Engaging with theories of dialogue and voice: Using Bakhtin as a framework to understand teaching and learning Indigenous Australian women's performance

In this paper I explore the Indigenous Australian women's performance classroom (hereafter ANTH2120) as a dialectic and discursive space where the location of possibility is opened for female Indigenous performers to enter into a dialogue from and between both non-Indigenous and Indigenous voices. The work of Bakhtin on dialogue serves as a useful standpoint for understanding the multiple speaking positions and texts in the ANTH2120 context. Bakhtin emphasizes performance, history, actuality and the openness of dialogue to provide an important framework for analysing multiple speaking positions and ways of making meaning through dialogue between shifting and differing subjectivities. I begin by briefly critiquing Bakhtin's "dialogic imagination" and consider the application and usefulness of concepts such as dialogism, heteroglossia and the utterance to understanding the ANTH2120 classroom as a polyphonic and discursive space. I then turn to an analysis of dialogue in the ANTH2120 classroom and primarily situate my gaze on an examination of the interactions that took place between the voices of myself as family/teacher/student and senior Yanyuwa women from the r e m o t e N o r t h e r n T e r r i t o r y A b o r i g i n a l c o m m u n i t y o f B o r r o l o o l a as family/performers/teachers. The 2000 and 2001 Yanyuwa women's performance workshops will be used as examples of the way power is constantly shifting in this dialogue to allow particular voices to speak with authority, and for others to remain silent as roles and relationships between myself and the Yanyuwa women change. Conclusions will be drawn regarding how my subject positions and white race privilege affect who speaks, who listens and on whose terms, and further, the efficacy of this pedagogical platform for opening up the location of possibility for Indigenous Australian women to play a powerful part in the construction of knowledges about women's performance traditions.

Selenium content of Australian foods: A review of literature values

The aim of this study was to review the published literature values for the selenium content of Australian foods. A secondary aim was to compare the results for Australian foods with food composition data from international sources to investigate the extent of geographical variation. Published food composition data sources for the selenium content in Australian foods were identified and assessed for data quality using established criteria. The selenium content is available for 148 individual food items. The highest values found are for fish (12.0-63.2 mug/100 g), meats (4.75-37.9 mug/100 g) and eggs (9.00-41.4 mug/100 g), followed by cereals (1.00-20.3 mug/100 g). Moderate levels are seen in dairy products (2.00-7.89 mug/100 g) while most fruits and vegetables have low levels (trace-3.27 mug/100 g). High selenium foods show the greatest level of geographical variation, with foods from the United States generally having higher selenium levels than Australian foods and foods from the United Kingdom and New Zealand having lower levels. This is the first attempt to review the available literature for selenium composition of Australian foods. These data serve as an interim measure for the assessment of selenium intake for use in epidemiological studies of diet-disease relationships. (C) 2002 Published by Elsevier Science Ltd.

The E(NK) model: extending the NK model to incorporate gene-by-environment interactions and epistasis for diploid genomes

The haploid NK model developed by Kauffman can be extended to diploid genomes and to incorporate gene-by-environment interaction effects in combination with epistasis. To provide the flexibility to include a wide range of forms of gene-by-environment interactions, a target population of environment types (TPE) is defined. The TPE consists of a set of E different environment types, each with their own frequency of occurrence. Each environment type conditions a different NK gene network structure or series of gene effects for a given network structure, providing the framework for defining gene-by-environment interactions. Thus, different NK models can be partially or completely nested within the E environment types of a TPE, giving rise to the E(NK) model for a biological system. With this model it is possible to examine how populations of genotypes evolve in context with properties of the environment that influence the contributions of genes to the fitness values of genotypes. We are using the E(NK) model to investigate how both epistasis and gene-by-environment interactions influence the genetic improvement of quantitative traits by plant breeding strategies applied to agricultural systems. © 2002 Wiley Periodicals, Inc.

