Making a match: Combining theory and evidence in policy-oriented macroeconomic modeling

A persistent question in the development of models for macroeconomic policy analysis has been the relative role of economic theory and evidence in their construction. This paper looks at some popular strategies that involve setting up a theoretical or conceptual model (CM) which is transformed to match the data and then made operational for policy analysis. A dynamic general equilibrium model is constructed that is similar to standard CMs. After calibration to UK data it is used to examine the utility of formal econometric methods in assessing the match of the CM to the data and also to evaluate some standard model-building strategies. Keywords: Policy oriented economic modeling; Model evaluation; VAR models

Teachers reporting child sexual abuse : towards evidence-based reform of law, policy and practice

This report presents the results of the largest study ever conducted into the law, policy and practice of primary school teachers’ reporting of child sexual abuse in New South Wales, Queensland and Western Australia. The study included the largest Australian survey of teachers about reporting sexual abuse, in both government and non-government schools (n=470). Our research has produced evidence-based findings to enhance law, policy and practice about teachers’ reporting of child sexual abuse. The major benefits of our findings and recommendations are to: • Show how the legislation in each State can be improved; • Show how the policies in government and non-government school sectors can be improved; and • Show how teacher training can be improved. These improvements can enhance the already valuable contribution that teachers are making to identify cases of child sexual abuse. Based on the findings of our research, this report proposes solutions to issues in seven key areas of law, policy and practice. These solutions are relevant for State Parliaments, government and non-government educational authorities, and child protection departments. The solutions in each State are practicable, low-cost, and align with current government policy approaches. Implementing these solutions will: • protect more children from sexual abuse; • save cost to governments and society; • develop a professional teacher workforce better equipped for their child protection role; and • protect government and school authorities from legal liability.

Generation next : post-cinema Australian moviemaking, innovation and implications for cultural policy

The Australian screen industries are a leading domestic creative industry sector at a crossroad. New production, distribution and exhibition technologies are challenging traditional models of ‘filmmaking’. For the screen industries to remain competitive they must renovate business models for an emerging marketplace. This paper is a preliminary examination of three key aspects of next generation filmmaking: post-cinema approaches to screen production, emerging production and business models, and issues for policy.

Transition pedagogy : a third generation approach to FYE : a case study of policy and practice for the higher education sector

Current research and practice related to the first year experience (FYE) of commencing higher education students are still mainly piecemeal rather than institution-wide with institutions struggling to achieve cross-institutional integration, coordination and coherence of FYE policy and practice. Drawing on a decade of FYE-related research including an ALTC Senior Fellowship and evidence at a large Australian metropolitan university, this paper explores how one institution has addressed that issue by tracing the evolution and maturation of strategies that ultimately conceptualize FYE as “everybody's business.” It is argued that, when first generation co-curricular and second generation curricular approaches are integrated and implemented through an intentionally designed curriculum by seamless partnerships of academic and professional staff in a whole-of-institution transformation, we have a third generation approach labelled here as transition pedagogy. It is suggested that transition pedagogy provides the optimal vehicle for dealing with the increasingly diverse commencing student cohorts by facilitating a sense of engagement, support and belonging. What is presented here is an example of transition pedagogy in action.

Mining robotics

Mining is the process of extracting mineral resources from the Earth for commercial value. It is an ancient human activity which can be traced back to Palaeolithic times (43 000 years ago), where for example the mineral hematite was mined to produce the red pigment ochre. The importance of many mined minerals is reflected in the names of the major milestones in human civilizations: the stone, copper, bronze, and iron ages. Much later coal provided the energy that was critical to the industrial revolution and still underpins modern society, creating 38% of world energy generation today. Ancient mines used human and later animal labor and broke rock using stone tools, heat, and water, and later iron tools. Today’s mines are heavily mechanized with large diesel and electrically powered vehicles, and rock is broken with explosives or rock cutting machines.

Reactive navigation and opportunistic localization for autonomous underground mining vehicles

This paper describes an autonomous navigation system for a large underground mining vehicle. The control architecture is based on a robust reactive wall-following behaviour. To make it purposeful we provide driving hints derived from an approximate nodal-map. For most of the time, the vehicle is driven with weak localization (odometry). This need only be improved at intersections where decisions must be made – a technique we refer to as opportunistic localization. The paper briefly reviews absolute and relative navigation strategies, and describes an implementation of a reactive navigation system on a 30 tonne Load-Haul-Dump truck. This truck has achieved full-speed autonomous operation at an artificial test mine, and subsequently, at a operational underground mine.

Dragline automation - a decade of development : shared autonomy for improving mining equipment productivity

Draglines are massive machines commonly used in surface mining to strip overburden, revealing the targeted minerals for extraction. Automating some or all of the phases of operation of these machines offers the potential for significant productivity and maintenance benefits. The mining industry has a history of slow uptake of automation systems due to the challenges contained in the harsh, complex, three-dimensional (3D), dynamically changing mine operating environment. Robotics as a discipline is finally starting to gain acceptance as a technology with the potential to assist mining operations. This article examines the evolution of robotic technologies applied to draglines in the form of machine embedded intelligent systems. Results from this work include a production trial in which 250,000 tons of material was moved autonomously, experiments demonstrating steps towards full autonomy, and teleexcavation experiments in which a dragline in Australia was tasked by an operator in the United States.

