Relating Across Difference : A Case Study in Transformative Learning

This chapter examines the process of “transformative learning” for the 2008 cohort of the St. Thomas More College–Intercordia Canada (STM/IC) international community service-learning program. My primary data comes from the eight students who were part of that cohort, when I was their program coordinator. That data later became the heart of my Master’s thesis and was approved by the Research Ethics Office of the University of Saskatchewan. In this chapter I focus on three of those eight participants, outlining the critical elements of their experiences that were conducive to their transformative learning. To be sure, my sample size is too small to draw generalizable conclusions, but the quality of information I received from these students and their colleagues, coupled with the follow-up conversations I had with other educators and with the accompanying literature, supports the value of reflecting at length here about these students’ comments. I have chosen to highlight the experiences of these three participants because together they provide a range of experiences that best enables an analysis of the conditions that both did and did not lead to transformative learning. This case study suggests that transformative learning occurs through: the dynamics of vulnerability, a discovery of persisting differences within inter-personal relationships, and an experience of welcome and hospitality in the host environment. In contrast to other studies that focus on the enhanced capacities, skills and subsequent employability of participants through international education, transformative learning for these students required a relinquishing of securities, a disorientation and critical interrogation of the self, and enhanced receptivity to the newly recognized Other. Moreover, consistent with the critical-humanistic educational philosophy shared in different ways by the participants of the STM/IC program, this study suggests that international community service-learning can most responsibly contribute to good global citizenship through the construction of relationships of solidarity across difference.

Setting the research agenda in IHRM

Firstly, on behalf of the secretariat that has coordinated these meetings every two years since 1985, our thanks to the organising committee here at the University of Economics in Cracow, Poland, for hosting this conference. I was asked to offer comment on the research agenda. There are many famous names to refer to. Two Australian colleagues here today are Peter Dowling and Helen De Cieri, longtime stalwarts of the field of IHRM. I acknowledge their contributions over many years, along with Randy Schuler and Denise Welch, and Dennis Briscoe. Other names such as Rosalie Tung, Pawan Bhudwhar, Michael Morley, Paul Sparrow and Wayne Cascio are known to us all. Their books have become classics. One example is the 700 page benchmark 2012 work by Chris Brewster and Wolfgang Mayrhofer, Handbook of Research on Comparative Human Resource Management (Brewster & Mayrhofer, 2012). More recently, in a book published by Cambridge University press in 2014, Mustafa Özbilgin, Dimitria Groutsis and William Harvey offer students a very accessible overview of the basics in IHRM (Ozbilgin, Groutsis, & Harvey, 2014). As for a research agenda, there are excellent literature reviews to which I would refer you, such as those by people who over the years have been frequent participants at this conference (Tarique & Schuler, 2010), (Farndale, Scullion, & Sparrow, 2010), and (Scullion & Collings, 2011).

Using enterprise information architecture methods to model wicked problems in information systems design research

Design Science is the process of solving ‘wicked problems’ through designing, developing, instantiating, and evaluating novel solutions (Hevner, March, Park and Ram, 2004). Wicked problems are described as agent finitude in combination with problem complexity and normative constraint (Farrell and Hooker, 2013). In Information Systems Design Science, determining that problems are ‘wicked’ differentiates Design Science research from Solutions Engineering (Winter, 2008) and is a necessary part of proving the relevance to Information Systems Design Science research (Hevner, 2007; Iivari, 2007). Problem complexity is characterised as many problem components with nested, dependent and co-dependent relationships interacting through multiple feedback and feed-forward loops. Farrell and Hooker (2013) specifically state for wicked problems “it will often be impossible to disentangle the consequences of specific actions from those of other co-occurring interactions”. This paper discusses the application of an Enterprise Information Architecture modelling technique to disentangle the wicked problem complexity for one case. It proposes that such a modelling technique can be applied to other wicked problems and can lay the foundations for proving relevancy to DSR, provide solution pathways for artefact development, and aid to substantiate those elements required to produce Design Theory.

