33 resultados para Barnes, Barry: Scientific knowledge. A sosiological analysis


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Purpose – The purpose of this editorial is to stimulate debate and discussion amongst marketing scholarship regarding the implications for scientific research of increasingly large amounts of data and sophisticated data analytic techniques. Design/methodology/approach – The authors respond to a recent editorial in WIRED magazine which heralds the demise of the scientific method in the face of the vast data sets now available. Findings – The authors propose that more data makes theory more important, not less. They differentiate between raw prediction and scientific knowledge – which is aimed at explanation. Research limitations/implications – These thoughts are preliminary and intended to spark thinking and debate, not represent editorial policy. Due to space constraints, the coverage of many issues is necessarily brief. Practical implications – Marketing researchers should find these thoughts at the very least stimulating, and may wish to investigate these issues further. Originality/value – This piece should provide some interesting food for thought for marketing researchers.

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In their search for innovative policy solutions to complex social problematics, local governance practitioners will look to synergising specific policy guidance from government departments with conceptual scientific research outputs. UK academics are also now expected to emphasise the relevance of their research and to increase its utilisation by practitioners. Away from utilitarian pressures, academics from applied discipline, such as Public Administration and Local Government Studies are increasingly drawn to the benefits of co-produced research. Despite the pressure for more co-research there are few opportunities for practitioners and academics to nurture relationships that would support close collaboration. This paper looks at the opportunity for closer collaboration when practitioners undertake research degrees, in order to enhance their cognitive skills and develop greater scientific knowledge of particular policy domains. If this route to closer collaboration is to succeed, it will require academics to think differently about their relationship with practitioner-students.

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Purpose: Amidst the current economic climate, which places many constraints on expensive flood defence schemes, the policy makers tend to favour schemes that are sympathetic to the needs of small and medium-sized enterprises (SMEs) and which promote empowering local communities based on their individual local contexts. Research has shown that although several initiatives are in place to create behavioural change among SMEs in undertaking adaptation approaches against flooding, they often tend to delay their responses by means of a "wait and see" attitude. The paper aims to discuss these issues. Design/methodology/approach: This paper argues that unless there are conscious efforts in the policy-making community to undertake explicit measures to engage with SMEs in a collaborative way, the uptake of adaptation measures will not be achieved as intended. With the use of the "honest broker" approach the paper provides a conceptual way forward of how a sense of collaboration can be instigated in an engagement process between the policy makers and SMEs, so that the scientific knowledge is translated in an appropriately rational way, which best meets the expectations of the SMEs. Findings: The paper proposes a conceptual model for engaging SMEs that will potentially increase the uptake of flood adaptation measures by SMEs. This could be a useful model with which to kick start a collaborative engagement process that could escalate to wider participation in other areas to improve impact of policy initiatives. Originality/value: The paper lays the conceptual foundation for a new theoretical base in the area, which will encourage more empirical investigations that will potentially enhance the practicality of some of the existing policies. © Emerald Group Publishing Limited.

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In this article I argue that the study of the linguistic aspects of epistemology has become unhelpfully focused on the corpus-based study of hedging and that a corpus-driven approach can help to improve upon this. Through focusing on a corpus of texts from one discourse community (that of genetics) and identifying frequent tri-lexical clusters containing highly frequent lexical items identified as keywords, I undertake an inductive analysis identifying patterns of epistemic significance. Several of these patterns are shown to be hedging devices and the whole corpus frequencies of the most salient of these, candidate and putative, are then compared to the whole corpus frequencies for comparable wordforms and clusters of epistemic significance. Finally I interviewed a ‘friendly geneticist’ in order to check my interpretation of some of the terms used and to get an expert interpretation of the overall findings. In summary I argue that the highly unexpected patterns of hedging found in genetics demonstrate the value of adopting a corpus-driven approach and constitute an advance in our current understanding of how to approach the relationship between language and epistemology.

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Through careful historical and ethnographic research and extensive use of local scholarly works, this book provides a persuasive and careful analysis of the production of knowledge in Central Asia. The author demonstrates that classical theories of science and society are inadequate for understanding the science project in Central Asia. Instead, a critical understanding of local science is more appropriate. In the region, the professional and political ethos of Marxism-Leninism was incorporated into the logic of science on the periphery of the Soviet empire. This book reveals that science, organizes and constructed by Soviet rule, was also defined by individual efforts of local scientists. Their work to establish themselves 'between Marx and the market' is therefore creating new political economies of knowledge at the edge of the scientific world system.