Mining agreements : negotiated frameworks in the Australian minerals sector

Discusses the role of negotiated frameworks as a regulatory mechanism in the development of Australia's premier industry of the 20th century.

Overview of the INEX 2009 XML mining track : clustering and classification of XML documents

This report explains the objectives, datasets and evaluation criteria of both the clustering and classification tasks set in the INEX 2009 XML Mining track. The report also describes the approaches and results obtained by the different participants.

Access to public sector information : law, technology and policy

On the back of the growing capacity of networked digital information technologies to process and visualise large amounts of information in a timely, efficient and user-driven manner we have seen an increasing demand for better access to and re-use of public sector information (PSI). The story is not a new one. Share knowledge and together we can do great things; limit access and we reduce the potential for opportunity. The two volumes of this book seek to explain and analyse this global shift in the way we manage public sector information. In doing so they collect and present papers, reports and submissions on the topic by leading authors and institutions from across the world. These in turn provide people tasked with mapping out and implementing information policy with reference material and practical guidance. Volume 1 draws together papers on the topic by policymakers, academics and practitioners while Volume 2 presents a selection of the key reports and submissions that have been published over the last few years.

Specifying and enforcing a fine-grained information flow policy : model and experiments

In this paper we present a model for defining and enforcing a fine-grained information flow policy. We describe how the policy can be enforced on a typical computer and present experiments using the proposed model. A key feature of the model is that it allows the expression of rules which detail precisely which information elements are allowed to mix together. For example, the model allows the expression of a policy which forbids a doctor from mixing the personal medical details of the patients. The enforcement mechanisms tracks and records information flows within the system so that dynamic changes to the policy can be made with respect to information elements which may have propagated to different locations in the system.

The development of strategies to drive government and academic policy to underpin e-portfolio practice

The impact of government policy can become a strong enabler for the use of e-portfolios to support learning and employability. E-portfolio policy and practice seeks to draw together the different elements of integrated education and learning, graduate attributes, employability skills, professional competencies and lifelong learning, ultimately to support an engaged and productive workforce. Drawing on and updating the research findings from a nationwide research study conducted as part of the Australian ePortfolio Project, the present chapter discusses two important areas of the e-portfolio environment, government policy and academic policy. The focus is on those jurisdictions where government and academic policy issues have had a significant impact on e-portfolio practice, such as the European Union, the Netherlands, Scandinavian countries and the United Kingdom, as well as in Australia and New Zealand. These jurisdictions are of interest as government policy discussions are currently focusing on the need for closer integration between the different education and employment sectors. Finally, issues to be considered as well as strategies for driving policy decision making are presented.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

Safety impacts of alcohol and other drugs in the construction industry : a research methodology

Anecdotal evidence from the infrastructure and building sectors highlights issues of drugs and alcohol and its association with safety risk on construction sites. Operating machinery and mobile equipment, proximity to live traffic together with congested sites, electrical equipment and operating at heights conspire to accentuate the potential adverse impact of drugs and alcohol in the workplace. While most Australian jurisdictions have identified this as a critical safety issue, information is limited regarding the prevalence of alcohol and other drugs in the workplace and there is limited evidential guidance regarding how to effectively and efficiently address such an issue. No known study has scientifically evaluated the relationship between the use of drugs and alcohol and safety impacts in construction, and there has been only limited adoption of nationally coordinated strategies, supported by employers and employees to render it socially unacceptable to arrive at a construction workplace with impaired judgement from drugs and alcohol. A nationally consistent collaborative approach across the construction workforce - involving employers and employees; clients; unions; contractors and sub-contractors is required to engender a cultural change in the construction workforce – in a similar manner to the on-going initiative in securing a cultural change to drink-driving in our society where peer intervention and support is encouraged. This study has four key objectives. Firstly, using the standard World Health Organisation AUDIT, a national qualitative and quantitative assessment of the use of drugs and alcohol will be carried out. This will build upon similar studies carried out in the Australian energy and mining sectors. Secondly, the development of an appropriate industry policy will adopt a non-punitive and rehabilitative approach developed in consultation with employers and employees across the infrastructure and building sectors, with the aim it be adopted nationally for adoption at the construction workplace. Thirdly, an industry-specific cultural change management program will be developed through a nationally collaborative approach to reducing the risk of impaired performance on construction sites and increasing workers’ commitment to drugs and alcohol safety. Finally, an implementation plan will be developed from data gathered from both managers and construction employees. Such an approach stands to benefit not only occupational health and safety, through a greater understanding of the safety impacts of alcohol and other drugs at work, but also alcohol and drug use as a wider community health issue. This paper will provide an overview of the background and significance of the study as well as outlining the proposed methodology that will be used to evaluate the safety impacts of alcohol and other drugs in the construction industry.