Optimizing I/O cost and managing memory for composition vector method based on correlation matrix calculation in bioinformatics

The generation of a correlation matrix for set of genomic sequences is a common requirement in many bioinformatics problems such as phylogenetic analysis. Each sequence may be millions of bases long and there may be thousands of such sequences which we wish to compare, so not all sequences may fit into main memory at the same time. Each sequence needs to be compared with every other sequence, so we will generally need to page some sequences in and out more than once. In order to minimize execution time we need to minimize this I/O. This paper develops an approach for faster and scalable computing of large-size correlation matrices through the maximal exploitation of available memory and reducing the number of I/O operations. The approach is scalable in the sense that the same algorithms can be executed on different computing platforms with different amounts of memory and can be applied to different bioinformatics problems with different correlation matrix sizes. The significant performance improvement of the approach over previous work is demonstrated through benchmark examples.

Making optimal and justifiable asset maintenance decisions

Maintenance decisions for large-scale asset systems are often beyond an asset manager's capacity to handle. The presence of a number of possibly conflicting decision criteria, the large number of possible maintenance policies, and the reality of budget constraints often produce complex problems, where the underlying trade-offs are not apparent to the asset manager. This paper presents the decision support tool "JOB" (Justification and Optimisation of Budgets), which has been designed to help asset managers of large systems assess, select, interpret and optimise the effects of their maintenance policies in the presence of limited budgets. This decision support capability is realized through an efficient, scalable backtracking- based algorithm for the optimisation of maintenance policies, while enabling the user to view a number of solutions near this optimum and explore tradeoffs with other decision criteria. To assist the asset manager in selecting between various policies, JOB also provides the capability of Multiple Criteria Decision Making. In this paper, the JOB tool is presented and its applicability for the maintenance of a complex power plant system.

Virulence properties of asymptomatic bacteriuria Escherichia coli

In asymptomatic bacteriuria (ABU), bacteria colonize the urinary tract without provoking symptoms. Here, we compared the virulence properties of a collection of ABU Escherichia coli strains to cystitis and pyelonephritis strains. Specific urinary tract infection (UTI)-associated virulence genes, hemagglutination characteristics, siderophore production, hemolysis, biofilm formation, and the ability of strains to adhere to and induce cytokine responses in epithelial cells were analyzed. ABU strains were phylogenetically related to strains that cause symptomatic UTI. However, the virulence properties of the ABU strains were variable and dependent on a combination of genotypic and phenotypic factors. Most ABU strains adhered poorly to epithelial cells; however, we also identified a subgroup of strongly adherent strains that were unable to stimulate an epithelial cell IL-6 cytokine response. Poor immune activation may represent one mechanism whereby ABU E. coli evade immune detection after the establishment of bacteriuria.

Locality-sensitive hashing for protein classification

Determination of sequence similarity is a central issue in computational biology, a problem addressed primarily through BLAST, an alignment based heuristic which has underpinned much of the analysis and annotation of the genomic era. Despite their success, alignment-based approaches scale poorly with increasing data set size, and are not robust under structural sequence rearrangements. Successive waves of innovation in sequencing technologies – so-called Next Generation Sequencing (NGS) approaches – have led to an explosion in data availability, challenging existing methods and motivating novel approaches to sequence representation and similarity scoring, including adaptation of existing methods from other domains such as information retrieval. In this work, we investigate locality-sensitive hashing of sequences through binary document signatures, applying the method to a bacterial protein classification task. Here, the goal is to predict the gene family to which a given query protein belongs. Experiments carried out on a pair of small but biologically realistic datasets (the full protein repertoires of families of Chlamydia and Staphylococcus aureus genomes respectively) show that a measure of similarity obtained by locality sensitive hashing gives highly accurate results while offering a number of avenues which will lead to substantial performance improvements over BLAST..

An alternative approach to setting a mill

The conventional approach to setting a milling unit is essentially based on the desire to achieve a particular bagasse moisture content or fibre fill in each nip of the mill. This approach relies on the selection of the speed at which the mill will operate for the selected fibre rate. There is rarely any checking that the selected speed or the selected fibre fill is achieved and the same set of assumptions is generally carried over to use again in the next year. The conventional approach largely ignores the fact that the selection of mill settings actually determines the speed at which the mill will operate. Making an adjustment with the intent of changing the performance of the mill often also changes the speed of the mill as an unintended consequence. This paper presents an alternative approach to mill setting. The approach discussed makes use of mill feeding theory to define the relationship between fibre rate, mill speed and mill settings and uses that theory to provide an alternative means of determining the settings in some nips of the mill. Mill feeding theory shows that, as the feed work opening reduces, roll speed increases. The theory also shows that there is an optimal underfeed opening and Donnelly chute exit opening that will minimise roll speed and that the current South African guidelines appear to be well away from those optimal values.

