Towards a plurilingual habitus: engendering interlinguality in urban spaces

This article focuses on the potential of the multilingual city to create spaces in which monolingual hegemonies may be challenged, inclusive, intercultural values may be nurtured, and plurilingualism may be valorised. Following a contextualisation of linguistic diversity in theories of globalisation and superdiversity, discourses of deficit and power are addressed, arguing that the problematisation of multilingualism and pathologisation of plurilingualism reflect a monolingual habitus. Bringing about a shift towards a plurilingual habitus requires a Deep Approach, as it involves a critical revaluing of deep-seated dispositions. It suggests that the city offers spaces, which can engender interlinguality, a construct that includes interculturality, criticality and a commitment to creative and flexible use of other languages in shared, pluralistic spaces. It then proposes critical, participatory and ethnographic research in three multidimensional spaces: the urban school and a potential interlingual curriculum; networks, lobbying for inclusive policy and organising celebratory events in public spaces; and grass roots-level local spaces, some created by linguistic communities to exercise agency and maintain their languages and cultures, and some emerging as linguistically hybrid spaces for convivial encounter

Socioecological stressor areas and black-white blood pressure: Detroit

1. 1. Blood pressure does appear to vary with `socioecological niches' or combinations of sex, race and residence, which reflect social class position as well as degree of social stressor conditions. Black High Stress males had higher adjusted levels than Black Low Stress males, while White High Stress females had higher adjusted pressures than White Low Stress females. Black High Stress females had significantly higher observed levels than Black Low Stress females.2. 2. Black High Stress males had a significantly higher per cent of Borderline and Hypertensive blood pressure than other male race-area groups; White Low Stress females had the lowest of all eight sex-race-stress area groups.3. 3. For Black males, the younger, overweight High Stress residents had significantly higher Borderline and Hypertensive levels than did a similar Black Low Stress subgroup. Further, for both groups, being raised in Detroit and not migrating from elsewhere was related to higher readings. Tests for age-stress area interaction, however, were not significant.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/33823/1/0000080.pd

EUNIS Habitat Classification: Expert system, characteristic species combinations and distribution maps of European habitats

Aim: The EUNIS Habitat Classification is a widely used reference framework for European habitat types (habitats), but it lacks formal definitions of individual habitats that would enable their unequivocal identification. Our goal was to develop a tool for assigning vegetation‐plot records to the habitats of the EUNIS system, use it to classify a European vegetation‐plot database, and compile statistically‐derived characteristic species combinations and distribution maps for these habitats. Location: Europe. Methods: We developed the classification expert system EUNIS‐ESy, which contains definitions of individual EUNIS habitats based on their species composition and geographic location. Each habitat was formally defined as a formula in a computer language combining algebraic and set‐theoretic concepts with formal logical operators. We applied this expert system to classify 1,261,373 vegetation plots from the European Vegetation Archive (EVA) and other databases. Then we determined diagnostic, constant and dominant species for each habitat by calculating species‐to‐habitat fidelity and constancy (occurrence frequency) in the classified data set. Finally, we mapped the plot locations for each habitat. Results: Formal definitions were developed for 199 habitats at Level 3 of the EUNIS hierarchy, including 25 coastal, 18 wetland, 55 grassland, 43 shrubland, 46 forest and 12 man‐made habitats. The expert system classified 1,125,121 vegetation plots to these habitat groups and 73,188 to other habitats, while 63,064 plots remained unclassified or were classified to more than one habitat. Data on each habitat were summarized in factsheets containing habitat description, distribution map, corresponding syntaxa and characteristic species combination. Conclusions: EUNIS habitats were characterized for the first time in terms of their species composition and distribution, based on a classification of a European database of vegetation plots using the newly developed electronic expert system EUNIS‐ESy. The data provided and the expert system have considerable potential for future use in European nature conservation planning, monitoring and assessment