From complexity to category: Responding to diagnostic uncertainties of autistic spectrum disorders

Objective: Recent data from Education Queensland has identified rising numbers of children receiving diagnoses of autistic spectrum disorder (ASD). Faced with funding diagnostic pressures, in clinical situations that are complex and inherently uncertain, it is possible that specialists err on the side of a positive diagnosis. This study examines the extent to which possible overinclusion of ASD diagnosis may exist in the presence of uncertainty and factors potentially related to this practice in Queensland. Methods: Using anonymous self-report, all Queensland child psychiatrists and paediatricians who see paediatric patients with development/behavioural problems were surveyed and asked whether they had ever specified an ASD diagnosis in the presence of diagnostic uncertainty. Using logistic regression, elicited responses to the diagnostic uncertainty questions were related to other clinical- and practice-related characteristics. Results: Overall, 58% of surveyed psychiatrists and paediatricians indicated that, in the face of diagnostic uncertainty, they had erred on the side of providing an ASD diagnosis for educational ascertainment and 36% of clinicians had provided an autism diagnosis for Carer's Allowance when Centrelink diagnostic specifications had not been met. Conclusion: In the absence of definitive biological markers, ASD remains a behavioural diagnosis that is often complex and uncertain. In response to systems that demand a categorical diagnostic response, specialists are providing ASD diagnoses, even when uncertain. The motivation for this practice appears to be a clinical risk/benefit analysis of what will achieve the best outcomes for children. It is likely that these practices will continue unless systems change eligibility to funding based on functional impairment rather than medical diagnostic categories.

An evolutionary economic perspective on technical change and adjustment in cane harvesting systems in the Australian sugar industry

Australian sugar-producing regions have differed in terms of the extent and rate of incorporation of new technology into harvesting systems. The Mackay sugar industry has lagged behind most other sugar-producing regions in this regard. The reasons for this are addressed by invoking an evolutionary economics perspective. The development of harvesting systems, and the role of technology in shaping them, is mapped and interpreted using the concept of path dependency. Key events in the evolution of harvesting systems are identified, which show how the past has shaped the regional development of harvesting systems. From an evolutionary economics perspective, the outcomes observed are the end result of a specific history.

Structural change in macroeconomic time series: A complex systems perspective

We demonstrate that the process of generating smooth transitions Call be viewed as a natural result of the filtering operations implied in the generation of discrete-time series observations from the sampling of data from an underlying continuous time process that has undergone a process of structural change. In order to focus discussion, we utilize the problem of estimating the location of abrupt shifts in some simple time series models. This approach will permit its to address salient issues relating to distortions induced by the inherent aggregation associated with discrete-time sampling of continuous time processes experiencing structural change, We also address the issue of how time irreversible structures may be generated within the smooth transition processes. (c) 2005 Elsevier Inc. All rights reserved.

Tracks of Change - the changing value commitments of non-profit organisations

If nonprofit organisations are moving towards more market oriented ways of operating, is this changing the traditional meanings and value of commitments associated with their activities? This article discusses the findings of a research project conducted by the University of Queensland into the impact that changes in government policies are having on the community services sector, in particular disability services. The values and belief systems traditionally associated with the sector were found to be fundamentally unaltered.

Increasing profits and reducing risks in crop production using participatory systems simulation approaches

