Engaging expert contractors: The work health and safety obligations of the business or undertaking

This article examines the legal principles governing the statutory work health and safety general duties of principals who engage expert contractors to carry out work beyond the expertise of the principal. The article examines recent case law in which superior courts accepted the principal’s argument that the engagement of the expert contractor was sufficient to discharge the principal’s statutory work health and safety general duty. It then reframes the debate within the principles of systematic work health and safety management, and key provisions in the harmonised Work Health and Safety Acts—the primary duty of care; the key underpinning principles; the positive and proactive officer’s duty; and the horizontal duty of consultation, cooperation and coordination. It argues that it is likely that courts examining the issue of the principal’s work health and safety obligations under the harmonised Work Health and Safety Acts will require principals to do more to actively manage the work of expert contractors to ensure the health and safety of all workers and others potentially affected by the work.

Using Bayesian Mixture Models That Combine Expert Knowledge and GIS Data to Define Ecoregions

Conservation planning and management programs typically assume relatively homogeneous ecological landscapes. Such “ecoregions” serve multiple purposes: they support assessments of competing environmental values, reveal priorities for allocating scarce resources, and guide effective on-ground actions such as the acquisition of a protected area and habitat restoration. Ecoregions have evolved from a history of organism–environment interactions, and are delineated at the scale or level of detail required to support planning. Depending on the delineation method, scale, or purpose, they have been described as provinces, zones, systems, land units, classes, facets, domains, subregions, and ecological, biological, biogeographical, or environmental regions. In each case, they are essential to the development of conservation strategies and are embedded in government policies at multiple scales.

Automated fit quantification of tibial nail designs during the insertion using computer three-dimensional modelling

Intramedullary nailing is the standard fixation method for displaced diaphyseal fractures of the tibia. An optimal nail design should both facilitate insertion and anatomically fit the bone geometry at its final position in order to reduce the risk of stress fractures and malalignments. Due to the nonexistence of suitable commercial software, we developed a software tool for the automated fit assessment of nail designs. Furthermore, we demonstrated that an optimised nail, which fits better at the final position, is also easier to insert. Three-dimensional models of two nail designs and 20 tibiae were used. The fitting was quantified in terms of surface area, maximum distance, sum of surface areas and sum of maximum distances by which the nail was protruding into the cortex. The software was programmed to insert the nail into the bone model and to quantify the fit at defined increment levels. On average, the misfit during the insertion in terms of the four fitting parameters was smaller for the Expert Tibial Nail Proximal bend (476.3 mm2, 1.5 mm, 2029.8 mm2, 6.5 mm) than the Expert Tibial Nail (736.7 mm2, 2.2 mm, 2491.4 mm2, 8.0 mm). The differences were statistically significant (p ≤ 0.05). The software could be used by nail implant manufacturers for the purpose of implant design validation.

Expert Opinion: Serious Concerns regarding Western Australian Planning Commission (WAPC) Draft Policy 3.7 “Planning for Bushfire Risk Management” and associated Guidelines (May 2014)

10 page document containing expert assessment of shortcomings of Western Australian State Planning Policy SPP3.7- Planning for Bushfire Risk Management. Document produced on behalf of QUT and submitted to and published by the WAPC as part of their public consultation process for their draft policy.

Psychometric validation of the Dysexecutive Questionnaire (DEX)

This study reported on the validation of the psychometric properties, the factorability, validity, and sensitivity of the Dysexecutive Questionnaire (DEX) in 3 clinical and nonclinical samples. A mixed sample of 997 participants—community (n = 663), psychiatric (depressed [n = 92] and anxious [n = 122]), and neurologically impaired (n = 120)—completed self-report questionnaires assessing executive dysfunction, depression, anxiety, stress, general self-efficacy, and satisfaction with life. Before analyses the data were randomly split into 2 subsets (A and B). Exploratory factor analysis performed on Subset A produced a 3-factor model (Factor 1: Inhibition, Factor 2: Volition, and Factor 3: Social Regulation) in which 15 of the original 20 items provided a revised factor structure that was superior to all other structures. A series of confirmatory factor analyses performed on Subset B confirmed that this revised factor structure was valid and reliable. The revised structure, labeled the DEX-R, was found to be a reliable and valid tool for assessing behavioral symptoms of dysexecutive functioning in mixed community, psychiatric, and neurological samples.

