994 resultados para Mining industries
Resumo:
This paper addresses contemporary neoliberal mobilisations of community undertaken by private corporations. It does so by examining the ways in which the mining industry, empowered through the legitimising framework of corporate social responsibility, is increasingly and profoundly involved in shaping the meaning, practice, and experience of ‘local community’. We draw on a substantial Australian case study, consisting of interviews and document analysis, as a means to examine ‘community-engagement’ practices undertaken by BHP Billiton’s Ravensthorpe Nickel Operation in the Shire of Ravensthorpe in rural Australia. This engagement, we argue, as a process of deepening neoliberalisation simultaneously defines and transforms local community according to the logic of global capital. As such, this study has implications for critical understandings of the intersections among corporate social responsibility, neoliberalisation, community, and capital.
Resumo:
This paper uses examples from the history and practices of multi-national and large companies in the oil, chemical and asbestos industries to examine their legal and illegal despoiling and destruction of the environment and impact on human and non-human life. The discussion draws on the literature on green criminology and state-corporate crime and considers measures and arrangements that might mitigate or prevent such damaging acts. This paper is part of ongoing work on green criminology and crimes of the economy. It places these actions and crimes in the context of a global neo-liberal economic system and considers and critiques the distorting impact of the GDP model of ‘economic health’ and its consequences for the environment.
Resumo:
This chapter is concerned with innovation that involves creative cultural occupations, but not within the creative industries. Rather, we examine the operation of cultural creative occupations that exist outside the creative industries - so-called 'embedded creatives' who work across all industry sectors (Cunningham and Higgs 2009). In doing so, we concur with Bilton (2007) that the separation of creative industries from other industries is a 'false step'. All industries must be innovative; however, they also must be able to combine both scientific and artistic creativity, and that creativity comes from the intersection of different thinking styles (Kurtzberg 2005). Moreover, we suggest that there are now detailed empirical studies, as well as a nascent theoretical base, to suggest that the transdisciplinarity which results from embedded cultural creativity is an engine of growth in the broader economy. Thus, it is relevant to both policymakers and managers. This chapter addresses the following questions: What is the role and significance of the embedded creative? Given a paucity of detailed empirical work in the area to date, what can be deduced from what extant literature there is about the nature of employment and management of these workers? And what are the practical implications of these consideration?
Resumo:
This thesis presents a sequential pattern based model (PMM) to detect news topics from a popular microblogging platform, Twitter. PMM captures key topics and measures their importance using pattern properties and Twitter characteristics. This study shows that PMM outperforms traditional term-based models, and can potentially be implemented as a decision support system. The research contributes to news detection and addresses the challenging issue of extracting information from short and noisy text.
Resumo:
The creative industries have become a key part of the economic development of many nations, with a particularly lively debate in the developing world taking place now.
Resumo:
Term-based approaches can extract many features in text documents, but most include noise. Many popular text-mining strategies have been adapted to reduce noisy information from extracted features; however, text-mining techniques suffer from low frequency. The key issue is how to discover relevance features in text documents to fulfil user information needs. To address this issue, we propose a new method to extract specific features from user relevance feedback. The proposed approach includes two stages. The first stage extracts topics (or patterns) from text documents to focus on interesting topics. In the second stage, topics are deployed to lower level terms to address the low-frequency problem and find specific terms. The specific terms are determined based on their appearances in relevance feedback and their distribution in topics or high-level patterns. We test our proposed method with extensive experiments in the Reuters Corpus Volume 1 dataset and TREC topics. Results show that our proposed approach significantly outperforms the state-of-the-art models.
Resumo:
Governments have recognised that the technological trades rely on knowledge embedded traditionally in science, technology, engineering and mathematics (STEM) disciplines. In this paper, we report preliminary findings on the development of two curricula that attempt to integrate science and mathematics with workplace knowledge and practices. We argue that these curricula provide educational opportunities for students to pursue their preferred career pathways. These curricula were co-developed by industry and educational personnel across two industry sectors, namely, mining and aerospace. The aim was to provide knowledge appropriate for students moving from school to the workplace in the respective industries. The analysis of curriculum and associated policy documents reveals that the curricula adopt applied learning orientations through teaching strategies and assessment practices which focus on practical skills. However, although key theoretical science and maths concepts have been well incorporated, the extent to which knowledge deriving from workplace practices is included varies across the curricula. Our findings highlight the importance of teachers having substantial practical industry experience and the role that whole school policies play in attempts to align the range of learning experiences with the needs of industry.
