Closing the gap : the next steps for the interaction of corporate reputation and psychological contract development

With an increasing body of literature linking the human resource management and marketing fields, one area receiving increased academic attention is how an organisation’s corporate reputation can be managed to attract potential recruits and shape their employment expectations through their psychological contracts. This paper seeks to enhance current models which focus on the interrelationship of corporate reputation and psychological contract theory. It is argued that a number of factors need to be considered in order the build a firmer foundation for such a theory. Firstly, a common understanding of the psychological contract needs to be established such that the focus on either expectations or promises is clarified. Secondly, the included components of the psychological contract need to be considered in light of their empirical founding and their relationship with one another. Thirdly, the interrelationship of corporate reputation, employer branding, identity and image needs to be explicated within the context of how they both influence and interrelate with the psychological contract. The final consideration surrounds the opportunity for potential employees to be considered within the corporate reputation literature as a significant stakeholder group.

Sensitivity of Dot-ELISA on Nitrocellulose Membranes in Comparison with ELISA on Polystyrene Plates for the Detection of Four Plant Viruses

ABSTR.4CT Senitivity of dot-immunobindinding ELf SA on nitrocellulose membrane (DotELISA)was compared with double-antibody sandwich ELISA (DAS-ELlSA) on polystyrene plates for the detection of bean yellow mosaic virus (BYMV), broad bean stain virus (WMV-2). Dot-ELISA was 2 and 1O times more sensitive than DAS-ELISA for the detection of BBSV and WMV-2, respectively, whereas DAS-ELISA was more sensitive than Dot-ELiSA for {he detection of BYMV. Both techniques were equally sensitive for the detection of BYDV. Using one day instead uf the two-day procedure, the four viruses were still detectable and the ralative sensitivity of both techniques remained the same.

Hierarchical Bayesian models for estimating the extent of plant pest invasions

Plant biosecurity requires statistical tools to interpret field surveillance data in order to manage pest incursions that threaten crop production and trade. Ultimately, management decisions need to be based on the probability that an area is infested or free of a pest. Current informal approaches to delimiting pest extent rely upon expert ecological interpretation of presence / absence data over space and time. Hierarchical Bayesian models provide a cohesive statistical framework that can formally integrate the available information on both pest ecology and data. The overarching method involves constructing an observation model for the surveillance data, conditional on the hidden extent of the pest and uncertain detection sensitivity. The extent of the pest is then modelled as a dynamic invasion process that includes uncertainty in ecological parameters. Modelling approaches to assimilate this information are explored through case studies on spiralling whitefly, Aleurodicus dispersus and red banded mango caterpillar, Deanolis sublimbalis. Markov chain Monte Carlo simulation is used to estimate the probable extent of pests, given the observation and process model conditioned by surveillance data. Statistical methods, based on time-to-event models, are developed to apply hierarchical Bayesian models to early detection programs and to demonstrate area freedom from pests. The value of early detection surveillance programs is demonstrated through an application to interpret surveillance data for exotic plant pests with uncertain spread rates. The model suggests that typical early detection programs provide a moderate reduction in the probability of an area being infested but a dramatic reduction in the expected area of incursions at a given time. Estimates of spiralling whitefly extent are examined at local, district and state-wide scales. The local model estimates the rate of natural spread and the influence of host architecture, host suitability and inspector efficiency. These parameter estimates can support the development of robust surveillance programs. Hierarchical Bayesian models for the human-mediated spread of spiralling whitefly are developed for the colonisation of discrete cells connected by a modified gravity model. By estimating dispersal parameters, the model can be used to predict the extent of the pest over time. An extended model predicts the climate restricted distribution of the pest in Queensland. These novel human-mediated movement models are well suited to demonstrating area freedom at coarse spatio-temporal scales. At finer scales, and in the presence of ecological complexity, exploratory models are developed to investigate the capacity for surveillance information to estimate the extent of red banded mango caterpillar. It is apparent that excessive uncertainty about observation and ecological parameters can impose limits on inference at the scales required for effective management of response programs. The thesis contributes novel statistical approaches to estimating the extent of pests and develops applications to assist decision-making across a range of plant biosecurity surveillance activities. Hierarchical Bayesian modelling is demonstrated as both a useful analytical tool for estimating pest extent and a natural investigative paradigm for developing and focussing biosecurity programs.

Factors affecting somatic embryogenesis and transformation in modern plant breeding

Somatic embryogenesis and transformation systems are indispensable modern plant breeding components since they provide an alternative platform to develop control strategies against the plethora of pests and diseases affecting many agronomic crops. This review discusses some of the factors affecting somatic embryogenesis and transformation, highlights the advantages and limitations of these systems and explores these systems as breeding tools for the development of crops with improved agronomic traits. The regeneration of non-chimeric transgenic crops through somatic embryogenesis with introduced disease and pest-resistant genes for instance, would be of significant benefit to growers worldwide.

Closing the gap between policy and 'Law' : Indigenous homelands and a working future

The Northern Territory Government's Working Future: Outstations/Homelands (2009) policy statement gives effect to the Council of Australian Government's Closing the Gap policy on Indigenous housing and remote service delivery. These policies mark a radical shift in public policy that winds back the outstations and homelands movement that began in the 1970's. This paper examines Indigenous homelands policy and considers whether these policies are consistent with the Indigenous human rights and in particular the United Nations Declaration on the Rights of Indigenous Peoples (2007), which Australia endorsed in 2009. The author argues that the current homelands policy breaches a number of Indigenous human rights and promotes assimiliation by forcing Indigenous Australians to relocate to access basic services such as health, housing and education. As a consequence these policies are counter-intuitive to the overall Closing the Gap goals of improving Indigenous health outcomes because they fail to take into account the importance of country and culture to Indigenous wellbeing. She concludes that Australian governments need to formulate a homelands policy that is consistent with Indigenous human rights and in particular the right of self determination, enjoyment of culture and protection against forced assimilation.

Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.

Closing the gap between bandit and full-information online optimization : high-probability regret bound

We demonstrate a modification of the algorithm of Dani et al for the online linear optimization problem in the bandit setting, which allows us to achieve an O( \sqrt{T ln T} ) regret bound in high probability against an adaptive adversary, as opposed to the in expectation result against an oblivious adversary of Dani et al. We obtain the same dependence on the dimension as that exhibited by Dani et al. The results of this paper rest firmly on those of Dani et al and the remarkable technique of Auer et al for obtaining high-probability bounds via optimistic estimates. This paper answers an open question: it eliminates the gap between the high-probability bounds obtained in the full-information vs bandit settings.