Negotiating the creative and the critical : Paul Dawson’s creative writing and the new humanities

In the first Modern Language Association newsletter for 2006, renowned poetry critic and MLA President, Marjorie Perloff, remarked on the growing ascendency of Creative Writing within English Studies in North America. In her column, Perloff notes that "[i]n studying the English Job Information List (JIL) so as to advise my own students and others I know currently on the market, I noticed what struck me as a curious trend: there are, in 2005, almost three times as many positions in creative writing as in the study of twentieth-century literature" (3). The dominance of Creative Writing in the English Studies job list in turn reflects the growing student demand for undergraduate and postgraduate degrees in the field—over the past 20 years, BA and MA degrees in Creative Writing in North American tertiary institutions have quadrupled (3)...

Using police crash databases for injury prevention research - a comparison of opt-out and opt-in approaches to study recruitment

Objective: The study aimed to examine the difference in response rates between opt-out and opt-in participant recruitment in a population-based study of heavy-vehicle drivers involved in a police-attended crash. Methods: Two approaches to subject recruitment were implemented in two different states over a 14-week period and response rates for the two approaches (opt-out versus opt-in recruitment) were compared. Results: Based on the eligible and contactable drivers, the response rates were 54% for the optout group and 16% for the opt-in group. Conclusions and Implications: The opt-in recruitment strategy (which was a consequence of one jurisdiction’s interpretation of the national Privacy Act at the time) resulted in an insufficient and potentially biased sample for the purposes of conducting research into risk factors for heavy-vehicle crashes. Australia’s national Privacy Act 1988 has had a long history of inconsistent practices by state and territory government departments and ethical review committees. These inconsistencies can have profound effects on the validity of research, as shown through the significantly different response rates we reported in this study. It is hoped that a more unified interpretation of the Privacy Act across the states and territories, as proposed under the soon-to-be released Australian Privacy Principles will reduce the recruitment challenges outlined in this study.

Evaluating the use of ambient and tangible interaction approaches for personal indoor climate preferences [Extended Abstract]

In this paper we describe the preliminary results of a field study which evaluated the use of MiniOrb, a system that employs ambient and tangible interaction mechanisms to allow inhabitants of office environments to report on subjectively perceived office comfort levels. The purpose of this study was to explore the role of ubiquitous computing in the individual control of indoor climate and specifically answer the question to what extent ambient and tangible interaction mechanisms are suited for the task of capturing individual comfort preferences in a non-obtrusive manner. We outline the preliminary results of an in-situ trial of the system.

A tag-based personalized item recommendation system using tensor modeling and topic model approaches

This research falls in the area of enhancing the quality of tag-based item recommendation systems. It aims to achieve this by employing a multi-dimensional user profile approach and by analyzing the semantic aspects of tags. Tag-based recommender systems have two characteristics that need to be carefully studied in order to build a reliable system. Firstly, the multi-dimensional correlation, called as tag assignment , should be appropriately modelled in order to create the user profiles [1]. Secondly, the semantics behind the tags should be considered properly as the flexibility with their design can cause semantic problems such as synonymy and polysemy [2]. This research proposes to address these two challenges for building a tag-based item recommendation system by employing tensor modeling as the multi-dimensional user profile approach, and the topic model as the semantic analysis approach. The first objective is to optimize the tensor model reconstruction and to improve the model performance in generating quality rec-ommendation. A novel Tensor-based Recommendation using Probabilistic Ranking (TRPR) method [3] has been developed. Results show this method to be scalable for large datasets and outperforming the benchmarking methods in terms of accuracy. The memory efficient loop implements the n-mode block-striped (matrix) product for tensor reconstruction as an approximation of the initial tensor. The probabilistic ranking calculates the probabil-ity of users to select candidate items using their tag preference list based on the entries generated from the reconstructed tensor. The second objective is to analyse the tag semantics and utilize the outcome in building the tensor model. This research proposes to investigate the problem using topic model approach to keep the tags nature as the “social vocabulary” [4]. For the tag assignment data, topics can be generated from the occurrences of tags given for an item. However there is only limited amount of tags availa-ble to represent items as collection of topics, since an item might have only been tagged by using several tags. Consequently, the generated topics might not able to represent the items appropriately. Furthermore, given that each tag can belong to any topics with various probability scores, the occurrence of tags cannot simply be mapped by the topics to build the tensor model. A standard weighting technique will not appropriately calculate the value of tagging activity since it will define the context of an item using a tag instead of a topic.

