Changing the rules in use? An examination of social enterprise in local governance

As multi-stakeholder entities that explicitly inhabit both social and economic domains, social enterprises pose new challenges and possibilities for local governance. In this paper, we draw on new institutional theory to examine the ways in which locally-focused social enterprises disrupt path dependencies and rules in use within local government. Rather than examining the more commonly asked question of the influence of the state on social enterprise, our purpose here is to examine the impacts of social enterprise on governmental institutions at the local level. Our discussion is based on a mixed-methods study, including an online survey of 66 local government staff, document analysis, and in-depth interviews with 24 social enterprise practitioners and local government actors working to support social enterprise development in Victoria, Australia. We find that, in some instances, the hybrid nature of social enterprise facilitates ‘joining up’ between different functional areas of local government. Beyond organisational relationships, social enterprise also influences local governance through the reinterpretation and regeneration of institutionalised public spaces.

Macroentrepreneurship : an expanded contact for entrepreneurship

The purpose if this paper is to show how entrepreneurial practices can be applied at macro level by industry and government bodies, particularly to identify opportunity areas in target industries and thereby promote new business ventures that best serve the economy and society. A new macro context is argued for entrepreneurial activity based on marketing and entrepreneurship principles, and their specialization areas or social and societal marketing, macromarketing and social entrepreneurship. An example of government and industry involvement in industry opportunity identification is outlines to demonstrate macro level entrepreneurial activity, showing how, in the same way that macromarketing seeks to address the bigger issues and the links between marketing systems and society, so too can entrepreneurship use this perspective to achieve its aims and contribute more effectively to the betterment of society. This paper makes and original contribution by demonstrating a new, expanded context for entrepreneurship's scholarly domain and its practice, showing how its key concepts can be effectively applied at industry level to provide a catalyst for development.

A model of teacher professional development based on the principles of lesson study

The researcher’s professional role as an Education Officer was the impetus for this study. Designing and implementing professional development activities is a significant component of the researcher’s position description and as a result of reflection and feedback from participants and colleagues, the creation of a more effective model of professional development became the focus for this study. Few studies have examined all three links between the purposes of professional development that is, increasing teacher knowledge, improving teacher practice, and improving student outcomes. This study is significant in that it investigates the nature of the growth of teachers who participated in a model of professional development which was based upon the principles of Lesson Study. The research provides qualitative and empirical data to establish some links between teacher knowledge, teacher practice, and student learning outcomes. Teacher knowledge in this study refers to mathematics content knowledge as well as pedagogical-content knowledge. The outcomes for students include achievement outcomes, attitudinal outcomes, and behavioural outcomes. As the study was conducted at one school-site, existence proof research was the focus of the methodology and data collection. Developing over the 2007 school year, with five teacher-participants and approximately 160 students from Year Levels 6 to 9, the Lesson Study-principled model of professional development provided the teacher-participants with on-site, on-going, and reflective learning based on their classroom environment. The focus area for the professional development was strategising the engagement with and solution of worded mathematics problems. A design experiment was used to develop the professional development as an intervention of prevailing teacher practice for which data were collected prior to and after the period of intervention. A model of teacher change was developed as an underpinning framework for the development of the study, and was useful in making decisions about data collection and analyses. Data sources consisted of questionnaires, pre-tests and post-tests, interviews, and researcher observations and field notes. The data clearly showed that: content knowledge and pedagogical-content knowledge were increased among the teacher-participants; teacher practice changed in a positive manner; and that a majority of students demonstrated improved learning outcomes. The positive changes to teacher practice are described in this study as the demonstrated use of mixed pedagogical practices rather than a polarisation to either traditional pedagogical practices or contemporary pedagogical practices. The improvement in student learning outcomes was most significant as improved achievement outcomes as indicated by the comparison of pre-test and post-test scores. The effectiveness of the Lesson Study-principled model of professional development used in this study was evaluated using Guskey’s (2005) Five Levels of Professional Development Evaluation.