Resumo:
The practices and public reputation of mining have been changing over time. In the past, mining operations frequently stood accused of being socially and environmentally disruptive, whereas mining today invests heavily in ‘socially responsible’ and ‘sustainable’ business practices. Changes such as these can be witnessed internationally as well as in places like Western Australia (WA), where the mining sector has matured into an economic pillar of the state, and indeed the nation in the context of the recent resources boom. This paper explores the role of mining in WA, presenting a multi-disciplinary perspective on the sector's contribution to sustainable development in the state. The perspectives offered here are drawn from community-based research and the associated academic literature as well as data derived from government sources and the not-for-profit sector. Findings suggest that despite noteworthy attitudinal and operational improvements in the industry, social, economic and environmental problem areas remain. As mining in WA is expected to grow in the years to come, these problem areas require the attention of business and government alike to ensure the long-term sustainability of development as well as people and place.
Resumo:
This paper presents an analysis of media reports of Australian women in mine management. It argues that a dominant storyline in the texts is one of gender change; in fact, a ‘feminine revolution’ is said to have occurred in the mining industry and corporate Australia more generally. Despite this celebratory and transformative discourse the female mine managers interviewed in the media texts seek to distance themselves from women/female identity/femininity and take up a script of gender neutrality. It is demonstrated, however, that this script is saturated with the assumptions and definitions of managerial masculinity.
Resumo:
This paper draws upon Hubbard's (1999, p. 57) term ‘scary heterosexualities,’ that is non-normative heterosexuality, in the context of the rural drawing on data from fieldwork in the remote Western Australian mining town of Kalgoorlie. Our focus is ‘the skimpie’ – a female barmaid who serves in her underwear and who, in both historical and contemporary times, is strongly associated with rural mining communities. Interviews with skimpies and local residents as well as participant observation reveal how potential fears and anxieties about skimpies are managed. We identify the discursive and spatial processes by which skimpie work is contained in Kalgoorlie so that the potential scariness ‘the skimpie’ represents to the rural is muted and buttressed in terms of a more conventional and less threatening rural heterosexuality.
Resumo:
Despite ongoing ‘boom’ conditions in the Australian mining industry, women remain substantially and unevenly under-represented in the sector, as is the case in other resource-dependent countries. Building on the literature critiquing business-case rationales and strategies as a means to achieve women’s equality in the workplace, we examine the business case for employing more women as advanced by the Australian mining industry. Specifically, we apply a discourse analysis to seven substantial, publically-available documents produced by the industry’s national and state peak organizations between 2005 and 2013. Our study makes two contributions. First, we map the features of the business case at the sectoral rather than firm or workplace level and examine its public mobilization. Second, we identify the construction and deployment of a normative identity – ‘the ideal mining woman’ – as a key outcome of this business-case discourse. Crucially, women are therein positioned as individually responsible for gender equality in the workplace.
Resumo:
In coastal areas, extreme weather events, such as floods and cyclones, can have debilitating effects on the social and economic viability of marine-based industries. In March 2011, the Great Barrier Reef Marine Park Authority implemented an Extreme Weather Response Program, following a period of intense flooding and cyclonic activity between December 2010 and February 2011. In this paper, we discuss the results of a project within the Program, which aimed to: (1) assess the impacts of extreme weather events on regional tourism and commercial fishing industries; and (2) develop and road-test an impact assessment matrix to improve government and industry responses to extreme weather events. Results revealed that extreme weather events both directly and indirectly affected all five of the measured categories, i.e. ecological, personal, social, infrastructure and economic components. The severity of these impacts, combined with their location and the nature of their business, influenced how tourism operators and fishers assessed the impact of the events (low, medium, high or extreme). The impact assessment tool was revised following feedback obtained during stakeholder workshops and may prove useful for managers in responding to potential direct and indirect impacts of future extreme weather events on affected marine industries. © 2013 Planning Institute Australia.
Resumo:
This study was a step forward to improve the performance for discovering useful knowledge – especially, association rules in this study – in databases. The thesis proposed an approach to use granules instead of patterns to represent knowledge implicitly contained in relational databases; and multi-tier structure to interpret association rules in terms of granules. Association mappings were proposed for the construction of multi-tier structure. With these tools, association rules can be quickly assessed and meaningless association rules can be justified according to the association mappings. The experimental results indicated that the proposed approach is promising.
Resumo:
This paper presents a novel framework to further advance the recent trend of using query decomposition and high-order term relationships in query language modeling, which takes into account terms implicitly associated with different subsets of query terms. Existing approaches, most remarkably the language model based on the Information Flow method are however unable to capture multiple levels of associations and also suffer from a high computational overhead. In this paper, we propose to compute association rules from pseudo feedback documents that are segmented into variable length chunks via multiple sliding windows of different sizes. Extensive experiments have been conducted on various TREC collections and our approach significantly outperforms a baseline Query Likelihood language model, the Relevance Model and the Information Flow model.