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’.

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.

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.

The Maori social science academy and evidence-based policy

This paper focuses on recent moves to forge stronger linkages between the Māori social science academy and the policy industry. A critical appraisal of this development is offered, with particular attention given to the desirability of enhancing the academy’s role in the policy process, given the policy industry’s continued privileging of Eurocentric theory and research methodologies within the developing evidence-based environment. The paper ends with a discussion of the possibilities and problems associated with engagement with the policy industry, particularly as these relate to the various roles members can (or are forced to) take; either as ‘insiders’ (such as policy workers and contract researchers), or independent, critical ‘outsiders’. The author concludes that the best that insiders can hope for are incremental, largely ineffective changes to Māori policy, while independent members of the academy are best placed to speak on behalf of Māori, Māori communities, hapu and iwi.

Collaborative inquiries into literacy, place and identity in changing policy contexts : implications for teacher development

In this chapter we describe a history of collaboration between university-based literacy researchers and school-based teachers in teacher development programs and practitioner inquiries designed to improve literacy outcomes for students living in low-socioeconomic circumstances. We consider how an inquiry stance has informed teachers working for social justice through curriculum and pedagogy designed to connect children’s developing literacy repertoires with their changing material, social and linguistic contexts. We use examples from the practices of two of our long-term teacher-collaborators to show what has been possible to achieve, even in radically different policy contexts, because of teachers’ continued commitment to themes of place and belonging, and language and identity.

Having a yarn about smoking : using action research to develop a 'no smoking' policy within an Aboriginal health organisation

Objectives: This article reports on a culturally appropriate process of development of a smoke-free workplace policy within the peak Aboriginal Controlled Community Health Organisation in Victoria, Australia. Smoking is acknowledged as being responsible for at least 20% of all deaths in Aboriginal communities in Australia, and many Aboriginal health workers smoke. Methods: The smoke-free workplace policy was developed using the iterative, discursive and experience-based methodology of Participatory Action Research, combined with the culturally embedded concept of ‘having a yarn’. Results: Staff members initially identified smoking as a topic to be avoided within workplace discussions. This was due, in part, to grief (everyone had suffered a smoking related bereavement). Further, there was anxiety that discussing smoking would result in culturally difficult conflict. The use of yarning opened up a safe space for discussion and debate,enabling development of a policy that was accepted across the organisation. Conclusions: Within Aboriginal organisations, it is not sufficient to focus on the outcomes of policy development. Rather, due attention must be paid to the process employed in development of policy, particularly when that policy is directly related to an emotionally and communally weighted topic such as smoking.