139 resultados para bio-ecological indices

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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Bronfenbrenner’s model of bio-ecological development has been utilized widely within the social sciences, in the field of human development, and in social work. Yet, while championing the rights of marginalised families and communities, Bronfenbrenner had under-theorized the role of power, agency and structure in shaping the ‘person-context’ interrelationship, life opportunities and social well-being. To respond to this deficit, this paper firstly outlines Bronfenbrenner’s ‘person, process, context, time’ model. Secondly, it then seeks to loosely align aspects of Bronfenbrenner’s model with Bourdieu’s analytical categories of habitus, field and capital. It is argued that these latter categories enable social workers to develop a critical ecology of child development, taking account of power and the interplay between agency and structure. The implications of the alignment for child and family social work are considered in the final section.

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Biodiversity, a multidimensional property of natural systems, is difficult to quantify partly because of the multitude of indices proposed for this purpose. Indices aim to describe general properties of communities that allow us to compare different regions, taxa, and trophic levels. Therefore, they are of fundamental importance for environmental monitoring and conservation, although there is no consensus about which indices are more appropriate and informative. We tested several common diversity indices in a range of simple to complex statistical analyses in order to determine whether some were better suited for certain analyses than others. We used data collected around the focal plant Plantago lanceolata on 60 temperate grassland plots embedded in an agricultural landscape to explore relationships between the common diversity indices of species richness (S), Shannon's diversity (H'), Simpson's diversity (D1), Simpson's dominance (D2), Simpson's evenness (E), and Berger–Parker dominance (BP). We calculated each of these indices for herbaceous plants, arbuscular mycorrhizal fungi, aboveground arthropods, belowground insect larvae, and P. lanceolata molecular and chemical diversity. Including these trait-based measures of diversity allowed us to test whether or not they behaved similarly to the better studied species diversity. We used path analysis to determine whether compound indices detected more relationships between diversities of different organisms and traits than more basic indices. In the path models, more paths were significant when using H', even though all models except that with E were equally reliable. This demonstrates that while common diversity indices may appear interchangeable in simple analyses, when considering complex interactions, the choice of index can profoundly alter the interpretation of results. Data mining in order to identify the index producing the most significant results should be avoided, but simultaneously considering analyses using multiple indices can provide greater insight into the interactions in a system.

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Summary statistics continue to play an important role in identifying and monitoring patterns and trends in educational inequalities between differing groups of pupils over time. However, this article argues that their uncritical use can also encourage the labelling of whole groups of pupils as ‘underachievers’ or ‘overachievers’ as the findings of group-level data are simply applied to individual group members, a practice commonly termed the ‘ecological fallacy’. Some of the adverse consequences of this will be outlined in relation to current debates concerning gender and ethnic differences in educational attainment. It will be argued that one way of countering this uncritical use of summary statistics and the ecological fallacy that it tends to encourage, is to make much more use of the principles and methods of what has been termed ‘exploratory data analysis’. Such an approach is illustrated through a secondary analysis of data from the Youth Cohort Study of England and Wales, focusing on gender and ethnic differences in educational attainment. It will be shown that, by placing an emphasis on the graphical display of data and on encouraging researchers to describe those data more qualitatively, such an approach represents an essential addition to the use of simple summary statistics and helps to avoid the limitations associated with them.

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Aims/Hypothesis: To describe the epidemiology of childhood-onset Type 1 (insulin-dependent) diabetes in Europe, the EURODIAB collaborative group has established prospective, geographically-defined registers of children diagnosed under 15 years. A total of 16,362 cases were registered by 44 centres during the period 1989-1994. The registers cover a population of approximately 28 million children with most European countries represented. Methods In most centres a primary and a secondary source of ascertainment were used so that the completeness of registration could be assessed by the capture-recapture method. Ecological correlation and regression analyses were used to study the relationship between incidence and various environmental, health and economic indicators. Findings: The standardised average annual incidence rate during the period 1989-94 ranged from 3.2 cases per 100,000 per annum in the Former Yugoslavian Republic of Macedonia to 40.2 cases per 100,000 per annum in Finland. Indicators of national prosperity such as infant mortality (r= -0.64) and gross domestic product (r= 0.58) were most strongly and significantly correlated with incidence rate, and previously-reported associations with coffee consumption (r= 0.51), milk consumption (r= 0.58) and latitude (r= 0.40) were also observed. Conclusion/Interpretation: The wide variation in childhood type 1 diabetes incidence rates within Europe could be partially explained by indicators of national prosperity. These indicators could reflect differences in environmental risk factors such as nutrition or lifestyle that are important in determining a country's incidence rate.