Delay distribution based robust H∞ control of networked control systems with uncertainties

Network induced delay in networked control systems (NCS) is inherently non-uniformly distributed and behaves with multifractal nature. However, such network characteristics have not been well considered in NCS analysis and synthesis. Making use of the information of the statistical distribution of NCS network induced delay, a delay distribution based stochastic model is adopted to link Quality-of-Control and network Quality-of-Service for NCS with uncertainties. From this model together with a tighter bounding technology for cross terms, H∞ NCS analysis is carried out with significantly improved stability results. Furthermore, a memoryless H∞ controller is designed to stabilize the NCS and to achieve the prescribed disturbance attenuation level. Numerical examples are given to demonstrate the effectiveness of the proposed method.

Load–frequency control : a GA-based multi-agent reinforcement learning

The load–frequency control (LFC) problem has been one of the major subjects in a power system. In practice, LFC systems use proportional–integral (PI) controllers. However since these controllers are designed using a linear model, the non-linearities of the system are not accounted for and they are incapable of gaining good dynamical performance for a wide range of operating conditions in a multi-area power system. A strategy for solving this problem because of the distributed nature of a multi-area power system is presented by using a multi-agent reinforcement learning (MARL) approach. It consists of two agents in each power area; the estimator agent provides the area control error (ACE) signal based on the frequency bias estimation and the controller agent uses reinforcement learning to control the power system in which genetic algorithm optimisation is used to tune its parameters. This method does not depend on any knowledge of the system and it admits considerable flexibility in defining the control objective. Also, by finding the ACE signal based on the frequency bias estimation the LFC performance is improved and by using the MARL parallel, computation is realised, leading to a high degree of scalability. Here, to illustrate the accuracy of the proposed approach, a three-area power system example is given with two scenarios.

How can entrepreneurial musicians use electronic social networks to diffuse their music

Principal Topic: ''In less than ten years music labels will not exist anymore.'' Michael Smelli, former Global COO Sony/BMG MCA/QUT IMP Business Lab Digital Music Think Thanks 9 May 2009, Brisbane Big music labels such as EMI, Sony BMG and UMG have been responsible for promoting and producing a myriad of stars in the music industry over the last decades. However, the industry structure is under enormous threat with the emergence of a new innovative era of digital music. Recent years have seen a dramatic shift in industry power with the emergence of Napster and other file sharing sites, iTunes and other online stores, iPod and the MP3 revolution. Myspace.com and other social networking sites are connecting entrepreneurial artists with fans and creating online music communities independent of music labels. In 2008 the digital music business internationally grew by around 25% to 3.7 Billion US-Dollar. Digital platforms now account for around 20% of recorded music sales, up from 15 % in 2007 (IFPI Digital music report 2009). CD sales have fallen by 40% since their peak levels. Global digital music sales totalled an estimated US$ 3 Billion in 2007, an increase of 40% on 2006 figures. Digital sales account for an estimated 15% of global market, up from 11% in 2006 and zero in 2003. The music industry is more advanced in terms of digital revenues than any other creative or entertainment industry (except games). Its digital share is more than twice that of newspapers (7%), films (35) or books (2%). All these shifts present new possibilities for music entrepreneurs to act entrepreneurially and promote their music independently of the major music labels. Diffusion of innovations has a long tradition in both sociology (e.g. Rogers 1962, 2003) and marketing (Bass 1969, Mahajan et al., 1990). The context of the current project is theoretically interesting in two respects. First, the role of online social networks replaces