Open content licensing of public sector information and the risk of tortious liability for Australian Governments

There has been an increasing interest by governments worldwide in the potential benefits of open access to public sector information (PSI). However, an important question remains: can a government incur tortious liability for incorrect information released online under an open content licence? This paper argues that the release of PSI online for free under an open content licence, specifically a Creative Commons licence, is within the bounds of an acceptable level of risk to government, especially where users are informed of the limitations of the data and appropriate information management policies and principles are in place to ensure accountability for data quality and accuracy.

Construction safety : development of an assessment tool to reduce risk on building sites

Australian construction and building workers are exposed to serious workplace risks - including injury, illness and death - and although there have been improvements in occupational health and safety (OHS) performance over the past 20 years, the injury and fatality rate in the Australian construction industry remains a matter of concern. The concept of safety culture is rapidly being adopted in the industry, including recognising the critical role that organisational leaders play in overall safety performance. This paper reviews recent research in construction safety leadership and provides some examples and applications relevant to risk reduction in the workforce. By focusing on developing safety competency in those that fulfil safety critical roles, and clearly articulating the relevant safety management tasks, leaders can positively influence the organisation’s safety culture. Finally, some promising research on Safety Effectiveness Indicators (SEIs) may be an industry-friendly solution to reducing workplace risks across the industry, by providing a credible, accurate, and timely measure of safety performance.

A Bayesian approach to assess interaction between known risk factors: The risk of lung cancer from exposure to asbestos and smoking

We review the literature on the combined effect of asbestos exposure and smoking on lung cancer, and explore a Bayesian approach to assess evidence of interaction. Previous approaches have focussed on separate tests for an additive or multiplicative relation. We extend these approaches by exploring the strength of evidence for either relation using approaches which allow the data to choose between both models. We then compare the different approaches.

The level and quality of Value-at-Risk disclosure by commercial banks

In this paper we study both the level of Value-at-Risk (VaR) disclosure and the accuracy of the disclosed VaR figures for a sample of US and international commercial banks. To measure the level of VaR disclosures, we develop a VaR Disclosure Index that captures many different facets of market risk disclosure. Using panel data over the period 1996–2005, we find an overall upward trend in the quantity of information released to the public. We also find that Historical Simulation is by far the most popular VaR method. We assess the accuracy of VaR figures by studying the number of VaR exceedances and whether actual daily VaRs contain information about the volatility of subsequent trading revenues. Unlike the level of VaR disclosure, the quality of VaR disclosure shows no sign of improvement over time. We find that VaR computed using Historical Simulation contains very little information about future volatility.

High-density lipoprotein and the risk of recurrent venous thromboembolism

BACKGROUND - High-density lipoprotein (HDL) protects against arterial atherothrombosis, but it is unknown whether it protects against recurrent venous thromboembolism. METHODS AND RESULTS - We studied 772 patients after a first spontaneous venous thromboembolism (average follow-up 48 months) and recorded the end point of symptomatic recurrent venous thromboembolism, which developed in 100 of the 772 patients. The relationship between plasma lipoprotein parameters and recurrence was evaluated. Plasma apolipoproteins AI and B were measured by immunoassays for all subjects. Compared with those without recurrence, patients with recurrence had lower mean (±SD) levels of apolipoprotein AI (1.12±0.22 versus 1.23±0.27 mg/mL, P<0.001) but similar apolipoprotein B levels. The relative risk of recurrence was 0.87 (95% CI, 0.80 to 0.94) for each increase of 0.1 mg/mL in plasma apolipoprotein AI. Compared with patients with apolipoprotein AI levels in the lowest tertile (<1.07 mg/mL), the relative risk of recurrence was 0.46 (95% CI, 0.27 to 0.77) for the highest-tertile patients (apolipoprotein AI >1.30 mg/mL) and 0.78 (95% CI, 0.50 to 1.22) for midtertile patients (apolipoprotein AI of 1.07 to 1.30 mg/mL). Using nuclear magnetic resonance, we determined the levels of 10 major lipoprotein subclasses and HDL cholesterol for 71 patients with recurrence and 142 matched patients without recurrence. We found a strong trend for association between recurrence and low levels of HDL particles and HDL cholesterol. CONCLUSIONS - Patients with high levels of apolipoprotein AI and HDL have a decreased risk of recurrent venous thromboembolism. © 2007 American Heart Association, Inc.

The impact of rhetoric and reality on community anticipation of risk in the development of multi-purpose services (MPS) : A grounded theory study

better health service.Conclusion:This research provides an insight into the perceptions of the rhetoric and reality of community member involvement in the process of developing multi-purpose services. It revealed a grounded theory in which fear and trust were intrinsic to a process of changing from a traditional hospital service to the acceptance of a new model of health care provided at a multi-purpose service.