eARTh : the dynamics of ontological representation

This Australian Indigenous creactive work and its Treatise promote ways of thinking about practice and research that extend well beyond the current discourse. It invites re-thinking on how research can be practice-led in new ways, and what that might mean for future students. When discussing the challenges of today, this work signifies how "Western Style" thinking and theory is wanting in so many ways. It engages a new dynamic and innovative way of theorising, encouraging future students to apply their full capacity of energy and wisdom. (Extract from examiners' reports.)

A distributed computing framework for all-to-all comparison problems

Distributed computation and storage have been widely used for processing of big data sets. For many big data problems, with the size of data growing rapidly, the distribution of computing tasks and related data can affect the performance of the computing system greatly. In this paper, a distributed computing framework is presented for high performance computing of All-to-All Comparison Problems. A data distribution strategy is embedded in the framework for reduced storage space and balanced computing load. Experiments are conducted to demonstrate the effectiveness of the developed approach. They have shown that about 88% of the ideal performance capacity have be achieved in multiple machines through using the approach presented in this paper.

Teacher education for high-poverty schools : keeping the bar high

For some time now, there has been a focus, both in Australia and internationally, on quality teaching as a fundamental component that affects the educational outcomes of all students. The question of how teacher education programs in Australia prepare effective teachers to work across all school settings-including low-SES schools-has been elevated to national prominence by data from the 20 12 Programme for International Student Assessment (PIS A), which revealed a fall in Australian students' world ranking across Mathematics, Reading and Science. Education is commonly acknowledged as a "foundation capability" that improves a person's life chances, including employment prospects, and it is widely understood to be a "route out of disadvantage" (McLachlan, Gilfillan, and Gordon 20 13). The Australian Bureau of Statistics 201 1- 12 data suggest that around 2.6 million (11.8%) Australians currently live under the poverty line (Phillips et a!. 2012, 8). According to the Organisation for Economic Cooperation and Development (OECD), despite the significant effects teachers have on student performance, disadvantaged schools are not always staffed with the highest quality teachers (see Darling-Hammond, 2006).

The global epidemiology and contribution of cannabis use and dependence to the global burden of disease: results from the GBD 2010 study

Aim Estimate the prevalence of cannabis dependence and its contribution to the global burden of disease. Methods Systematic reviews of epidemiological data on cannabis dependence (1990-2008) were conducted in line with PRISMA and meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines. Culling and data extraction followed protocols, with cross-checking and consistency checks. DisMod-MR, the latest version of generic disease modelling system, redesigned as a Bayesian meta-regression tool, imputed prevalence by age, year and sex for 187 countries and 21 regions. The disability weight associated with cannabis dependence was estimated through population surveys and multiplied by prevalence data to calculate the years of life lived with disability (YLDs) and disability-adjusted life years (DALYs). YLDs and DALYs attributed to regular cannabis use as a risk factor for schizophrenia were also estimated. Results There were an estimated 13.1 million cannabis dependent people globally in 2010 (point prevalence0.19% (95% uncertainty: 0.17-0.21%)). Prevalence peaked between 20-24 yrs, was higher in males (0.23% (0.2-0.27%)) than females (0.14% (0.12-0.16%)) and in high income regions. Cannabis dependence accounted for 2 million DALYs globally (0.08%; 0.05-0.12%) in 2010; a 22% increase in crude DALYs since 1990 largely due to population growth. Countries with statistically higher age-standardised DALY rates included the United States, Canada, Australia, New Zealand and Western European countries such as the United Kingdom; those with lower DALY rates were from Sub-Saharan Africa-West and Latin America. Regular cannabis use as a risk factor for schizophrenia accounted for an estimated 7,000 DALYs globally. Conclusion Cannabis dependence is a disorder primarily experienced by young adults, especially in higher income countries. It has not been shown to increase mortality as opioid and other forms of illicit drug dependence do. Our estimates suggest that cannabis use as a risk factor for schizophrenia is not a major contributor to population-level disease burden.