traditional face-to-face word of mouth communications. Second, as music is a hedonistic product, this strongly influences the nature of interpersonal communications and their diffusion patterns. Both of these have received very little attention in the diffusion literature to date, and no studies have investigated the influence of both simultaneously. This research project is concerned with the role of social networks in this new music industry landscape, and how this may be leveraged by musicians willing to act entrepreneurially. Our key research question we intend to address is: How do online social network communities impact the nature, pattern and speed that music diffuses? Methodology/Key Propositions : We expect the nature/ character of diffusion of popular, generic music genres to be different from specialized, niche music. To date, only Moe & Fader (2002) and Lee et al. (2003) investigated diffusion patterns of music and these focus on forecast weekly sales of music CDs based on the advance purchase orders before the launch, rather than taking a detailed look at diffusion patterns. Consequently, our first research questions are concerned with understanding the nature of online communications within the context of diffusion of music and artists. Hence, we have the following research questions: RQ1: What is the nature of fan-to-fan ''word of mouth'' online communications for music? Do these vary by type of artist and genre of music? RQ2: What is the nature of artist-to-fan online communications for music? Do these vary by type of artist and genre of music? What types of communication are effective? Two outcomes from research social network theory are particularly relevant to understanding how music might diffuse through social networks. Weak tie theory (Granovetter, 1973), argues that casual or infrequent contacts within a social network (or weak ties) act as a link to unique information which is not normally contained within an entrepreneurs inner circle (or strong tie) social network. A related argument, structural hole theory (Burt, 1992), posits that it is the absence of direct links (or structural holes) between members of a social network which offers similar informational benefits. Although these two theories argue for the information benefits of casual linkages, and diversity within a social network, others acknowledge that a balanced network which consists of a mix of strong ties, weak ties is perhaps more important overall (Uzzi, 1996). It is anticipated that the network structure of the fan base for different types of artists and genres of music will vary considerably. This leads to our third research question: RQ3: How does the network structure of online social network communities impact the pattern and speed that music diffuses? The current paper is best described as theory elaboration. It will report the first exploratory phase designed to develop and elaborate relevant theory (the second phase will be a quantitative study of network structure and diffusion). We intend to develop specific research propositions or hypotheses from the above research questions. To do so we will conduct three focus group discussions of independent musicians and three focus group discussions of fans active in online music communication on social network sites. We will also conduct five case studies of bands that have successfully built fan bases through social networking sites (e.g. myspace.com, facebook.com). The idea is to identify which communication channels they employ and the characteristics of the fan interactions for different genres of music. We intend to conduct interviews with each of the artists and analyse their online interaction with their fans. Results and Implications : At the current stage, we have just begun to conduct focus group discussions. An analysis of the themes from these focus groups will enable us to further refine our research questions into testable hypotheses. Ultimately, our research will provide a better understanding of how social networks promote the diffusion of music, and how this varies for different genres of music. Hence, some music entrepreneurs will be able to promote their music more effectively. The results may be further generalised to other industries where online peer-to-peer communication is common, such as other forms of entertainment and consumer technologies.