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Visualising data for exploratory analysis is a big challenge in scientific and engineering domains where there is a need to gain insight into the structure and distribution of the data. Typically, visualisation methods like principal component analysis and multi-dimensional scaling are used, but it is difficult to incorporate prior knowledge about structure of the data into the analysis. In this technical report we discuss a complementary approach based on an extension of a well known non-linear probabilistic model, the Generative Topographic Mapping. We show that by including prior information of the covariance structure into the model, we are able to improve both the data visualisation and the model fit.

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This thesis was concerned with investigating methods of improving the IOP pulse’s potential as a measure of clinical utility. There were three principal sections to the work. 1. Optimisation of measurement and analysis of the IOP pulse. A literature review, covering the years 1960 – 2002 and other relevant scientific publications, provided a knowledge base on the IOP pulse. Initial studies investigated suitable instrumentation and measurement techniques. Fourier transformation was identified as a promising method of analysing the IOP pulse and this technique was developed. 2. Investigation of ocular and systemic variables that affect IOP pulse measurements In order to recognise clinically important changes in IOP pulse measurement, studies were performed to identify influencing factors. Fourier analysis was tested against traditional parameters in order to assess its ability to detect differences in IOP pulse. In addition, it had been speculated that the waveform components of the IOP pulse contained vascular characteristic analogous to those components found in arterial pulse waves. Validation studies to test this hypothesis were attempted. 3. The nature of the intraocular pressure pulse in health and disease and its relation to systemic cardiovascular variables. Fourier analysis and traditional parameters were applied to the IOP pulse measurements taken on diseased and healthy eyes. Only the derived parameter, pulsatile ocular blood flow (POBF) detected differences in diseased groups. The use of an ocular pressure-volume relationship may have improved the POBF measure’s variance in comparison to the measurement of the pulse’s amplitude or Fourier components. Finally, the importance of the driving force of pulsatile blood flow, the arterial pressure pulse, is highlighted. A method of combining the measurements of pulsatile blood flow and pulsatile blood pressure to create a measure of ocular vascular impedance is described along with its advantages for future studies.

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This article presents two novel approaches for incorporating sentiment prior knowledge into the topic model for weakly supervised sentiment analysis where sentiment labels are considered as topics. One is by modifying the Dirichlet prior for topic-word distribution (LDA-DP), the other is by augmenting the model objective function through adding terms that express preferences on expectations of sentiment labels of the lexicon words using generalized expectation criteria (LDA-GE). We conducted extensive experiments on English movie review data and multi-domain sentiment dataset as well as Chinese product reviews about mobile phones, digital cameras, MP3 players, and monitors. The results show that while both LDA-DP and LDAGE perform comparably to existing weakly supervised sentiment classification algorithms, they are much simpler and computationally efficient, rendering themmore suitable for online and real-time sentiment classification on the Web. We observed that LDA-GE is more effective than LDA-DP, suggesting that it should be preferred when considering employing the topic model for sentiment analysis. Moreover, both models are able to extract highly domain-salient polarity words from text.

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It is widely observed that the global geography of innovation is rapidly evolving. This paper presents evidence concerning the contemporary evolution of the globe's most productive regions. The paper uncovers the underlying structure and co-evolution of knowledge-based resources, capabilities and outputs across these regions. The analysis identifies two key trends by which the economic evolution and growth patterns of these regions are differentiated-namely, knowledge-based growth and labour market growth. The knowledge-based growth factor represents the underlying commonality found between the growth of economic output, earnings and a range of knowledge-based resources. The labour market growth factor represents the capability of regions to draw on their human capital. Overall, spectacular knowledge-based growth of leading Chinese regions is evident, highlighting a continued shift of knowledge-based resources to Asia. It is concluded that regional growth in knowledge production investment and the capacity to draw on regional human capital reserves are neither necessarily traded-off nor complementary to each other. © 2012 Urban Studies Journal Limited.

