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.

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.

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.

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.

Adapting to concurrent expert evidence in medical litigation

In medical negligence litigation expert evidence has long played a dominant role. The trend towards the use of concurrent expert evidence is now well underway. However, for the lawyers and the doctors involved, the pathway is not yet familiar. Disputes have frequently arisen in the context of pre-hearing expert conclaves, given the adversarial nature of litigation and perhaps fuelled by fears of a less transparent process at this increasingly important stage. This article explains the concurrent expert evidence framework and examines areas of common dispute both in the conclaves and at trial, with a view to providing assistance to legal practitioners working in this area and the medical practitioners called upon to provide expert evidence in such litigation.

Global standard for the composition of infant formula: Recommendations of an ESPGHAN coordinated international expert group

The Codex Alimentarius Commission of the Food and Agriculture Organization of the United Nations (FAO) and the World Health Organization (WHO) develops food standards, guidelines and related texts for protecting consumer health and ensuring fair trade practices globally. The major part of the world's population lives in more than 160 countries that are members of the Codex Alimentarius. The Codex Standard on Infant Formula was adopted in 1981 based on scientific knowledge available in the 1970s and is currently being revised. As part of this process, the Codex Committee on Nutrition and Foods for Special Dietary Uses asked the ESPGHAN Committee on Nutrition to initiate a consultation process with the international scientific community to provide a proposal on nutrient levels in infant formulae, based on scientific analysis and taking into account existing scientific reports on the subject. ESPGHAN accepted the request and, in collaboration with its sister societies in the Federation of International Societies on Pediatric Gastroenterology, Hepatology and Nutrition, invited highly qualified experts in the area of infant nutrition to form an International Expert Group (IEG) to review the issues raised. The group arrived at recommendations on the compositional requirements for a global infant formula standard which are reported here.

Assessing performance in critical care nursing practice using the Benner Novice to expert model: A pilot study

Background It is often believed that by ensuring the ongoing completion of competency documents and life-long learning in nursing practice guarantees quality patient care. This is probably true in most cases where it provides reassurances that the nursing team is maintaining a safe “generalised” level of practice. However, competency does not always promise quality performance. There are a number of studies that have reported differences in what practitioners know and what they actually do despite being deemed competent. Aim The aim of this study was to assess whether our current competency documentation is fit for purpose and to ascertain whether performance assessment needs to be a key component in determining competence. Method 15 nurses within a General ICU who had been on the unit <4 years agreed to participate in this project. Using participant observation and assessing performance against key indicators of the Benner Novice to Expert5 model the participants were supported and assessed over the course of a ‘normal’ nursing shift. Results The results were surprising both positively and negatively. First, the nurses felt more empowered in their clinical decision making skills; second, it identified individual learning needs and milestones in educational development. There were some key challenges identified which included 5 nurses over estimating their level of competence, practice was still very much focused on task acquisition and skill and surprisingly some nurses still felt dominated by the other health professionals within the unit. Conclusion We found that the capacity and capabilities of our nursing workforce needs continual ongoing support especially if we want to move our staff from capable task-doer to competent performers. Using the key novice to expert indicators identified the way forward for us in how we assess performance and competence in practice particularly where promotion to higher grades is based on existing documentation.

A generic design environment for the rural industry knowledge acquisition

This paper describes a new knowledge acquisition method using a generic design environment where context-sensitive knowledge is used to build specific DSS for rural business. Although standard knowledge acquisition methods have been applied in rural business applications, uptake remains low and familiar weaknesses such as obsolescence and brittleness apply. We describe a decision support system (DSS) building environment where contextual factors relevant to the end users are directly taken into consideration. This "end user enabled design environment" (EUEDE) engages both domain experts in creating an expert knowledge base and business operators/end users (such as farmers) in using this knowledge for building their specific DSS. We document the knowledge organisation for the problem domain, namely a dairy industry application. This development involved a case-study research approach used to explore dairy operational knowledge. In this system end users can tailor their decision-making requirements using their own judgement to build specific DSSs. In a specific end user's farming context, each specific DSS provides expert suggestions to assist farmers in improving their farming practice. The paper also shows the environment's generic capability.