The GP problem: quantifying gene-to-phenotype relationships

In this paper we refer to the gene-to-phenotype modeling challenge as the GP problem. Integrating information across levels of organization within a genotype-environment system is a major challenge in computational biology. However, resolving the GP problem is a fundamental requirement if we are to understand and predict phenotypes given knowledge of the genome and model dynamic properties of biological systems. Organisms are consequences of this integration, and it is a major property of biological systems that underlies the responses we observe. We discuss the E(NK) model as a framework for investigation of the GP problem and the prediction of system properties at different levels of organization. We apply this quantitative framework to an investigation of the processes involved in genetic improvement of plants for agriculture. In our analysis, N genes determine the genetic variation for a set of traits that are responsible for plant adaptation to E environment-types within a target population of environments. The N genes can interact in epistatic NK gene-networks through the way that they influence plant growth and development processes within a dynamic crop growth model. We use a sorghum crop growth model, available within the APSIM agricultural production systems simulation model, to integrate the gene-environment interactions that occur during growth and development and to predict genotype-to-phenotype relationships for a given E(NK) model. Directional selection is then applied to the population of genotypes, based on their predicted phenotypes, to simulate the dynamic aspects of genetic improvement by a plant-breeding program. The outcomes of the simulated breeding are evaluated across cycles of selection in terms of the changes in allele frequencies for the N genes and the genotypic and phenotypic values of the populations of genotypes.

Plasma growth hormone and growth hormone-binding protein during development in the marsupial brushtail possum (Trichosurus vulpecula)

Plasma concentrations of growth hormone (GH) were measured in the brushtail possum (Trichosurus vulpecula) pouch young from 25 through to 198 days post-partum (n=71). GH concentrations were highest early in pouch life (around 100 ng/ml), and thereafter declined in an exponential fashion to reach adult concentrations (10.8 +/- 1.8 ng/ml; n=21) by approximately 121-145 days post-partum, one to two months before the young is weaned. Growth hormone-binding protein (GHBP), which has been shown to modify the cellular actions of GH in eutherian mammals, was identified for the first time in a marsupial. Based on size exclusion gel filtration, possum GHBP had an estimated molecular mass of approximate to 65 kDa, similar to that identified in other mammalian species, and binding of I-125-labelled human GH (hGH) was displaced by excess hGH (20 mug). An immunoprecipitation method, in which plasma GHBP was rendered polyethylene glycol precipitable with a monoclonal antibody to the rabbit GHBP/GH receptor (MAb 43) and labelled with I-125-hGH, was used to quantitate plasma GHBP by Scatchard analysis in the developing (pooled plasma samples) and adult (individual animals) possums. Binding affinity (K-a) values in pouch young aged between 45 and 54 and 144 and 153 days post-partum varied between 1.0 and 2.4 x 10(9)/M, which was slightly higher than that in adult plasma (0.96 +/- 0.2 x 10(9)/M, n = 6). Binding capacity (B-max) values increased from non-detectable levels in animals aged 25-38 days post-partum to reach concentrations around half that seen in the adult (1.4 +/- 0.2 x 10(-9) M) by about 117 days post-partum and remained at this level until 153 days post-partum. Therefore, in early pouch life when plasma GH concentrations are highest, the very low concentrations of GHBP are unlikely to be important in terms of competing with GH-receptor for ligand or altering the half-life of circulating GH.

delta N-15 values of tropical savanna and monsoon forest species reflect root specialisations and soil nitrogen status

