Europe) were collected and analysed. Different near infrared spectrometers combined with different chemometric packages were used in two independent laboratories to investigate the feasibility of classifying geographical origin of DDGS. Base on the same dataset, one laboratory developed a partial least square discriminant analysis model and another laboratory developed an orthogonal partial least square discriminant analysis model. Results showed that both models could perfectly classify DDGS samples from different geographical origins. These promising results encourage the development of larger scale efforts to produce datasets which can be used to differentiate the geographical origin of DDGS and such efforts are required to provide higher level food security measures on a global scale.

Inside the tent: Community and government in refugee camps

Refugee camps are increasingly managed through a liberal rationality of government similar to that of many industrialized societies, with security mechanisms being used to optimize the life of particular refugee populations. This governmentality has encompassed programmes introduced by the United Nations High Commissioner for Refugees (UNHCR) and various non-governmental organizations (NGOs) to build and empower communities through the spatial technology of the camp. The present article argues that such attempts to ‘govern through community’ have been too easily dismissed or ignored. It therefore examines how such programmes work to produce, manage and conduct refugees through the use of a highly instrumentalized understanding of community in the spatial and statistical management of displaced people in camps. However, community is always both more and less than what is claimed of it, and therefore undermines attempts to use it as a governing tactic. By shifting to a more ontological understanding of community as unavoidable coexistence, inspired by Jean-Luc Nancy, we can see how the scripting of and government through community in camps is continually exceeded, redirected and resisted. Ethnographies of specific camps in Africa and the Middle East enable us both to see how the necessary sociality of being resists its own instrumentalization and to view the camp as a spatial security technology. Such resistance does not necessarily lead to greater security, but it redirects our attention to how community is used to conduct the behaviour of refugees, while also producing counter-conducts that offer greater agency, meaning and mobility to those displaced in camps.

Twitter Sentiment Analysis for Security-Related Information Gathering

Analysing public sentiment about future events, such as demonstration or parades, may provide valuable information while estimating the level of disruption and disorder during these events. Social media, such as Twitter or Facebook, provides views and opinions of users related to any public topics. Consequently, sentiment analysis of social media content may be of interest to different public sector organisations, especially in the security and law enforcement sector. In this paper we present a lexicon-based approach to sentiment analysis of Twitter content. The algorithm performs normalisation of the sentiment in an effort to provide intensity of the sentiment rather than positive/negative label. Following this, we evaluate an evidence-based combining function that supports the classification process in cases when positive and negative words co-occur in a tweet. Finally, we illustrate a case study examining the relation between sentiment of twitter posts related to English Defence League and the level of disorder during the EDL related events.

Select Document: Sir George Radcliffe’s “Original of Government” (1639) and Absolutist Political Theory in Stuart Ireland

A seventeenth-century manuscript miscellany, which once belonged to Archbishop James Ussher of Armagh, contains a short treatise on the origins of government by Sir George Radcliffe. Radcliffe was legal assistant to Sir Thomas Wentworth, lord deputy of Ireland (from January 1640 earl of Strafford and lord lieutenant). The treatise insisted on the divine origin of all human political power and implied that the best form of government was absolute monarchy, in which the monarch was free of all human law and subject to divine restraint alone. It will be suggested below that the composition of this treatise can be dated to the summer of 1639. This introduction will offer an outline of Radcliffe’s education and political career, explain the genesis of his treatise on government, point out some pertinent aspects of its argument, and finally assess the document’s significance.

Machine learning classification of surgical pathology reports and chunk recognition for information extraction noise reduction

Background and aims: Machine learning techniques for the text mining of cancer-related clinical documents have not been sufficiently explored. Here some techniques are presented for the pre-processing of free-text breast cancer pathology reports, with the aim of facilitating the extraction of information relevant to cancer staging.

Materials and methods: The first technique was implemented using the freely available software RapidMiner to classify the reports according to their general layout: ‘semi-structured’ and ‘unstructured’. The second technique was developed using the open source language engineering framework GATE and aimed at the prediction of chunks of the report text containing information pertaining to the cancer morphology, the tumour size, its hormone receptor status and the number of positive nodes. The classifiers were trained and tested respectively on sets of 635 and 163 manually classified or annotated reports, from the Northern Ireland Cancer Registry.

Results: The best result of 99.4% accuracy – which included only one semi-structured report predicted as unstructured – was produced by the layout classifier with the k nearest algorithm, using the binary term occurrence word vector type with stopword filter and pruning. For chunk recognition, the best results were found using the PAUM algorithm with the same parameters for all cases, except for the prediction of chunks containing cancer morphology. For semi-structured reports the performance ranged from 0.97 to 0.94 and from 0.92 to 0.83 in precision and recall, while for unstructured reports performance ranged from 0.91 to 0.64 and from 0.68 to 0.41 in precision and recall. Poor results were found when the classifier was trained on semi-structured reports but tested on unstructured.

Conclusions: These results show that it is possible and beneficial to predict the layout of reports and that the accuracy of prediction of which segments of a report may contain certain information is sensitive to the report layout and the type of information sought.