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The evolution of a regional economy and its competitiveness capacity may involve multiple independent trajectories, through which different sets of resources and capabilities evolve together. However, there is a dearth of evidence concerning how these trends are occurring across the globe. This paper seeks to present evidence in relation to the recent development of the globe’s most productive regions from the viewpoint of their growth trajectories, and the particular form of growth they are experiencing. The aim is to uncover the underlying structure of the changes in knowledge-based resources, capabilities and outputs across regions, and offer an analysis of these regions according to an uncovered set of key trends. The analysis identifies three key trends by which the economic evolution and growth patterns of these regions are differentiated—namely the Fifth Wave Growth, the Third & Fourth Wave Growth, and Government-led Third Wave Growth. Overall, spectacular knowledge-based growth of leading Chinese regions is evident, highlighting a continued shift of knowledge-based resources to Asia. In addition, a superstructure is observed at the global scale, consisting of two separate continuums that explicitly distinguish Chinese regions from the rest in terms of regional growth trajectories.

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Background - This study investigates the coverage of adherence to medicine by the UK and US newsprint media. Adherence to medicine is recognised as an important issue facing healthcare professionals and the newsprint media is a key source of health information, however, little is known about newspaper coverage of medication adherence. Methods - A search of the newspaper database Nexis®UK from 2004–2011 was performed. Content analysis of newspaper articles which referenced medication adherence from the twelve highest circulating UK and US daily newspapers and their Sunday equivalents was carried out. A second researcher coded a 15% sample of newspaper articles to establish the inter-rater reliability of coding. Results - Searches of newspaper coverage of medication adherence in the UK and US yielded 181 relevant articles for each country. There was a large increase in the number of scientific articles on medication adherence in PubMed® over the study period, however, this was not reflected in the frequency of newspaper articles published on medication adherence. UK newspaper articles were significantly more likely to report the benefits of adherence (p = 0.005), whereas US newspaper articles were significantly more likely to report adherence issues in the elderly population (p = 0.004) and adherence associated with diseases of the central nervous system (p = 0.046). The most commonly reported barriers to adherence were patient factors e.g. poor memory, beliefs and age, whereas, the most commonly reported facilitators to adherence were medication factors including simplified regimens, shorter treatment duration and combination tablets. HIV/AIDS was the single most frequently cited disease (reported in 20% of newspaper articles). Poor quality reporting of medication adherence was identified in 62% of newspaper articles. Conclusion - Adherence is not well covered in the newspaper media despite a significant presence in the medical literature. The mass media have the potential to help educate and shape the public’s knowledge regarding the importance of medication adherence; this potential is not being realised at present.

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Radio Frequency Identification (RFID) has been identified as a crucial technology for the modern 21st century knowledge-based economy. Some businesses have realised benefits of RFID adoption through improvements in operational efficiency, additional cost savings, and opportunities for higher revenues. RFID research in warehousing operations has been less prominent than in other application domains. To investigate how RFID technology has had an impact in warehousing, a comprehensive analysis of research findings available from articles through leading scientific article databases has been conducted. Articles from years 1995 to 2010 have been reviewed and analysed with respect to warehouse operations, RFID application domains, benefits achieved and obstacles encountered. Four discussion topics are presented covering RFID in warehousing focusing on its applications, perceived benefits, obstacles to its adoption and future trends. This is aimed at elucidating the current state of RFID in the warehouse and providing insights for researchers to establish new research agendas and for practitioners to consider and assess the adoption of RFID in warehousing functions. © 2013 Elsevier B.V.

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In this paper, we explore the idea of social role theory (SRT) and propose a novel regularized topic model which incorporates SRT into the generative process of social media content. We assume that a user can play multiple social roles, and each social role serves to fulfil different duties and is associated with a role-driven distribution over latent topics. In particular, we focus on social roles corresponding to the most common social activities on social networks. Our model is instantiated on microblogs, i.e., Twitter and community question-answering (cQA), i.e., Yahoo! Answers, where social roles on Twitter include "originators" and "propagators", and roles on cQA are "askers" and "answerers". Both explicit and implicit interactions between users are taken into account and modeled as regularization factors. To evaluate the performance of our proposed method, we have conducted extensive experiments on two Twitter datasets and two cQA datasets. Furthermore, we also consider multi-role modeling for scientific papers where an author's research expertise area is considered as a social role. A novel application of detecting users' research interests through topical keyword labeling based on the results of our multi-role model has been presented. The evaluation results have shown the feasibility and effectiveness of our model.