A large number of herbaceous and woody plants from tropical woodland, savanna, and monsoon forest were analysed to determine the impact of environmental factors (nutrient and water availability, fire) and biological factors (microbial associations, systematics) on plant delta(15)N values. Foliar delta(15)N values of herbaceous and woody species were not related to growth form or phenology, but a strong relationship existed between mycorrhizal status and plant delta(15)N. In woodland and savanna, woody species with ectomycorrhizal (ECM) associations and putative N-2-fixing species with ECM/arbuscular (AM) associations had lowest foliar delta(15)N values (1.0-0.6parts per thousand), AM species had mostly intermediate delta(15)N values (average +0.6parts per thousand), while non-mycorrhizal Proteaceae had highest delta(15)N values (+2.9 to +4.1parts per thousand). Similar differences in foliar delta(15)N were observed between AM (average 0.1 and 0.2parts per thousand) and non-mycorrhizal (average +0.8 and +0.3parts per thousand) herbaceous species in woodland and savanna. Leguminous savanna species had significantly higher leaf N contents (1.8-2.5% N) than non-fixing species (0.9-1.2% N) indicating substantial N acquisition via N-2 fixation. Monsoon forest species had similar leaf N contents (average 2.4% N) and positive delta(15)N values (+0.9 to +2.4parts per thousand). Soil nitrification and plant NO3- use was substantially higher in monsoon forest than in woodland or savanna. In the studied communities, higher soil N content and nitrification rates were associated with more positive soil delta(15)N and plant delta(15)N. In support of this notion, Ficus, a high NO3- using taxa associated with NO3- rich sites in the savanna, had the highest delta(15)N values of all AM species in the savanna. delta(15)N of xylem sap was examined as a tool for studying plant delta(15)N relations. delta(15)N of xylem sap varied seasonally and between differently aged Acacia and other savanna species. Plants from annually burnt savanna had significantly higher delta(15)N values compared to plants from less frequently burnt savanna, suggesting that foliar N-15 natural abundance could be used as marker for assessing historic fire regimes. Australian woodland and savanna species had low leaf delta(15)N and N content compared to species from equivalent African communities indicating that Australian biota are the more N depauperate. The largest differences in leaf delta(15)N occurred between the dominant ECM Australian and African savanna (miombo) species, which were depleted and enriched in N-15, respectively. While the depleted delta(15)N of Australian ECM species are similar to those of previous reports on ECM species in natural plant communities, the N-15-enriched delta(15)N of African ECM species represent an anomaly.

Bridging the gap between different statistical approaches: An integrated framework for modelling

This paper proposes a template for modelling complex datasets that integrates traditional statistical modelling approaches with more recent advances in statistics and modelling through an exploratory framework. Our approach builds on the well-known and long standing traditional idea of 'good practice in statistics' by establishing a comprehensive framework for modelling that focuses on exploration, prediction, interpretation and reliability assessment, a relatively new idea that allows individual assessment of predictions. The integrated framework we present comprises two stages. The first involves the use of exploratory methods to help visually understand the data and identify a parsimonious set of explanatory variables. The second encompasses a two step modelling process, where the use of non-parametric methods such as decision trees and generalized additive models are promoted to identify important variables and their modelling relationship with the response before a final predictive model is considered. We focus on fitting the predictive model using parametric, non-parametric and Bayesian approaches. This paper is motivated by a medical problem where interest focuses on developing a risk stratification system for morbidity of 1,710 cardiac patients given a suite of demographic, clinical and preoperative variables. Although the methods we use are applied specifically to this case study, these methods can be applied across any field, irrespective of the type of response.

An EM-based Semi-Parametric Mixture Model Approach to the Regression Analysis of Competing-Risks Data

We consider a mixture model approach to the regression analysis of competing-risks data. Attention is focused on inference concerning the effects of factors on both the probability of occurrence and the hazard rate conditional on each of the failure types. These two quantities are specified in the mixture model using the logistic model and the proportional hazards model, respectively. We propose a semi-parametric mixture method to estimate the logistic and regression coefficients jointly, whereby the component-baseline hazard functions are completely unspecified. Estimation is based on maximum likelihood on the basis of the full likelihood, implemented via an expectation-conditional maximization (ECM) algorithm. Simulation studies are performed to compare the performance of the proposed semi-parametric method with a fully parametric mixture approach. The results show that when the component-baseline hazard is monotonic increasing, the semi-parametric and fully parametric mixture approaches are comparable for mildly and moderately censored samples. When the component-baseline hazard is not monotonic increasing, the semi-parametric method consistently provides less biased estimates than a fully parametric approach and is comparable in efficiency in the estimation of the parameters for all levels of censoring. The methods are illustrated using a real data set of prostate cancer patients treated with different dosages of the drug diethylstilbestrol. Copyright (C) 2003 John Wiley Sons, Ltd.

Study of n-fold Weibull competing risk model

This paper deals with an n-fold Weibull competing risk model. A characterisation of the WPP plot is given along with estimation of model parameters when modelling a given data set. These are illustrated through two examples. A study of the different possible shapes for the density and failure rate functions is also presented. (C) 2003 Elsevier Ltd. All rights reserved.