Perception of critical situations involving football fans: dynamics of conflict escalation and de-escalation

Title: The perception of critical situations involving football fans – how conflicts escalate or de-escalate Authors: Brechbühl, A.1, Schumacher, A.1 & Seiler, R.1 1Institute of Sport Science, University of Bern, Switzerland Abstract: Introduction: Fan violence in the context of football matches is a prominent issue in today’s western societies and Switzerland presents no exception. A lot of research has been conducted on reasons for fan violence, mostly with fans of national teams. A prominent model is the Elaborated Social Identity Model (ESIM; Drury & Reicher, 2000): ESIM highlights the importance of interactions between the involved groups and their effect on the development of social identities. Another model is the aggravation mitigation model (AM model; Hylander & Guvå, 2010) which illustrates factors that can contribute towards an escalation or non-escalation of group violence, such as the “categorization” of the opponent group. Despite these models, research about the individual perceptions, and in particular, what factors distinguish between an escalation versus a non-escalation of a potentially violent situation in domestic football, is as yet scarce. This explorative study examines perceptions of critical situations in the domestic football fan context in Switzerland. Methods: An explorative qualitative design was employed to gather data about critical situations (CS) around football matches of two clubs of the Raiffeisen Super League. A CS is defined as a setting in or around the football stadium where violence between football fans and another group could occur. Eight CS were identified and analysed. Fifty-nine narrative interviews with individuals involved in a CS, e.g. fans, police officers or security personnel, were conducted. Interviews were analysed using interpretative phenomenological analysis (IPA). Results: The involved opposing groups expressed group-specific perceptions. Furthermore a strong tendency to negatively stereotype the opponent group was observed. Provocative symbols, such as balaclavas or riot-gear uniforms, were considered as highly relevant for the interpretation of the situation. Successful communication and sufficient distance between opponent groups supported the appeasement of a CS. These findings also underline the importance of knowledge about the local fan culture. This culture serves as basis for the perception of legitimacy, which was assessed to be essential for a de-escalation of a CS by fans. Discussion/Conclusion: This study improves the understanding of fan violence in the domestic football context in Switzerland. Based on the results it is suggested to deploy security or police forces without riot gear but with the goal of seeking dialogue with the fans to increase the likelihood of a peaceful ending in a CS. The findings also support the applicability of the ESIM (Drury & Reicher, 2000) and the AM model (Hylander & Guvå, 2010) in the context of domestic fan violence. Due to possible differences in the local fan cultures in Switzerland, research in this area should be continued. References: Drury, J., & Reicher, S. (2000). Collective action and psychological change: The emergence of new social identities. British Journal of Social Psychology, 39, 579-604. Hylander, I., & Guvå, G. (2010). Misunderstanding of out-group behaviour: Different interpretations of the same crowd events among police officers and demonstrators. Nordic Psychology, 62, 25-47.

A practical approach to designing syndromic surveillance systems for livestock and poultry

The field of animal syndromic surveillance (SyS) is growing, with many systems being developed worldwide. Now is an appropriate time to share ideas and lessons learned from early SyS design and implementation. Based on our practical experience in animal health SyS, with additions from the public health and animal health SyS literature, we put forward for discussion a 6-step approach to designing SyS systems for livestock and poultry. The first step is to formalise policy and surveillance goals which are considerate of stakeholder expectations and reflect priority issues (1). Next, it is important to find consensus on national priority diseases and identify current surveillance gaps. The geographic, demographic, and temporal coverage of the system must be carefully assessed (2). A minimum dataset for SyS that includes the essential data to achieve all surveillance objectives while minimizing the amount of data collected should be defined. One can then compile an inventory of the data sources available and evaluate each using the criteria developed (3). A list of syndromes should then be produced for all data sources. Cases can be classified into syndrome classes and the data can be converted into time series (4). Based on the characteristics of the syndrome-time series, the length of historic data available and the type of outbreaks the system must detect, different aberration detection algorithms can be tested (5). Finally, it is essential to develop a minimally acceptable response protocol for each statistical signal produced (6). Important outcomes of this pre-operational phase should be building of a national network of experts and collective action and evaluation plans. While some of the more applied steps (4 and 5) are currently receiving consideration, more emphasis should be put on earlier conceptual steps by decision makers and surveillance developers (1-3).

Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data

Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.

Evaluation of an inventory for the assessment of critical incidents involving football fans