Expert Identity in Development of Core-Task-Oriented Working Practices for Mastering Demanding Situations

The point of departure in this dissertation was the practical safety problem of unanticipated, unfamiliar events and unexpected changes in the environment, the demanding situations which the operators should take care of in the complex socio-technical systems. The aim of this thesis was to increase the understanding of demanding situations and of the resources for coping with these situations by presenting a new construct, a conceptual model called Expert Identity (ExId) as a way to open up new solutions to the problem of demanding situations and by testing the model in empirical studies on operator work. The premises of the Core-Task Analysis (CTA) framework were adopted as a starting point: core-task oriented working practices promote the system efficiency (incl. safety, productivity and well-being targets) and that should be supported. The negative effects of stress were summarised and the possible countermeasures related to the operators' personal resources such as experience, expertise, sense of control, conceptions of work and self etc. were considered. ExId was proposed as a way to bring emotional-energetic depth into the work analysis and to supplement CTA-based practical methods to discover development challenges and to contribute to the development of complex socio-technical systems. The potential of ExId to promote understanding of operator work was demonstrated in the context of the six empirical studies on operator work. Each of these studies had its own practical objectives within the corresponding quite broad focuses of the studies. The concluding research questions were: 1) Are the assumptions made in ExId on the basis of the different theories and previous studies supported by the empirical findings? 2) Does the ExId construct promote understanding of the operator work in empirical studies? 3) What are the strengths and weaknesses of the ExId construct? The layers and the assumptions of the development of expert identity appeared to gain evidence. The new conceptual model worked as a part of an analysis of different kinds of data, as a part of different methods used for different purposes, in different work contexts. The results showed that the operators had problems in taking care of the core task resulting from the discrepancy between the demands and resources (either personal or external). The changes of work, the difficulties in reaching the real content of work in the organisation and the limits of the practical means of support had complicated the problem and limited the possibilities of the development actions within the case organisations. Personal resources seemed to be sensitive to the changes, adaptation is taking place, but not deeply or quickly enough. Furthermore, the results showed several characteristics of the studied contexts that complicated the operators' possibilities to grow into or with the demands and to develop practices, expertise and expert identity matching the core task. They were: discontinuation of the work demands, discrepancy between conceptions of work held in the other parts of organisation, visions and the reality faced by the operators, emphasis on the individual efforts and situational solutions. The potential of ExId to open up new paths to solving the problem of the demanding situations and its ability to enable studies on practices in the field was considered in the discussion. The results were interpreted as promising enough to encourage the conduction of further studies on ExId. This dissertation proposes especially contribution to supporting the workers in recognising the changing demands and their possibilities for growing with them when aiming to support human performance in complex socio-technical systems, both in designing the systems and solving the existing problems.

Eliciting and encoding expert knowledge on variable selection into classical or Bayesian species distribution models

The quality of species distribution models (SDMs) relies to a large degree on the quality of the input data, from bioclimatic indices to environmental and habitat descriptors (Austin, 2002). Recent reviews of SDM techniques, have sought to optimize predictive performance e.g. Elith et al., 2006. In general SDMs employ one of three approaches to variable selection. The simplest approach relies on the expert to select the variables, as in environmental niche models Nix, 1986 or a generalized linear model without variable selection (Miller and Franklin, 2002). A second approach explicitly incorporates variable selection into model fitting, which allows examination of particular combinations of variables. Examples include generalized linear or additive models with variable selection (Hastie et al. 2002); or classification trees with complexity or model based pruning (Breiman et al., 1984, Zeileis, 2008). A third approach uses model averaging, to summarize the overall contribution of a variable, without considering particular combinations. Examples include neural networks, boosted or bagged regression trees and Maximum Entropy as compared in Elith et al. 2006. Typically, users of SDMs will either consider a small number of variable sets, via the first approach, or else supply all of the candidate variables (often numbering more than a hundred) to the second or third approaches. Bayesian SDMs exist, with several methods for eliciting and encoding priors on model parameters (see review in Low Choy et al. 2010). However few methods have been published for informative variable selection; one example is Bayesian trees (O’Leary 2008). Here we report an elicitation protocol that helps makes explicit a priori expert judgements on the quality of candidate variables. This protocol can be flexibly applied to any of the three approaches to variable selection, described above, Bayesian or otherwise. We demonstrate how this information can be obtained then used to guide variable selection in classical or machine learning SDMs, or to define priors within Bayesian SDMs.

Consumers' emotional judgement of materials durability and disposal

The literature demonstrates that understanding relating to the use of materials in product design has been investigated from both engineering and design perspectives. However, none of these studies have explored the consumers’ concepts of the materials; rather they have focused on participants’ discussions of material samples. Consumers’ emotional reactions to the materials themselves or the consumers’ reaction to the durability of the materials have not been previously explored in depth. This research has investigated these issues and has found that consumers have very specific concepts about materials. Furthermore, the combinations of consumer concepts that are likely to elicit an emotional judgement by the consumer have also been identified. It was found that consumers are conscious of the durability of their products and the materials that they are made from. This knowledge contributes to the support of environmentally conscious design, as well as user-centered design knowledge and practice. An understanding of the emotion consumers attribute to the effect wear and aging had on the materials’ physical appearance has been achieved. This understanding of consumers’ emotional reactions to materials can contribute not only to design considerations but to knowledge regarding the promotion of prolonged product-user relationships.