Characteristics of sustainable entrepreneurship : some early explorations from the CAUSEE study

Principal Topic: For forward thinking companies, the environment may represent the ''biggest opportunity for enterprise and invention the industrial world has ever seen'' (Cairncross 1990). Increasing awareness of environmental and sustainability issues through media including the promotion of Al Gore's ''An Inconvenient Truth'' has seen increased awareness of environmental and sustainability issues and increased demand for business processes that reduce detrimental environmental impacts of global development (Dean & McMullen 2007). The increased demand for more environmentally sensitive products and services represents an opportunity for the development of ventures that seek to satisfy this demand through entrepreneurial action. As a consequence, increasing recent market developments in renewable energy, carbon emissions, fuel cells, green building, and other sectors suggest an increasing importance of opportunities for environmental entrepreneurship (Dean and McMullen 2007) and increasingly important area of business activity (Schaper 2005). In the last decade in particular, big business has sought to develop a more ''sustainability/ green friendly'' orientation as a response to public pressure and increased government legislation and policy to improve environmental performance (Cohen and Winn 2007). Whilst much of the literature and media is littered with examples of sustainability practices of large firms, nascent and young sustainability firms have only recently begun generating strong research and policy interest (Shepherd, Kuskova and Patzelt 2009): not only for their potential to generate above average financial performance and returns owing to a greater popularity and demand towards sustainability products and services offerings, but also for their intent to lessen environmental impacts, and to provide a more accurate reflection of the ''true cost'' of market offerings taking into account carbon and environmental impacts. More specifically, researchers have suggested that although the previous focus has been on large firms and their impact on the environment, the estimated collective impact of entries and exits of nascent and young firms in development is substantial and could outweigh the combined environmental impact of large companies (Hillary, 2000). Therefore, it may be argued that greater attention should be paid to nascent and young firms and researching sustainability practices, for both their impact in reducing environmental impacts and potential higher financial performance. Whilst acknowledging this research only uses the first wave of a four year longitudinal study of nascent and young firms, it can still begin to provide initial analysis on which to continue further research. The aim of this paper therefore is to provide an overview of the emerging literature in sustainable entrepreneurship and to present some selected preliminary results from the first wave of the data collection, with comparison, where appropriate, of sustainable and firms that do not fulfil this criteria. ''One of the key challenges in evaluating sustainability entrepreneurship is the lack of agreement in how it is defined'' (Schaper, 2005: 10). Some evaluate sustainable entrepreneurs simply as one category of entrepreneurs with little difference between them and traditional entrepreneurs (Dees, 1998). Other research recognises values-based sustainable enterprises requiring a unique perspective (Parrish, 2005). Some see the environmental or sustainable entrepreneurship is a subset of social entrepreneurship (Cohen & Winn, 2007; Dean & McMullen, 2007) whilst others see it as a separate, distinct theory (Archer 2009). Following one of the first definitions of sustainability developed by the Brundtland Commission (1987) we define sustainable entrepreneurship as firms which ''seek to meet the needs and aspirations of the present without compromising the ability to meet those of the future''. ---------- Methodology/Key Propositions: In this exploratory paper we investigate sustainable entrepreneurship using Cohen et al.'s (2008) framework to identify strategies of nascent and young entrepreneurial firms. We use data from The Comprehensive Australian Study of Entrepreneurial Emergence (CAUSEE). This study shares the general empirical approach with PSED studies in the US (Reynolds et al 1994; Reynolds & Curtin 2008). The overall study uses samples of 727 nascent (not yet operational) firms and another 674 young firms, the latter being in an operational stage but less than four years old. To generate the sub sample of sustainability firms, we used content analysis techniques on firm titles, descriptions and product descriptions provided by respondents. Two independent coders used a predefined codebook developed from our review of the sustainability entrepreneurship literature (Cohen et al. 2009) to evaluate the content based on terms such as ''sustainable'' ''eco-friendly'' ''renewable energy'' ''environment'' amongst others. The inter-rater reliability was checked and the Kappa's co-efficient was found to be within the acceptable range (0.746). 85 firms fulfilled the criteria given for inclusion in the sustainability cohort. ---------- Results and Implications: The results for this paper are based on Wave one of the CAUSEE survey which has been completed and the data is available for analysis. It is expected that the findings will assist in beginning to develop an understanding of nascent and young firms that are driven to contribute to a society which is sustainable, not just from an economic perspective (Cohen et al 2008), but from an environmental and social perspective as well. The CAUSEE study provides an opportunity to compare the characteristics of sustainability entrepreneurs with entrepreneurial firms without a stated environmental purpose, which constitutes the majority of the new firms created each year, using a large scale novel longitudinal dataset. The results have implications for Government in the design of better conditions for the creation of new business, firms who assist sustainability in developing better advice programs in line with a better understanding of their needs and requirements, individuals who may be considering becoming entrepreneurs in high potential arenas and existing entrepreneurs make better decisions.

Evidence-based practice

Introduction This chapter traces the history of evidence-based practice from its roots in evidence-based medicine to contemporary thinking about the usefulness of such an approach to practice. It defines evidence-based practice and differentiates it from terms such as evidence-based medicine, evidence-based policy and evidence-based healthcare. As evidence-based practice is concerned with identifying ‘good evidence’, this chapter will first describe the nature and production of knowledge, as it is important to understand the subjective nature of knowledge and the research process. The chapter considers the necessary skills for evidence-based practice, and discusses the processes of attaining the necessary evidence and its limitations. We examine the barriers and facilitators to identifying and implementing ‘best practice’ and when evidence-based practice is appropriate to use. The chapter concludes with a discussion about the limitations of evidence-based practice and the potential use of other sources of information to guide practice.

