Gifted young adolescents : voices of self

Despite the challenges that giftedness can add to self-formation during early adolescence, gifted young adolescents seldom are asked about their lives outside of counselling and educational contexts. The study considers the complexities that face gifted young adolescents in the process of self-discovery and self-representation, thereby building a case for seeking their own viewpoints. A guiding assumption for the study was that gifted young adolescents may respond positively to the opportunity to share their own perspectives and their own versions of “who they are”. The theoretical underpinnings for this study drew from Dialogical Self Theory. The study resides within an interactive view of self as a dynamic construction rather than a static state, where “who we are” is formed in everyday exchanges with self and others. Self-making as a process among gifted young adolescents is presented as an interactive network of “I” voices interpreted to reflect internal and external dialogue. In this way, self is understood within dialogical concepts of voices as multiple expressions. The study invited twelve gifted young adolescents to write freely about themselves over a six month period in an email journal project. Participants were recruited online and by word-of-mouth and they were able to negotiate their own levels of involvement. Access to the lives of individual young adolescents was sought in an out-of-school setting using narrative methods of personal writing in the form of journals sent as emails to the researcher. The role of the researcher was to act as a supportive listener who responded to participant-led emails and thereby facilitated the process of authoring that occurred across the data-gathering phase. The listening process involved responses that were affirming and designed to build trust. Data in the form of email texts were analysed using a close listening method that uncovered patterns of voices that were explicitly or subtly expressed by participants. The interpretation of voices highlighted the tensions and contradictions involved in the process of participants forming a “self” that emerged as multiple “I” voices. There were three key findings of the study. First, the gifted young adolescent participants each constructed a self around four key voices of Author, Achiever, Resistor/Co-operator and Self-Innovator. These voices were dialogical selfconstructions that showed multiplicity as a normal way of being. Second, the selfmaking processes of the gifted young adolescent participants were guided by a hierarchy of voices that were directed through self-awareness. Third, authoring in association with a responsive adult listener emerged as a dialogic space for promoting self-awareness and a language of self-expression among gifted young adolescents. The findings of the study contribute to knowledge about gifted young adolescents by presenting their own versions of “who” they are, perspectives that might differ from mainstream perceptions. Participants were shown to have highly diverse, complex and individual expressions that have implications for how well they are understood and supported by others. The use of email journals helped to create a synergy for self-disclosure and a safe space for self-expression where participants’ abilities to be themselves were encouraged. Increased self-awareness and selfknowledge among gifted young adolescents is vital to their self-formation and their management of self and others’ expectations. This study makes an original contribution to the field of self-study by highlighting the processes and complexities of young adolescents’ self-constructions. Through the innovative use of narrative methods and an inter-disciplinary approach, the voices of gifted young adolescents were privileged. At a practical level, the study can inform educators, policy-makers, parents and all those who seek to contribute to the well-being of gifted young adolescents.

A sociolinguistic approach to applied epistemology : examining technocratic values in global 'Knowledge' policy

This special issue presents an excellent opportunity to study applied epistemology in public policy. This is an important task because the arena of public policy is the social domain in which macro conditions for ‘knowledge work’ and ‘knowledge industries’ are defined and created. We argue that knowledge-related public policy has become overly concerned with creating the politico-economic parameters for the commodification of knowledge. Our policy scope is broader than that of Fuller (1988), who emphasizes the need for a social epistemology of science policy. We extend our focus to a range of policy documents that include communications, science, education and innovation policy (collectively called knowledge-related public policy in acknowledgement of the fact that there is no defined policy silo called ‘knowledge policy’), all of which are central to policy concerned with the ‘knowledge economy’ (Rooney and Mandeville, 1998). However, what we will show here is that, as Fuller (1995) argues, ‘knowledge societies’ are not industrial societies permeated by knowledge, but that knowledge societies are permeated by industrial values. Our analysis is informed by an autopoietic perspective. Methodologically, we approach it from a sociolinguistic position that acknowledges the centrality of language to human societies (Graham, 2000). Here, what we call ‘knowledge’ is posited as a social and cognitive relationship between persons operating on and within multiple social and non-social (or, crudely, ‘physical’) environments. Moreover, knowing, we argue, is a sociolinguistically constituted process. Further, we emphasize that the evaluative dimension of language is most salient for analysing contemporary policy discourses about the commercialization of epistemology (Graham, in press). Finally, we provide a discourse analysis of a sample of exemplary texts drawn from a 1.3 million-word corpus of knowledge-related public policy documents that we compiled from local, state, national and supranational legislatures throughout the industrialized world. Our analysis exemplifies a propensity in policy for resorting to technocratic, instrumentalist and anti-intellectual views of knowledge in policy. We argue that what underpins these patterns is a commodity-based conceptualization of knowledge, which is underpinned by an axiology of narrowly economic imperatives at odds with the very nature of knowledge. The commodity view of knowledge, therefore, is flawed in its ignorance of the social systemic properties of knowing’.