Exercise barriers self-efficacy : development and validation of a subcale for individuals with cancer-related lymphedema

Background No tool exists to measure self-efficacy for overcoming lymphedema-related exercise barriers in individuals with cancer-related lymphedema. However, an existing scale measures confidence to overcome general exercise barriers in cancer survivors. Therefore, the purpose of this study was to develop, validate and assess the reliability of a subscale, to be used in conjunction with the general barriers scale, for determining exercise barriers self-efficacy in individuals facing lymphedema-related exercise barriers. Methods A lymphedema-specific exercise barriers self-efficacy subscale was developed and validated using a cohort of 106 cancer survivors with cancer-related lymphedema, from Brisbane, Australia. An initial ten-item lymphedema-specific barrier subscale was developed and tested, with participant feedback and principal components analysis results used to guide development of the final version. Validity and test-retest reliability analyses were conducted on the final subscale. Results The final lymphedema-specific subscale contained five items. Principal components analysis revealed these items loaded highly (> 0.75) on a separate factor when tested with a well-established nine-item general barriers scale. The final five-item subscale demonstrated good construct and criterion validity, high internal consistency (Cronbach’s alpha=0.93) and test-retest reliability (ICC=0.67, p< 0.01). Conclusions A valid and reliable lymphedema-specific subscale has been developed to assess exercise barriers self-efficacy in individuals with cancer-related lymphedema. This scale can be used in conjunction with an existing general exercise barriers scale to enhance exercise adherence in this understudied patient group.

Development and validation of the Self-Gifting Consumer Behaviour scale

Self-gifting consumer behaviour (SGCB) is on the rise as consumers seek reward and therapeutic benefits from their shopping experiences. SGCB is defined as personally symbolic, self-communication through special indulgences, which tend to be premeditated and highly context bound. Prior research into the measurement of this growing behavioural phenomenon has been fragmented because of differences in conceptualisation. This research builds upon the prior literature and through a series of qualitative and quantitative studies, develops a valid, multidimensional measure of SGCB that will be useful for future quantitative inquiry into self-gifting consumption.

Learning the learning rate for prediction with expert advice

Most standard algorithms for prediction with expert advice depend on a parameter called the learning rate. This learning rate needs to be large enough to fit the data well, but small enough to prevent overfitting. For the exponential weights algorithm, a sequence of prior work has established theoretical guarantees for higher and higher data-dependent tunings of the learning rate, which allow for increasingly aggressive learning. But in practice such theoretical tunings often still perform worse (as measured by their regret) than ad hoc tuning with an even higher learning rate. To close the gap between theory and practice we introduce an approach to learn the learning rate. Up to a factor that is at most (poly)logarithmic in the number of experts and the inverse of the learning rate, our method performs as well as if we would know the empirically best learning rate from a large range that includes both conservative small values and values that are much higher than those for which formal guarantees were previously available. Our method employs a grid of learning rates, yet runs in linear time regardless of the size of the grid.

Enterprise business technology governance: A validation of three technology-governance competencies for boards of directors

The competent leadership and governance of digital transformation needs to involve the board of directors. The reported lack of such capability in boards is becoming a pressing issue. Underpinning leadership in such transformation are the competencies to effectively govern Enterprise Technology (ETG). In this paper we take the position that ETG competencies are essential in boards because competent enterprise business technology governance has been shown to contribute to increased revenue, profit, and returns. We report the industry validation processes of a set of three board-of-director competencies needed for effective ETG related to strategy and planning; investment and risk; and, innovation and value creation. We conclude that gaps in board ETG competence remain.

Prior and posterior linear pooling for combining expert opinions: Uses and impact on Bayesian Networks

The use of expert knowledge to quantify a Bayesian Network (BN) is necessary when data is not available. This however raises questions regarding how opinions from multiple experts can be used in a BN. Linear pooling is a popular method for combining probability assessments from multiple experts. In particular, Prior Linear Pooling (PrLP), which pools opinions then places them into the BN is a common method. This paper firstly proposes an alternative pooling method, Posterior Linear Pooling (PoLP). This method constructs a BN for each expert, then pools the resulting probabilities at the nodes of interest. Secondly, it investigates the advantages and disadvantages of using these pooling methods to combine the opinions of multiple experts. Finally, the methods are applied to an existing BN, the Wayfinding Bayesian Network Model, to investigate the behaviour of different groups of people and how these different methods may be able to capture such differences. The paper focusses on 6 nodes Human Factors, Environmental Factors, Wayfinding, Communication, Visual Elements of Communication and Navigation Pathway, and three subgroups Gender (female, male),Travel Experience (experienced, inexperienced), and Travel Purpose (business, personal) and finds that different behaviors can indeed be captured by the different methods.