Improving PLDA speaker verification using WMFD and linear-weighted approaches in limited microphone data conditions

This paper proposes the addition of a weighted median Fisher discriminator (WMFD) projection prior to length-normalised Gaussian probabilistic linear discriminant analysis (GPLDA) modelling in order to compensate the additional session variation. In limited microphone data conditions, a linear-weighted approach is introduced to increase the influence of microphone speech dataset. The linear-weighted WMFD-projected GPLDA system shows improvements in EER and DCF values over the pooled LDA- and WMFD-projected GPLDA systems in inter-view-interview condition as WMFD projection extracts more speaker discriminant information with limited number of sessions/ speaker data, and linear-weighted GPLDA approach estimates reliable model parameters with limited microphone data.

Combining meta- and mega-analytic approaches for multi-site diffusion imaging based genetic studies: From the enigma-DTI working group

Meta-analyses estimate a statistical effect size for a test or an analysis by combining results from multiple studies without necessarily having access to each individual study's raw data. Multi-site meta-analysis is crucial for imaging genetics, as single sites rarely have a sample size large enough to pick up effects of single genetic variants associated with brain measures. However, if raw data can be shared, combining data in a "mega-analysis" is thought to improve power and precision in estimating global effects. As part of an ENIGMA-DTI investigation, we use fractional anisotropy (FA) maps from 5 studies (total N=2, 203 subjects, aged 9-85) to estimate heritability. We combine the studies through meta-and mega-analyses as well as a mixture of the two - combining some cohorts with mega-analysis and meta-analyzing the results with those of the remaining sites. A combination of mega-and meta-approaches may boost power compared to meta-analysis alone.

Location and labor: Critical crossroads in global film and television

I approached the editorial prompt as an opportunity to work through some of the concerns driving my current research on creative labor in emergent or ‘peripheral’ media hubs, centers of production activity outside established media capitals that are nevertheless increasingly integrated into a global production apparatus. It builds from my research on the role that film, television and digital media production have played in the economic and cultural strategies of Glasgow, Scotland, and extends the focus on media work to other locations, including Prague and Budapest. I am particularly drawn to the spatial dynamics at play in these locations and how local producers, writers, directors and crew negotiate a sense of place and creative identity against the flows and counter-flows of capital and culture. This means not only asking questions about the growing ensemble of people, places, firms and policies that make international productions possible, but also studying the more quotidian relationships between media workers and the locations (both near and far) where they now find work. I do not see these tasks as unrelated. On the one hand, such queries underscore how international production depends on a growing constellation of interchangeable parts and is facilitated by various actors whose agendas may or may not converge. On the other hand, these questions also betray an even more complicated dynamic, a process that is shifting the spatial orientation of both location and labor around uneven and contested scales. As local industries reimagine themselves as global players, media practitioners are caught up in a new geography of creative labor: not only are personnel finding it increasingly necessary to hop from place to place to follow the work, but also place itself is changing, as locations morph into nebulous amalgamations of tax rebates, subsidized facilities, production services and (when it still matters) natural beauty.

The iconic and the critical

Theodor Adorno was opposed to the cinema because he felt it was too close to reality, and ipso facto an extension of ideological Capital, as he wrote in 1944 in Dialectic of Enlightenment. What troubled Adorno was the iconic nature of cinema – the semiotic category invented by C. S. Peirce where the signifier (sign) does not merely signify, in the arbitrary capacity attested by Saussure, but mimics the formal-visual qualities of its referent. Iconicity finds its perfect example in the film’s ingenuous surface illusion of an unmediated reality – its genealogy (the iconic), since classical antiquity, lay in the Greek term eikōn which meant “image,” to refer to the ancient portrait statues of victorious athletes which were thought to bear a direct similitude with their parent divinities. For the postwar, Hollywood-film spectator, Adorno said, “the world outside is an extension of the film he has just left,” because realism is a precise instrument for the manipulation of the mass spectator by the culture industry, for which the filmic image is an advertisement for the world unedited. Mimesis, or the reproduction of reality, is a “mere reproduction of the economic base.” It is precisely film’s iconicity, then, its “realist aesthetic . . . [that] makes it inseparable from its commodity character.”...

The fisc and the frontier: Approaches to cross-border charity in Australia and the UK

The late twentieth century witnessed the transformation of the global economy beyond the fixed geographic boundaries of the nation-state system to one dominated by financial centers, global markets, and transnational firms. In the two decades to 2011, cross-border philanthropy from OECD Development Assistance Committee (DAC) donor countries to the developing world grew from approximately USD 5 billion to USD 32 billion (OECD, n.d.),[1] with some estimates for 2011 as high as USD 59 billion (Center for Global Prosperity, 2013). This is only part of cross-border philanthropy, which also includes remittances from migrant communities, social-media-enabled global fundraising, and medical research collaborations.

