Electronic voting systems in undergraduate teaching

One of the major differences undergraduates experience during the transition to university is the style of teaching. In schools and colleges most students study key stage 5 subjects in relatively small informal groups where teacher–pupil interaction is encouraged and two-way feedback occurs through question and answer type delivery. On starting in HE students are amazed by the sizes of the classes. For even a relatively small chemistry department with an intake of 60-70 students, biologists, pharmacists, and other first year undergraduates requiring chemistry can boost numbers in the lecture hall to around 200 or higher. In many universities class sizes of 400 are not unusual for first year groups where efficiency is crucial. Clearly the personalised classroom-style delivery is not practical and it is a brave student who shows his ignorance by venturing to ask a question in front of such an audience. In these environments learning can be a very passive process, the lecture acts as a vehicle for the conveyance of information and our students are expected to reinforce their understanding by ‘self-study’, a term, the meaning of which, many struggle to understand. The use of electronic voting systems (EVS) in such situations can vastly change the students’ learning experience from a passive to a highly interactive process. This principle has already been demonstrated in Physics, most notably in the work of Bates and colleagues at Edinburgh.1 These small hand-held devices, similar to those which have become familiar through programmes such as ‘Who Wants to be a Millionaire’ can be used to provide instant feedback to students and teachers alike. Advances in technology now allow them to be used in a range of more sophisticated settings and comprehensive guides on use have been developed for even the most techno-phobic staff.

Voting rights of refugees

The book develops a novel legal argument about the voting rights of recognised 1951 Geneva Convention Refugees. The main normative contention is that such refugees should have the right to vote in the political community where they reside, assuming that the political community is a democracy and that its citizens have the right to vote. The basis of this contention is that the right to political participation in some political community is a basic right from the point of view of dignity and the protection of one’s interests. Due to their unique political predicament, 1951 Geneva Convention Refugees are a special category of non-citizen residents. They are unable to participate in elections of their state of origin, do not enjoy its diplomatic protection and consular assistance abroad, and – most fundamentally – are unable or unwilling, owing to a well-founded fear of persecution, to return to it; thus, they are in limbo for a potentially protracted period. Refugees, too, deserve to have a place in the world in the Arendtian sense, where their opinions are significant and their actions are effective. Their state of asylum is, for the time being, the only community in which there is any realistic prospect of political participation on their part.

Cheap dates and the delusion of gratification: are votes sold or traded in the EU Council of Ministers?

Each year, small Member States receive a disproportionate share of the European Union's (EU's) budget. A prominent explanation for this is that Council decision-making involves a healthy dose of vote selling, whereby large Member States offer small states generous fiscal transfers in exchange for influence over policy. But nobody has investigated whether net budget contributors actually get anything for their money. In this paper I identify the vote selling model's observable implications and find virtually no evidence consistent with Council cash-for-votes exchanges. I also show that a compromise model – the leading model of EU decision-making to date – modified to incorporate vote selling does not outperform a standard one that assumes votes are traded rather than sold. Taken together, the results suggest that Council decision-making operates with little or no vote selling, and that regardless of whatever they think they might be buying, net budget contributors get little or nothing in return for their money. These findings call for further investigation into how Member States approach the issue of fiscal transfers, and into the factors other than formal voting weight that affect the power of actors engaged in EU decision-making.

The impact of Group Intelligence software on enquiry-based learning

Despite the increasing use of groupware technologies in education, there is little evidence of their impact, especially within an enquiry-based learning (EBL) context. In this paper, we examine the use of a commercial standard Group Intelligence software called GroupSystems®ThinkTank. To date, ThinkTank has been adopted mainly in the USA and supports teams in generating ideas, categorising, prioritising, voting and multi-criteria decision-making and automatically generates a report at the end of each session. The software was used by students carrying out an EBL project, set by employers, for a full academic year. The criteria for assessing the impact of ThinkTank on student learning were those of creativity, participation, productivity, engagement and understanding. Data was collected throughout the year using a combination of interviews and questionnaires, and written feedback from employers. The overall findings show an increase in levels of productivity and creativity, evidence of a deeper understanding of their work but some variation in attitudes towards participation in the early stages of the project.

Identifying key knowledge needs for evidence-based conservation of wild insect pollinators: a collaborative cross-sectoral exercise

In response to evidence of insect pollinator declines, organisations in many sectors, including the food and farming industry, are investing in pollinator conservation. They are keen to ensure that their efforts use the best available science. We convened a group of 32 ‘conservation practitioners’ with an active interest in pollinators and 16 insect pollinator scientists. The conservation practitioners include representatives from UK industry (including retail), environmental non-government organisations and nature conservation agencies. We collaboratively developed a long list of 246 knowledge needs relating to conservation of wild insect pollinators in the UK. We refined and selected the most important knowledge needs, through a three-stage process of voting and scoring, including discussions of each need at a workshop. We present the top 35 knowledge needs as scored by conservation practitioners or scientists. We find general agreement in priorities identified by these two groups. The priority knowledge needs will structure ongoing work to make science accessible to practitioners, and help to guide future science policy and funding. Understanding the economic benefits of crop pollination, basic pollinator ecology and impacts of pesticides on wild pollinators emerge strongly as priorities, as well as a need to monitor floral resources in the landscape.

