98 resultados para locality influences
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It has frequently been argued that multinational companies are moving towards network forms whereby subsidiaries share different practices with the rest of the company. This paper presents large-scale empirical evidence concerning the extent to which subsidiaries input novel practices into the rest of the multinational. We investigate this in the field of human resources through analysis of a unique international data set in four host countries - Canada, Ireland, Spain and the UK - and address the question of how we can explain variation between subsidiaries in terms of whether they initiate the diffusion of practices to other subsidiaries. The data support the argument that multiple, rather than single, factor explanations are required to more effectively understand the factors promoting or retarding the diffusion of human resource practices within multinational companies. It emerges that national, corporate and functional contexts all matter. More specifically, actors at subsidiary level who seek to initiate diffusion appear to be differentially placed according to their national context, their place within corporate structures and the extent to which the human resource function is internationally networked.
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The density and composition of stream bed metal deposits are affected by physical, chemical and biological processes. In this paper we investigate the importance of these processes and their relation to algal and non-photosynthetic detrital (NPD) biomass in a set of upland streams in Northern Ireland. Deposit density and Fe, Mn, Al and P concentrations varied with stream pH across sites but not seasonally. No effects of stream bed erosion or photoreduction were detected on deposit densities. Seasonal variation in stream water metal concentrations was correlated with rainfall. NPD biomass was a significant predictor of both spatial and seasonal variation in deposit concentrations. There were strong, non-linear, relations between NPD biomass and deposit metal concentrations, with Fe and Mn becoming relatively more important and algal biomass declining above threshold deposit/NPD densities. The results suggest that NPD biomass influences deposit density and reduces the biomass of photosynthetic autotrophs above a threshold deposit density.
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Metal concentrations from stream waters in two geological blocks in Northern Ireland were compared to determine the contributions of catchment characteristics and in-stream conditions. One block is composed of metamorphosed schist and unconsolidated glacial drift with peat or peaty podzol (mainly humic) soils, while the other block consists of tertiary basalt with brown earth and gley soils. Water samples were collected from 52 stream sites and analysed for Fe, Mn and Al as well as a range of other chemical determinands known to affect metal solubility. Densities of metal-rich ochre deposit were determined for stream bed stone samples. Higher conductivities and concentrations of bicarbonate, alkalinity, Ca and Mg occurred on basalt than on schist. Despite higher Fe and Mn oxide concentrations in basalt-derived non-humic soils, stream water concentrations were much lower and ochre deposit densities only one third of those on schist overlain by humic soils. Neither rock nor soil type predicted Al concentrations, but pH and dissolved oxygen did. Peat-generated acidity and the limited acid neutralising capacity of base-poor metamorphosed schist have resulted in elevated concentrations of metals and ochre deposit in surface waters.
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Most traditional data mining algorithms struggle to cope with the sheer scale of data efficiently. In this paper, we propose a general framework to accelerate existing clustering algorithms to cluster large-scale datasets which contain large numbers of attributes, items, and clusters. Our framework makes use of locality sensitive hashing (LSH) to significantly reduce the cluster search space. We also theoretically prove that our framework has a guaranteed error bound in terms of the clustering quality. This framework can be applied to a set of centroid-based clustering algorithms that assign an object to the most similar cluster, and we adopt the popular K-Modes categorical clustering algorithm to present how the framework can be applied. We validated our framework with five synthetic datasets and a real world Yahoo! Answers dataset. The experimental results demonstrate that our framework is able to speed up the existing clustering algorithm between factors of 2 and 6, while maintaining comparable cluster purity.
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In recent years, the internet has become a key site for the portrayal of Rio de Janeiro’s favelas. This article examines blogging by favela residents and argues that digital culture constitutes a vital, and as yet not systematically explored, arena of research on the representation of Rio de Janeiro and its favelas. Based on ethnographically inspired research carried out in 2009–2010, this article examines two examples of blog ‘framing content’ (a sidebar and a static page) encountered during fieldwork, which functioned to establish a concrete link between the posts on the blogs in question, their authors, and a named favela, even when the posts were not explicitly about that favela. At the same time, the framing content also made visible, and affirmed, the translocal connections between that favela, other favelas, and the city as a whole. These illustrative examples from a wider study show how favela bloggers are engaged in resignifying and remapping the relationships between different empirical scales of locality (and associated identities) in Rio de Janeiro, demonstrating the contribution an interdisciplinary approach to the digital texts and practices of favela residents can make to an understanding of the contemporary city and its representational conundrums, from the perspective of ‘ordinary practitioners’.