Bayesian and Decision Tree Approaches for Pattern Recognition Including Feature Measurement Costs

The minimum cost classifier when general cost functionsare associated with the tasks of feature measurement and classification is formulated as a decision graph which does not reject class labels at intermediate stages. Noting its complexities, a heuristic procedure to simplify this scheme to a binary decision tree is presented. The optimizationof the binary tree in this context is carried out using ynamicprogramming. This technique is applied to the voiced-unvoiced-silence classification in speech processing.

Comparison of decision tree, support vector machines, and Bayesian network approaches for classification of falls in Parkinson’s disease

Being able to accurately predict the risk of falling is crucial in patients with Parkinson’s dis- ease (PD). This is due to the unfavorable effect of falls, which can lower the quality of life as well as directly impact on survival. Three methods considered for predicting falls are decision trees (DT), Bayesian networks (BN), and support vector machines (SVM). Data on a 1-year prospective study conducted at IHBI, Australia, for 51 people with PD are used. Data processing are conducted using rpart and e1071 packages in R for DT and SVM, con- secutively; and Bayes Server 5.5 for the BN. The results show that BN and SVM produce consistently higher accuracy over the 12 months evaluation time points (average sensitivity and specificity > 92%) than DT (average sensitivity 88%, average specificity 72%). DT is prone to imbalanced data so needs to adjust for the misclassification cost. However, DT provides a straightforward, interpretable result and thus is appealing for helping to identify important items related to falls and to generate fallers’ profiles.

Managing teams: Comparing organizational and sport psychological approaches to teamwork

This paper examines how teams and teamwork research have been conceptualised in the fields of sport psychology and organizational psychology. Specifically, it provides a close inspection of the general theoretical assumptions that inhere in the two disciplines. The results of a discursive analysis of research literature suggest that the fields have significantly different ways of conceptualising teams and teamwork and that conceptual borrowing may prove fruitful. A key argument is however, that in order for meaningful cross-fertilisation to take place a sound understanding of these differences is necessary. Working from this premise, the essential differences between sport and organizational approaches to teams are outlined. The paper is concluded with a discussion of contributions that organizational psychology can make to understandings of sport-oriented teams.

Species-based and community-level approaches to conservation prioritization

One major reason for the global decline of biodiversity is habitat loss and fragmentation. Conservation areas can be designed to reduce biodiversity loss, but as resources are limited, conservation efforts need to be prioritized in order to achieve best possible outcomes. The field of systematic conservation planning developed as a response to opportunistic approaches to conservation that often resulted in biased representation of biological diversity. The last two decades have seen the development of increasingly sophisticated methods that account for information about biodiversity conservation goals (benefits), economical considerations (costs) and socio-political constraints. In this thesis I focus on two general topics related to systematic conservation planning. First, I address two aspects of the question about how biodiversity features should be valued. (i) I investigate the extremely important but often neglected issue of differential prioritization of species for conservation. Species prioritization can be based on various criteria, and is always goal-dependent, but can also be implemented in a scientifically more rigorous way than what is the usual practice. (ii) I introduce a novel framework for conservation prioritization, which is based on continuous benefit functions that convert increasing levels of biodiversity feature representation to increasing conservation value using the principle that more is better. Traditional target-based systematic conservation planning is a special case of this approach, in which a step function is used for the benefit function. We have further expanded the benefit function framework for area prioritization to address issues such as protected area size and habitat vulnerability. In the second part of the thesis I address the application of community level modelling strategies to conservation prioritization. One of the most serious issues in systematic conservation planning currently is not the deficiency of methodology for selection and design, but simply the lack of data. Community level modelling offers a surrogate strategy that makes conservation planning more feasible in data poor regions. We have reviewed the available community-level approaches to conservation planning. These range from simplistic classification techniques to sophisticated modelling and selection strategies. We have also developed a general and novel community level approach to conservation prioritization that significantly improves on methods that were available before. This thesis introduces further degrees of realism into conservation planning methodology. The benefit function -based conservation prioritization framework largely circumvents the problematic phase of target setting, and allowing for trade-offs between species representation provides a more flexible and hopefully more attractive approach to conservation practitioners. The community-level approach seems highly promising and should prove valuable for conservation planning especially in data poor regions. Future work should focus on integrating prioritization methods to deal with multiple aspects in combination influencing the prioritization process, and further testing and refining the community level strategies using real, large datasets.