Priority research questions for the UK food system

The rise of food security up international political, societal and academic agendas has led to increasing interest in novel means of improving primary food production and reducing waste. There are however, also many ‘post-farm gate’ activities that are critical to food security, including processing, packaging, distributing, retailing, cooking and consuming. These activities all affect a range of important food security elements, notably availability, affordability and other aspects of access, nutrition and safety. Addressing the challenge of universal food security, in the context of a number of other policy goals (e.g. social, economic and environmental sustainability), is of keen interest to a range of UK stakeholders but requires an up-to-date evidence base and continuous innovation. An exercise was therefore conducted, under the auspices of the UK Global Food Security Programme, to identify priority research questions with a focus on the UK food system (though the outcomes may be broadly applicable to other developed nations). Emphasis was placed on incorporating a wide range of perspectives (‘world views’) from different stakeholder groups: policy, private sector, non-governmental organisations, advocacy groups and academia. A total of 456 individuals submitted 820 questions from which 100 were selected by a process of online voting and a three-stage workshop voting exercise. These 100 final questions were sorted into 10 themes and the ‘top’ question for each theme identified by a further voting exercise. This step also allowed four different stakeholder groups to select the top 7–8 questions from their perspectives. Results of these voting exercises are presented. It is clear from the wide range of questions prioritised in this exercise that the different stakeholder groups identified specific research needs on a range of post-farm gate activities and food security outcomes. Evidence needs related to food affordability, nutrition and food safety (all key elements of food security) featured highly in the exercise. While there were some questions relating to climate impacts on production, other important topics for food security (e.g. trade, transport, preference and cultural needs) were not viewed as strongly by the participants.

Does political proximity to the U.S. cause terror?

We analyze the impact of political proximity to the United States on the occurrence and severity of terror. Employing panel data for 116 countries over the period 1975–2001 we find that countries voting in line with the U.S. are victims of more and deadlier attacks.

How large is congressional dependence in agriculture. Bayesian inference about ‘scale’ and ‘scope’ in measuring a spatial externality

The political economy literature on agriculture emphasizes influence over political outcomes via lobbying conduits in general, political action committee contributions in particular and the pervasive view that political preferences with respect to agricultural issues are inherently geographic. In this context, ‘interdependence’ in Congressional vote behaviour manifests itself in two dimensions. One dimension is the intensity by which neighboring vote propensities influence one another and the second is the geographic extent of voter influence. We estimate these facets of dependence using data on a Congressional vote on the 2001 Farm Bill using routine Markov chain Monte Carlo procedures and Bayesian model averaging, in particular. In so doing, we develop a novel procedure to examine both the reliability and the consequences of different model representations for measuring both the ‘scale’ and the ‘scope’ of spatial (geographic) co-relations in voting behaviour.

Risk aversion, overconfidence and private information as determinants of majority thresholds

We present and experimentally test a theoretical model of majority threshold determination as a function of voters’ risk preferences. The experimental results confirm the theoretical prediction of a positive correlation between the voter's risk aversion and the corresponding preferred majority threshold. Furthermore, the experimental results show that a voter's preferred majority threshold negatively relates to the voter's confidence about how others will vote. Moreover, in a treatment in which individuals receive a private signal about others’ voting behaviour, the confidence-related motivation of behaviour loses ground to the signal's strength.

A Genetic Algorithm for the selection of structural MRI features for classification of Mild Cognitive Impairment and Alzheimer's Disease

This work investigates the problem of feature selection in neuroimaging features from structural MRI brain images for the classification of subjects as healthy controls, suffering from Mild Cognitive Impairment or Alzheimer’s Disease. A Genetic Algorithm wrapper method for feature selection is adopted in conjunction with a Support Vector Machine classifier. In very large feature sets, feature selection is found to be redundant as the accuracy is often worsened when compared to an Support Vector Machine with no feature selection. However, when just the hippocampal subfields are used, feature selection shows a significant improvement of the classification accuracy. Three-class Support Vector Machines and two-class Support Vector Machines combined with weighted voting are also compared with the former and found more useful. The highest accuracy achieved at classifying the test data was 65.5% using a genetic algorithm for feature selection with a three-class Support Vector Machine classifier.