Cluster-based Intrusion Detection (CBID) architecture for mobile ad hoc networks

The ad hoc networks are vulnerable to attacks due to distributed nature and lack of infrastructure. Intrusion detection systems (IDS) provide audit and monitoring capabilities that offer the local security to a node and help to perceive the specific trust level of other nodes. The clustering protocols can be taken as an additional advantage in these processing constrained networks to collaboratively detect intrusions with less power usage and minimal overhead. Existing clustering protocols are not suitable for intrusion detection purposes, because they are linked with the routes. The route establishment and route renewal affects the clusters and as a consequence, the processing and traffic overhead increases due to instability of clusters. The ad hoc networks are battery and power constraint, and therefore a trusted monitoring node should be available to detect and respond against intrusions in time. This can be achieved only if the clusters are stable for a long period of time. If the clusters are regularly changed due to routes, the intrusion detection will not prove to be effective. Therefore, a generalized clustering algorithm has been proposed that can run on top of any routing protocol and can monitor the intrusions constantly irrespective of the routes. The proposed simplified clustering scheme has been used to detect intrusions, resulting in high detection rates and low processing and memory overhead irrespective of the routes, connections, traffic types and mobility of nodes in the network. Clustering is also useful to detect intrusions collaboratively since an individual node can neither detect the malicious node alone nor it can take action against that node on its own.

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

An ecology of centre-based child care

The studies in the thesis were derived from a program of research focused on centre-based child care in Australia. The studies constituted an ecological analysis as they examined proximal and distal factors which have the potential to affect children's developmental opportunities (Bronfenbrenner, 1979). The project was conducted in thirty-two child care centres located in south-east Queensland. Participants in the research included staff members at the centres, families using the centres and their children. The first study described the personal and professional characteristics of one hundred and forty-four child care workers, as well as their job satisfaction and job commitment. Factors impinging on the stability of care afforded to children were examined, specifically child care workers' intentions to leave their current position and actual staff turnover at a twelve month follow-up. This is an ecosystem analysis (Bronfenbrenner & Crouter, 1983), as it examined the world of work for carers; a setting not directly involving the developing child, but which has implications for children's experiences. Staff job satisfaction was focused on working with children and other adults, including parents and colleagues. Involvement with children was reported as being the most rewarding aspect of the work. This intrinsic satisfaction was enough to sustain caregivers' efforts to maintain their employment in child care programs. It was found that, while improving working conditions may help to reduce turnover, it is likely that moderate turnover rates will remain as child care staff work in relatively small centres and they leave in order to improve career prospects. Departure from a child care job appeared to be as much about improving career opportunities or changing personal circumstances, as it was about poor wages and working conditions. In the second study, factors that influence maternal satisfaction with child care arrangements were examined. The focus included examination of the nature and qualities of parental interaction with staff. This was a mesosystem analysis (Bronfenbrenner & Crouter, 1983), as it considered the links between family and child care settings. Two hundred and twenty-two questionnaires were returned from mothers whose children were enrolled in the participating centres. It was found that maternal satisfaction with child care encompassed the domains of child-centred and parent-centred satisfaction. The nature and range of responses in the quantitative and qualitative data indicated that these parents were genuinely satisfied with their children's care. In the prediction of maternal satisfaction with child care, single parents, mothers with high role satisfaction, and mothers who were satisfied with the frequency of staff contact and degree of supportive communication had higher levels of satisfaction with their child care arrangements. The third study described the structural and process variations within child care programs and examined program differences for compliance with regulations and differences by profit status of the centre, as a microsystem analysis (Bronfenbrenner, 1979). Observations were made in eighty-three programs which served children from two to five years. The results of the study affirmed beliefs that nonprofit centres are superior in the quality of care provided, although this was not to a level which meant that the care in for-profit centres was inadequate. Regulation of structural features of child care programs, per se, did not guarantee higher quality child care as measured by global or process indicators. The final study represented an integration of a range of influences in child care and family settings which may impact on development. Features of child care programs which predict children's social and cognitive development, while taking into account child and family characteristics, were identified. Results were consistent with other research findings which show that child and family characteristics and child care quality predict children's development. Child care quality was more important to the prediction of social development, while family factors appeared to be more predictive of cognitive/language development. An influential variable predictive of development was the period of time which the child had been in the centre. This highlighted the importance of the stability of child care arrangements. Child care quality features which had most influence were global ratings of the qualities of the program environment. However, results need to be interpreted cautiously as the explained variance in the predictive models developed was low. The results of these studies are discussed in terms of the implications for practice and future research. Considerations for an expanded view of ecological approaches to child care research are outlined. Issues discussed include the need to generate child care research which is relevant to social policy development, the implications of market driven policies for child care services, professionalism and professionalisation of child care work, and the need to reconceptualise child care research when the goal is to develop greater theoretical understanding about child care environments and developmental processes.