Improving the performance of facial expression recognition using dynamic, subtle and regional features

Human facial expression is a complex process characterized of dynamic, subtle and regional emotional features. State-of-the-art approaches on facial expression recognition (FER) have not fully utilized this kind of features to improve the recognition performance. This paper proposes an approach to overcome this limitation using patch-based ‘salient’ Gabor features. A set of 3D patches are extracted to represent the subtle and regional features, and then inputted into patch matching operations for capturing the dynamic features. Experimental results show a significant performance improvement of the proposed approach due to the use of the dynamic features. Performance comparison with pervious work also confirms that the proposed approach achieves the highest CRR reported to date on the JAFFE database and a top-level performance on the Cohn-Kanade (CK) database.

Redefining excellence : a strategic policy framework for community engagement and higher education

This report provides a current overview and analysis of the role of universities in local community development in the State of Victoria. Drawing on successful programs of community engagement in Victoria, Australia, Europe, Africa, and North America, the report proposes policy strategies for fostering community development for Victorian Higher Education through effective community engagement programs.

Dynamic response of distributed generators in a hybrid microgrid

A microgrid may be supplied from inertial (rotating type) and non-inertial (converter-interfaced) distributed generators (DGs). However the dynamic response of these two types of DGs is different. Inertial DGs have a slower response due to their governor characteristics while non inertial DGs have the ability to respond very quickly. The focus of this paper is to propose better controls using droop characteristics to improve the dynamic interaction between different DG types in an autonomous microgrid. The transient behavior of DGs in the microgrid is investigated during the DG synchronization and load changes. Power sharing strategies based on frequency and voltage droop are considered for DGs. Droop control strategies are proposed for DGs to improve the smooth synchronization and dynamic power sharing minimizing transient oscillations in the microgrid. Simulation studies are carried out on PSCAD for validation.

Urban maze : A typological investigation in porous morphology and dynamic pedestrian networks

Mixed use typologies and pedestrian networks are two strategies commonly applied in design of the contemporary city. These approaches, aimed towards the creation of a more sustainalble urban environment, have their roots in the traditional, pre-industrial towns; they characterize urban form, articulating the tension between privaate and public realms through a series of typological variations as well as stimulating commercial activity in the city centre. Arcades, loggias and verandas are just some of the elements which can mediate this tension. Historically they have defined physical and social spaces with particular character; in the contemporary city these features are applied to deform the urban form and create a porous, dynamic morphology. This paper, comparing case studies from Italy, Japan and Australia, investigates how the design of the transition zone can define hybrid pedestrian networks, where a clear distinction between the public and private realms is no longer applicable. Pedestrians use the city in a dynamic way, combining trajectories on the public street with ones on the fringe or inside of the private built environment. In some cases, cities offer different pedestrian network possibilities at different times, as the commercial precints are subject to variations in accessibility across various timeframes. These walkable systems have an impact on the urban form and identity of places, redefining typologies and requiring an in depth analysis through plan, section and elevation diagrams.

Infinite-horizon policy-gradient estimation

Gradient-based approaches to direct policy search in reinforcement learning have received much recent attention as a means to solve problems of partial observability and to avoid some of the problems associated with policy degradation in value-function methods. In this paper we introduce GPOMDP, a simulation-based algorithm for generating a biased estimate of the gradient of the average reward in Partially Observable Markov Decision Processes (POMDPs) controlled by parameterized stochastic policies. A similar algorithm was proposed by Kimura, Yamamura, and Kobayashi (1995). The algorithm's chief advantages are that it requires storage of only twice the number of policy parameters, uses one free parameter β ∈ [0,1) (which has a natural interpretation in terms of bias-variance trade-off), and requires no knowledge of the underlying state. We prove convergence of GPOMDP, and show how the correct choice of the parameter β is related to the mixing time of the controlled POMDP. We briefly describe extensions of GPOMDP to controlled Markov chains, continuous state, observation and control spaces, multiple-agents, higher-order derivatives, and a version for training stochastic policies with internal states. In a companion paper (Baxter, Bartlett, & Weaver, 2001) we show how the gradient estimates generated by GPOMDP can be used in both a traditional stochastic gradient algorithm and a conjugate-gradient procedure to find local optima of the average reward. ©2001 AI Access Foundation and Morgan Kaufmann Publishers. All rights reserved.