The development of cropping systems simulation capabilities world-wide combined with easy access to powerful computing has resulted in a plethora of agricultural models and consequently, model applications. Nonetheless, the scientific credibility of such applications and their relevance to farming practice is still being questioned. Our objective in this paper is to highlight some of the model applications from which benefits for farmers were or could be obtained via changed agricultural practice or policy. Changed on-farm practice due to the direct contribution of modelling, while keenly sought after, may in some cases be less achievable than a contribution via agricultural policies. This paper is intended to give some guidance for future model applications. It is not a comprehensive review of model applications, nor is it intended to discuss modelling in the context of social science or extension policy. Rather, we take snapshots around the globe to 'take stock' and to demonstrate that well-defined financial and environmental benefits can be obtained on-farm from the use of models. We highlight the importance of 'relevance' and hence the importance of true partnerships between all stakeholders (farmer, scientists, advisers) for the successful development and adoption of simulation approaches. Specifically, we address some key points that are essential for successful model applications such as: (1) issues to be addressed must be neither trivial nor obvious; (2) a modelling approach must reduce complexity rather than proliferate choices in order to aid the decision-making process (3) the cropping systems must be sufficiently flexible to allow management interventions based on insights gained from models. The pro and cons of normative approaches (e.g. decision support software that can reach a wide audience quickly but are often poorly contextualized for any individual client) versus model applications within the context of an individual client's situation will also be discussed. We suggest that a tandem approach is necessary whereby the latter is used in the early stages of model application for confidence building amongst client groups. This paper focuses on five specific regions that differ fundamentally in terms of environment and socio-economic structure and hence in their requirements for successful model applications. Specifically, we will give examples from Australia and South America (high climatic variability, large areas, low input, technologically advanced); Africa (high climatic variability, small areas, low input, subsistence agriculture); India (high climatic variability, small areas, medium level inputs, technologically progressing; and Europe (relatively low climatic variability, small areas, high input, technologically advanced). The contrast between Australia and Europe will further demonstrate how successful model applications are strongly influenced by the policy framework within which producers operate. We suggest that this might eventually lead to better adoption of fully integrated systems approaches and result in the development of resilient farming systems that are in tune with current climatic conditions and are adaptable to biophysical and socioeconomic variability and change. (C) 2001 Elsevier Science Ltd. All rights reserved.

A model of factors affecting an information system's change in state

Management are keen to maximize the life span of an information system because of the high cost, organizational disruption, and risk of failure associated with the re-development or replacement of an information system. This research investigates the effects that various factors have on an information system's life span by understanding how the factors affect an information system's stability. The research builds on a previously developed two-stage model of information system change whereby an information system is either in a stable state of evolution in which the information system's functionality is evolving, or in a state of revolution, in which the information system is being replaced because it is not providing the functionality expected by its users. A case study surveyed a number of systems within one organization. The aim was to test whether a relationship existed between the base value of the volatility index (a measure of the stability of an information system) and certain system characteristics. Data relating to some 3000 user change requests covering 40 systems over a 10-year period were obtained. The following factors were hypothesized to have significant associations with the base value of the volatility index: language level (generation of language of construction), system size, system age, and the timing of changes applied to a system. Significant associations were found in the hypothesized directions except that the timing of user changes was not associated with any change in the value of the volatility index. Copyright (C) 2002 John Wiley Sons, Ltd.

Crisis, change, and institutions in forest management: the Wet Tropics of northeastern Australia

This paper tests the four-phase heuristic model of change in resource management regimes developed by Gunderson et al. (1995. In: Barriers and Bridges to the Renewal of Ecosystems and Institutions. Columbia University Press, New York, pp. 489-533) by applying it to a case analysis of rainforest management in northeastern Australia. The model suggests that resource management regimes change in four phases: (i) crisis caused by external factors, (ii) a search for alternative management solutions, (iii) creation of a new management regime, and (iv) bureaucratic implementation of the new arrangements. The history of human use arid management of the tropical forests of this region is described and applied to this model. The ensuing analysis demonstrates that: (i) resource management tends to be characterized by a series of distinct eras; (ii) changes to management regimes are precipitated by crisis; and (iii) change is externally generated. The paper concludes by arguing that this theoretical perspective oil institutional change in resource management systems has wider utility. (C) 2002 Elsevier Science Ltd. All rights reserved.

Ecological responses to recent climate change

There is now ample evidence of the ecological impacts of recent climate change, from polar terrestrial to tropical marine environments. The responses of both flora and fauna span an array of ecosystems and organizational hierarchies, from the species to the community levels. Despite continued uncertainty as to community and ecosystem trajectories under global change, our review exposes a coherent pattern of ecological change across systems. Although we are only at an early stage in the projected trends of global warming, ecological responses to recent climate change are already clearly visible.

Phenomenological turbulence and innovation in knowledge systems

Most considerations of knowledge management focus on corporations and, until recently, considered knowledge to be objective, stable, and asocial. In this paper we wish to move the focus away from corporations, and examine knowledge and national innovation systems. We argue that the knowledge systems in which innovation takes place are phenomenologically turbulent, a state not made explicit in the change, innovation and socio-economic studies of knowledge literature, and that this omission poses a serious limitation to the successful analysis of innovation and knowledge systems. To address this lack we suggest that three evolutionary processes must be considered: self-referencing, self-transformation and self-organisation. These processes, acting simultaneously, enable system cohesion, radical innovation and adaptation. More specifically, we argue that in knowledge-based economies the high levels of phenomenological turbulence drives these processes. Finally, we spell out important policy principles that derive from these processes.