Inquiry-based science in a primary classroom : professional development impacting practice

The critical factor in determining students' interest and motivation to learn science is the quality of the teaching. However, science typically receives very little time in primary classrooms, with teachers often lacking the confidence to engage in inquiry-based learning because they do not have a sound understanding of science or its associated pedagogical approaches. Developing teacher knowledge in this area is a major challenge. Addressing these concerns with didactic "stand and deliver" modes of Professional Development (PD) has been shown to have little relevance or effectiveness, yet is still the predominant approach used by schools and education authorities. In response to that issue, the constructivist-inspired Primary Connections professional learning program applies contemporary theory relating to the characteristics of effective primary science teaching, the changes required for teachers to use those pedagogies, and professional learning strategies that facilitate such change. This study investigated the nature of teachers' engagement with the various elements of the program. Summative assessments of such PD programs have been undertaken previously, however there was an identified need for a detailed view of the changes in teachers' beliefs and practices during the intervention. This research was a case study of a Primary Connections implementation. PD workshops were presented to a primary school staff, then two teachers were observed as they worked in tandem to implement related curriculum units with their Year 4/5 classes over a six-month period. Data including interviews, classroom observations and written artefacts were analysed to identify common themes and develop a set of assertions related to how teachers changed their beliefs and practices for teaching science. When teachers implement Primary Connections, their students "are more frequently curious in science and more frequently learn interesting things in science" (Hackling & Prain, 2008). This study has found that teachers who observe such changes in their students consequently change their beliefs and practices about teaching science. They enhance science learning by promoting student autonomy through open-ended inquiries, and they and their students enhance their scientific literacy by jointly constructing investigations and explaining their findings. The findings have implications for teachers and for designers of PD programs. Assertions related to teaching science within a pedagogical framework consistent with the Primary Connections model are that: (1) promoting student autonomy enhances science learning; (2) student autonomy presents perceived threats to teachers but these are counteracted by enhanced student engagement and learning; (3) the structured constructivism of Primary Connections resources provides appropriate scaffolding for teachers and students to transition from didactic to inquiry-based learning modes; and (4) authentic science investigations promote understanding of scientific literacy and the "nature of science". The key messages for designers of PD programs are that: (1) effective programs model the pedagogies being promoted; (2) teachers benefit from taking the role of student and engaging in the proposed learning experiences; (3) related curriculum resources foster long-term engagement with new concepts and strategies; (4) change in beliefs and practices occurs after teachers implement the program or strategy and see positive outcomes in their students; and (5) implementing this study's PD model is efficient in terms of resources. Identified topics for further investigation relate to the role of assessment in providing evidence to support change in teachers' beliefs and practices, and of teacher reflection in making such change more sustainable.

On the nature of over-dispersion in motor vehicle crash prediction models

Statistical modeling of traffic crashes has been of interest to researchers for decades. Over the most recent decade many crash models have accounted for extra-variation in crash counts—variation over and above that accounted for by the Poisson density. The extra-variation – or dispersion – is theorized to capture unaccounted for variation in crashes across sites. The majority of studies have assumed fixed dispersion parameters in over-dispersed crash models—tantamount to assuming that unaccounted for variation is proportional to the expected crash count. Miaou and Lord [Miaou, S.P., Lord, D., 2003. Modeling traffic crash-flow relationships for intersections: dispersion parameter, functional form, and Bayes versus empirical Bayes methods. Transport. Res. Rec. 1840, 31–40] challenged the fixed dispersion parameter assumption, and examined various dispersion parameter relationships when modeling urban signalized intersection accidents in Toronto. They suggested that further work is needed to determine the appropriateness of the findings for rural as well as other intersection types, to corroborate their findings, and to explore alternative dispersion functions. This study builds upon the work of Miaou and Lord, with exploration of additional dispersion functions, the use of an independent data set, and presents an opportunity to corroborate their findings. Data from Georgia are used in this study. A Bayesian modeling approach with non-informative priors is adopted, using sampling-based estimation via Markov Chain Monte Carlo (MCMC) and the Gibbs sampler. A total of eight model specifications were developed; four of them employed traffic flows as explanatory factors in mean structure while the remainder of them included geometric factors in addition to major and minor road traffic flows. The models were compared and contrasted using the significance of coefficients, standard deviance, chi-square goodness-of-fit, and deviance information criteria (DIC) statistics. The findings indicate that the modeling of the dispersion parameter, which essentially explains the extra-variance structure, depends greatly on how the mean structure is modeled. In the presence of a well-defined mean function, the extra-variance structure generally becomes insignificant, i.e. the variance structure is a simple function of the mean. It appears that extra-variation is a function of covariates when the mean structure (expected crash count) is poorly specified and suffers from omitted variables. In contrast, when sufficient explanatory variables are used to model the mean (expected crash count), extra-Poisson variation is not significantly related to these variables. If these results are generalizable, they suggest that model specification may be improved by testing extra-variation functions for significance. They also suggest that known influences of expected crash counts are likely to be different than factors that might help to explain unaccounted for variation in crashes across sites