Age and gender comparisons of driving while sleepy : behaviours and risk perceptions

To assist road safety professionals in developing effective strategies to combat the risk associated with driving while fatigued, a survey was administered to 1000 Australian drivers. Participants reported their past behaviours in regards to driving while sleepy and their perceptions of risk associated with driving fatigued as compared to speeding and driving under the influence of alcohol. Although participants appeared to be aware of the substantial risk associated with driving while sleepy, many drivers reported that they frequently drive when sleepy. Age and gender comparisons, revealed that risk taking behaviour in regards to driving while sleepy is occurring across all age groups and in both male and female drivers. Overall young to middle age drivers and male drivers reported the highest frequency of driving while sleepy and reported the lowest perceived personal risk in regards to driving while sleepy.

Measuring risk and blameworthiness in the sentencing of criminal defendants : an exploratory study in Western Australia's Higher Courts

The focal concern perspective dominates quantitative explorations of judicial sentencing. A critical argument underlying this perspective is the role of judicial assessments of risk and blameworthiness. Prior research has not generally explored how these two concepts fit together. This study provides an empirical test of the focal concerns perspective by examining the latent structure among the measures traditionally used in sentencing research, and investigates the extent to which focal concerns can be applied in a non-US jurisdiction. Using factor analysis (as suggested by prior research), we find evidence of distinct factors of risk and blameworthiness, with separate and independent effects on sentencing outcomes. We also identify the need for further development of the focal concerns perspective, especially around the role of perceptual shorthand.

Risk of falls, injurious falls, and other injuries resulting from visual impairment among older adults with age-related macular degeneration

Purpose: Age-related macular degeneration (AMD) is the leading cause of irreversible visual impairment among older adults. This study explored the relationship between AMD, falls risk and other injuries and identified visual risk factors for these adverse events. Methods: Participants included 76 community-dwelling individuals with a range of severity of AMD (mean age, 77.0±6.9 years). Baseline assessment included binocular visual acuity, contrast sensitivity and merged visual fields. Participants completed monthly falls and injury diaries for one year following the baseline assessment. Results: Overall, 74% of participants reported having either a fall, injurious fall or other injury. Fifty-four percent of participants reported a fall and 30% reported more than one fall; of the 102 falls reported, 63% resulted in an injury. Most occurred outdoors (52%), between late morning and late afternoon (61%) and when navigating on level ground (62%). The most common non-fall injuries were lacerations (36%) and collisions with an object (35%). Reduced contrast sensitivity and visual acuity were associated with increased fall rate, after controlling for age, gender, cognitive function, cataract severity and self-reported physical function. Reduced contrast sensitivity was the only significant predictor of falls and other injuries. Conclusion: Among older adults with AMD, increased visual impairment was significantly associated with an increased incidence of falls and other injuries. Reduced contrast sensitivity was significantly associated with increased rates of falls, injurious falls and injuries, while reduced visual acuity was only associated with increased falls risk. These findings have important implications for the assessment of visually impaired older adults.

Unlicensed drivers : are they high risk?

- Road safety implications of unlicensed driving - Present results from three studies examining: the crash involvement of unlicensed drivers; the impact of licence disqualification on offending; characteristics of unlicensed driving offenders - Countermeasure implications - Discussion of high-risk groups and innovative countermeasure options

Convexity, Classification, and Risk Bounds

Many of the classification algorithms developed in the machine learning literature, including the support vector machine and boosting, can be viewed as minimum contrast methods that minimize a convex surrogate of the 0–1 loss function. The convexity makes these algorithms computationally efficient. The use of a surrogate, however, has statistical consequences that must be balanced against the computational virtues of convexity. To study these issues, we provide a general quantitative relationship between the risk as assessed using the 0–1 loss and the risk as assessed using any nonnegative surrogate loss function. We show that this relationship gives nontrivial upper bounds on excess risk under the weakest possible condition on the loss function—that it satisfies a pointwise form of Fisher consistency for classification. The relationship is based on a simple variational transformation of the loss function that is easy to compute in many applications. We also present a refined version of this result in the case of low noise, and show that in this case, strictly convex loss functions lead to faster rates of convergence of the risk than would be implied by standard uniform convergence arguments. Finally, we present applications of our results to the estimation of convergence rates in function classes that are scaled convex hulls of a finite-dimensional base class, with a variety of commonly used loss functions.

Rademacher and Gaussian complexities: Risk bounds and structural results

We investigate the use of certain data-dependent estimates of the complexity of a function class, called Rademacher and Gaussian complexities. In a decision theoretic setting, we prove general risk bounds in terms of these complexities. We consider function classes that can be expressed as combinations of functions from basis classes and show how the Rademacher and Gaussian complexities of such a function class can be bounded in terms of the complexity of the basis classes. We give examples of the application of these techniques in finding data-dependent risk bounds for decision trees, neural networks and support vector machines.