Although evictions are a significant cause of homelessness they have received relatively little interest from social scientists. International data are scarce and there are few descriptions of the processes leading to evictions. This paper attempts to shed some light on this under-researched issue. First, an attempt is made to develop a theoretical framework placing evictions in the intersection between civil and social citizenship, and the importance of distinguishing between the macro- and micro- levels in the analysis of evictions is underlined. Secondly, three specific countries are studied: Germany, the Netherlands and Sweden. The legal basis for evictions, eviction procedures, and the possibilities for avoiding homelessness arising from rent arrears are presented and compared.
Tipping is a social norm in many countries and has important functions as a source of income, with significant social welfare effects. Tipping can also represent a form of lost tax revenue, as service workers and restaurants may not declare all cash tips. These interrelationships remain generally insufficiently understood. This paper presents the results of a comparative survey of resident tipping patterns in restaurants in Spain, France, Germany, Switzerland, Sweden, Norway, and the Netherlands. ANOVA and ANCOVA analyses confirm significant variation in tipping norms between countries, for instance with regard to the frequency of tipping and the proportion of tips in relation to bill size. The paper discusses these findings in the context of employment conditions and social welfare effects, comparing the European Union minimum wage model to gratuity-depending income approaches in the USA. Results have importance for the hospitality sector and policymakers concerned with social welfare
MULTIFILE
The impacts of tourism on destinations and the perceptions of local communities have been a major concern both for the industry and research in the past decades. However, tourism planning has been mainly focused on traditions that promote the increase of tourism without taking under consideration the wellbeing of both residents and visitors. To develop a more sustainable tourism model, the inclusion of local residents in tourism decision-making is vital. However, this is not always possible due to structural, economic and socio-cultural restrictions that residents face resulting to their disempowerment. This study aims to explore and interpret the formal processes around tourism decision-making and community empowerment in urban settings. The research proposes a comparative study of three urban destinations in Europe (The Hague in the Netherlands, San Sebastian in Spain and, Ioannina in Greece) that experience similar degree of tourism growth. The proposed study will use a design-based approach in order to understand tourism decision-making and what empowers or disempowers community participation within the destinations. Based on the findings of primary and secondary data, a community empowerment model will be applied in one the destinations as a pilot for resident engagement in tourism planning. The evaluation of the pilot will allow for an optimized model to be created with implications for tourism planning at a local level that can contribute to sustainable destinations that safeguard the interests of local residents and tourists.
Dit project heeft tot doel het ontwerp en de exploitatie van lokale energiesystemen te verbeteren voor buurten met een hoge zelfvoorziening en een hoge betrokkenheid van alle betrokken belanghebbenden. In dit project wordt een integrale aanpak toegepast door zowel technische als sociale aspecten mee te nemen.
Human kind has a major impact on the state of life on Earth, mainly caused by habitat destruction, fragmentation and pollution related to agricultural land use and industrialization. Biodiversity is dominated by insects (~50%). Insects are vital for ecosystems through ecosystem engineering and controlling properties, such as soil formation and nutrient cycling, pollination, and in food webs as prey or controlling predator or parasite. Reducing insect diversity reduces resilience of ecosystems and increases risks of non-performance in soil fertility, pollination and pest suppression. Insects are under threat. Worldwide 41 % of insect species are in decline, 33% species threatened with extinction, and a co-occurring insect biomass loss of 2.5% per year. In Germany, insect biomass in natural areas surrounded by agriculture was reduced by 76% in 27 years. Nature inclusive agriculture and agri-environmental schemes aim to mitigate these kinds of effects. Protection measures need success indicators. Insects are excellent for biodiversity assessments, even with small landscape adaptations. Measuring insect biodiversity however is not easy. We aim to use new automated recognition techniques by machine learning with neural networks, to produce algorithms for fast and insightful insect diversity indexes. Biodiversity can be measured by indicative species (groups). We use three groups: 1) Carabid beetles (are top predators); 2) Moths (relation with host plants); 3) Flying insects (multiple functions in ecosystems, e.g. parasitism). The project wants to design user-friendly farmer/citizen science biodiversity measurements with machine learning, and use these in comparative research in 3 real life cases as proof of concept: 1) effects of agriculture on insects in hedgerows, 2) effects of different commercial crop production systems on insects, 3) effects of flower richness in crops and grassland on insects, all measured with natural reference situations