Harnessing ICT-based tool for improving the collaborative health planning debate : the case of Logan-Beaudesert, Australia

The field of collaborative health planning faces significant challenges posed by the lack of effective information, systems and a framework to organise that information. Such a framework is critical in order to make accessible and informed decisions for planning healthy cities. The challenges have been exaggerated by the rise of the healthy cities movement, as a result of which, there have been more frequent calls for localised, collaborative and evidence-based decision-making. Some studies suggest that the use of ICT-based tools in health planning may lead to: increased collaboration between stakeholder sand the community; improve the accuracy and quality of the decision making process; and, improve the availability of data and information for health decision-makers as well as health service planners. Research has justified the use of decision support systems (DSS) in planning for healthy cities as these systems have been found to improve the planning process. DSS are information communication technology (ICT) tools including geographic information systems (GIS) that provide the mechanisms to help decision-makers and related stake holders assess complex problems and solve these in a meaningful way. Consequently, it is now more possible than ever before to make use of ICT-based tools in health planning. However, knowledge about the nature and use of DSS within collaborative health planning is relatively limited. In particular, little research has been conducted in terms of evaluating the impact of adopting these tools upon stakeholders, policy-makers and decision-makers within the health planning field. This paper presents an integrated method that has been developed to facilitate an informed decision-making process to assist in the health planning process. Specifically, the paper describes the participatory process that has been adopted to develop an online GIS-based DSS for health planners. The literature states that the overall aim of DSS is to improve the efficiency of the decisions made by stakeholders, optimising their overall performance and minimizing judgmental biases. For this reason, the paper examines the effectiveness and impact of an innovative online GIS-based DSS on health planners. The case study of the online DSS is set within a unique settings-based initiative designed to plan for and improve the health capacity of Logan-Beaudesert area, Australia. This unique setting-based initiative is named the Logan-Beaudesert Health Coalition (LBHC).The paper outlines the impact occurred by implementing the ICT-based DSS. In conclusion, the paper emphasizes upon the need for the proposed tool for enhancing health planning.

Fashion as consumer entrepreneurship : emergent risk culture, social network markets, and the launch of Vogue in China

China has a reputation as an economy based on utility: the large-scale manufacture of low-priced goods. But useful values like functionality, fitness for purpose and efficiency are only part of the story. More important are what Veblen called ‘honorific’ values, arguably the driving force of development, change and value in any economy. To understand the Chinese economy therefore, it is not sufficient to point to its utilitarian aspect. Honorific status-competition is a more fundamental driver than utilitarian cost-competition. We argue that ‘social network markets’ are the expression of these honorific values, relationships and connections that structure and coordinate individual choices. This paper explores how such markets are developing in China in the area of fashion and fashion media. These, we argue, are an expression of ‘risk culture’ for high-end entrepreneurial consumers and producers alike, providing a stimulus to dynamic innovation in the arena of personal taste and comportment, as part of an international cultural system based on constant change. We examine the launch of Vogue China in 2005, and China’s reception as a fashion player among the international editions of Vogue, as an expression of a ‘decisive moment’ in the integration of China into an international social network market based on honorific values.