Introduction: Fan violence is a frequent occurrence in Swiss football (Bundesamt für Polizei, 2015) leading to high costs for prevention and control (Mensch & Maurer, 2014). Various theories put forward an explanation of fan violence, such as the Elaborated Social Identity Model (Drury & Reicher, 2000) and the Aggravation Mitigation Model (Hylander & Guvå, 2010). Important observations from these theories are the multi-dimensional understanding of fan violence and the dynamics occurring in the fan group. Nevertheless, none of them deal with critical incidents (CIs) which involve a tense atmosphere combined with a higher risk of fan violence. Schumacher Dimech, Brechbühl and Seiler (2015) tackled this gap in research and explored CIs where 43 defining criteria were identified and compiled in an integrated model of CIs. The defining criteria were categorised in four higher-order themes “antecedents” (e.g. a documented history of fan rivalry), “triggers” (e.g. the arrest of a fan), “reactions” (e.g. fans masking themselves) and “consequences” (e.g. fans avoiding communication with fan social workers). Methods: An inventory based on this model is being developed including these 43 criteria. In an exploratory phase, this inventory was presented as an online questionnaire and was completed by 143 individuals. Three main questions are examined: Firstly, the individual items are tested using descriptive analyses. An item analysis is conducted to test reliability, item difficulty and discriminatory power. Secondly, the model’s four higher-order themes are tested using exploratory factor analysis (EFA). Thirdly, differences between sub-groups are explored, such as gender and agerelated differences. Results: Respondents rated the items’ importance as high and the quota of incomplete responses was not systematic. Two items were removed from the inventory because of low mean or a high rate of “don’t know”-responses. EFA produced a six-factor solution grouping items into match-related factors, repressive measures, fans’ delinquent behaviour, intra-group behaviour, communication and control and inter-group factors. The item “fans consume alcohol” could not be ordered into any category but was retained since literature accentuates this factor’s influence on fan violence. Analyses examining possible differences between groups are underway. Discussion: Results exploring the adequacy of this inventory assessing defining criteria of CIs in football are promising and thus further evaluative investigation is recommended. This inventory can be used in two ways: as a standardised instrument of assessment for experts evaluating specific CIs and as an instrument for exploring differences in perception and assessment of a CI e.g. gender and age differences, differences between interest groups and stakeholders. References: Bundesamt für Polizei. (2015). Jahresbericht 2014. Kriminalitätsbekämpfung Bund. Lage, Massnahmen und Mittel [Electronic Version]. Drury, J., & Reicher, S. (2000). Collective action and psychological change. The emergence of new social identities. British Journal of Social Psychology, 39, 579-604. Hylander, I., & Guvå, G. (2010). Misunderstanding of out-group behaviour: Different interpretations of the same crowd events among police officers and demonstrators. Nordic Psychology, 62, 25-47. Schumacher-Dimech, A., Brechbühl, A. &, Seiler, R. (2016). Dynamics of critical incidents with potentially violent outcomes involving ultra fans: an explorative study. Sport in Society. Advance online publication. doi: 10.1080/17430437.2015.1133597

The Principle of Common Concern and Climate Change

Effective policies combating global warming and incentivising reduction of greenhouse gases face fundamental collective action problems. States defending short term interests avoid international commitments and seek to benefit from measures combating global warming taken elsewhere. The paper explores the potential of Common Concern as an emerging principle of international law, in particular international environmental law, in addressing collective action problems and the global commons. It expounds the contours of the principle, its relationship to common heritage of mankind, to shared and differentiated responsibility and to public goods. It explores its potential to provide the foundations not only for international cooperation, but also to justify, and delimitate at the same time, unilateral action at home and deploying extraterritorial effects in addressing the challenges of global warming and climate change mitigation. As unilateral measures mainly translate into measures of trade policy, the principle of Common Concern is inherently linked and limited by existing legal disciplines in particular of the law of the World Trade Organization.

The use of mechanisms and modes of toxic action in integrated testing strategies: the report and recommendations of a workshop held as part of the European Union OSIRIS Integrated Project

This report on The Potential of Mode of Action (MoA) Information Derived from Non-testing and Screening Methodologies to Support Informed Hazard Assessment, resulted from a workshop organised within OSIRIS (Optimised Strategies for Risk Assessment of Industrial Chemicals through Integration of Non-test and Test Information), a project partly funded by the EU Commission within the Sixth Framework Programme. The workshop was held in Liverpool, UK, on 30 October 2008, with 35 attendees. The goal of the OSIRIS project is to develop integrated testing strategies (ITS) fit for use in the REACH system, that would enable a significant increase in the use of non-testing information for regulatory decision making, and thus minimise the need for animal testing. One way to improve the evaluation of chemicals may be through categorisation by way of mechanisms or modes of toxic action. Defining such groups can enhance read-across possibilities and priority settings for certain toxic modes or chemical structures responsible for these toxic modes. Overall, this may result in a reduction of in vivo testing on organisms, through combining available data on mode of action and a focus on the potentially most-toxic groups. In this report, the possibilities of a mechanistic approach to assist in and guide ITS are explored, and the differences between human health and environmental areas are summarised.

Keeping citizens, companies, and organizations informed by Web KnowARR

For the main part, electronic government (or e-government for short) aims to put digital public services at disposal for citizens, companies, and organizations. To that end, in particular, e-government comprises the application of Information and Communications Technology (ICT) to support government operations and provide better governmental services (Fraga, 2002) as possible with traditional means. Accordingly, e-government services go further as traditional governmental services and aim to fundamentally alter the processes in which public services are generated and delivered, after this manner transforming the entire spectrum of relationships of public bodies with its citizens, businesses and other government agencies (Leitner, 2003). To implement this transformation, one of the most important points is to inform the citizen, business, and/or other government agencies faithfully and in an accessible way. This allows all the partaking participants of governmental affairs for a transition from passive information access to active participation (Palvia and Sharma, 2007). In addition, by a corresponding handling of the participants' data, a personalization towards these participants may even be accomplished. For instance, by creating significant user profiles as a kind of participants' tailored knowledge structures, a better-quality governmental service may be provided (i.e., expressed by individualized governmental services). To create such knowledge structures, thus known information (e.g., a social security number) can be enriched by vague information that may be accurate to a certain degree only. Hence, fuzzy knowledge structures can be generated, which help improve governmental-participants relationship. The Web KnowARR framework (Portmann and Thiessen, 2013; Portmann and Pedrycz, 2014; Portmann and Kaltenrieder, 2014), which I introduce in my presentation, allows just all these participants to be automatically informed about changes of Web content regarding a- respective governmental action. The name Web KnowARR thereby stands for a self-acting entity (i.e. instantiated form the conceptual framework) that knows or apprehends the Web. In this talk, the frameworks respective three main components from artificial intelligence research (i.e. knowledge aggregation, representation, and reasoning), as well as its specific use in electronic government will be briefly introduced and discussed.