Do you see what I mean? charting changing representations and receptions of the disabled body in contemporary and pop cultural performance

The meaning of the body emerges through acts of seeing, looking and staring in daily and dramatic performances. Acts that are, as Maike Bleeker argues1, bound up with the scopic rules, regimes and narratives that apply in specific cultures at specific times. In Western culture, the disabled body has been seen as a sign of defect, deficiency, fear, shame or stigma. Disabled artists – Mat Fraser, Bill Shannon, Aaron Williamson, Katherine Araniello, Liz Crow and Ju Gosling – have attempted, via performances that co-opt conventional images of the disabled body, to challenge dominant ways of representing and responding such bodies from within. In this paper, I consider what happens when non-disabled artists co-opt images of the disabled body to draw attention to, affirm, and even exoticise, eroticise or beautify, other modalities of or desires for difference. As Carrie Sandahl has noted2, the signs, symbols and somatic idiosyncrasies of the disabled body are, today, transported or translated into theatre, film and television as a metaphor or "master trope" for every body’s experience of difference. This happens in performance art (Guillermo Gomez-Pena’s use of a wheelchair in Chamber of Confessions), performance (Marie Chouinard's use of crutches, canes and walkers to represent dancers’ experience of becoming different or mutant during training in bODY rEMIX /gOLDBERG vARIATIONS), and pop culture (characters in wheelchairs in Glee or Oz). In this paper, I chart changing representations and receptions of the disabled body in such contexts. I use analysis of this cultural shift as a starting point for a re-consideration of questions about whether a face-toface encounter with a disabled body is in fact a privileged site for the emergence of a politics, and whether co-opting disability as a metaphor for a range of difference differences reduces its currency as a category around which a specific group might mobilise a politics.

Mean-field descriptions of collective migration with strong adhesion

Random walk models based on an exclusion process with contact effects are often used to represent collective migration where individual agents are affected by agent-to-agent adhesion. Traditional mean field representations of these processes take the form of a nonlinear diffusion equation which, for strong adhesion, does not predict the averaged discrete behavior. We propose an alternative suite of mean-field representations, showing that collective migration with strong adhesion can be accurately represented using a moment closure approach.

iiNet’s Hollywood ending : what does its court victory mean for copyright law?

In what is being billed as iiNet versus Hollywood, the Australian internet service provider has come out an apparent winner after the High Court dismissed a copyright infringement case brought by industry movie studios. The case was a final appeal by the industry in its attempts to crack down on internet users infringing copyright by using BitTorrent to download movies.

Estimating the effects of environmental exposures using a weighted mean of monitoring stations

The health effects of environmental hazards are often examined using time series of the association between a daily response variable (e.g., death) and a daily level of exposure (e.g., temperature). Exposures are usually the average from a network of stations. This gives each station equal importance, and negates the opportunity for some stations to be better measures of exposure. We used a Bayesian hierarchical model that weighted stations using random variables between zero and one. We compared the weighted estimates to the standard model using data on health outcomes (deaths and hospital admissions) and exposures (air pollution and temperature) in Brisbane, Australia. The improvements in model fit were relatively small, and the estimated health effects of pollution were similar using either the standard or weighted estimates. Spatial weighted exposures would be probably more worthwhile when there is either greater spatial detail in the health outcome, or a greater spatial variation in exposure.

Sufficiently informative measurements for stability of approximate conditional mean estimates

This paper establishes sufficient conditions to bound the error in perturbed conditional mean estimates derived from a perturbed model (only the scalar case is shown in this paper but a similar result is expected to hold for the vector case). The results established here extend recent stability results on approximating information state filter recursions to stability results on the approximate conditional mean estimates. The presented filter stability results provide bounds for a wide variety of model error situations.

Does weaker copyright mean stronger creative industries? Some lessons from China

We review the theory of intellectual property (IP) in the creative industries (CI) from the evolutionary economic perspective based on evidence from China. We argue that many current confusions and dysfunctions about IP can be traced to three widely overlooked aspects of the growth of knowledge context of IP in the CI: (1) the effect of globalization; (2) the dominating relative economic value of reuse of creative output over monopoly incentives to create input; and (3) the evolution of business models in response to institutional change. We conclude that a substantial weakening of copyright will, in theory, produce positive net public and private gain due to the evolutionary dynamics of all three dimensions.

Simplified method for including spatial correlations in mean-field approximations

Biological systems involving proliferation, migration and death are observed across all scales. For example, they govern cellular processes such as wound-healing, as well as the population dynamics of groups of organisms. In this paper, we provide a simplified method for correcting mean-field approximations of volume-excluding birth-death-movement processes on a regular lattice. An initially uniform distribution of agents on the lattice may give rise to spatial heterogeneity, depending on the relative rates of proliferation, migration and death. Many frameworks chosen to model these systems neglect spatial correlations, which can lead to inaccurate predictions of their behaviour. For example, the logistic model is frequently chosen, which is the mean-field approximation in this case. This mean-field description can be corrected by including a system of ordinary differential equations for pair-wise correlations between lattice site occupancies at various lattice distances. In this work we discuss difficulties with this method and provide a simplication, in the form of a partial differential equation description for the evolution of pair-wise spatial correlations over time. We test our simplified model against the more complex corrected mean-field model, finding excellent agreement. We show how our model successfully predicts system behaviour in regions where the mean-field approximation shows large discrepancies. Additionally, we investigate regions of parameter space where migration is reduced relative to proliferation, which has not been examined in detail before, and our method is successful at correcting the deviations observed in the mean-field model in these parameter regimes.

Genetic response to combined family selection for improved mean harvest weight in giant freshwater prawn (Macrobrachium rosenbergii) in Vietnam

We estimated genetic changes in body and carcass weight traits in a giant freshwater prawn (GFP) (Macrobrachium rosenbergii) population selected for increased body weight at harvest in Vietnam. The data set consisted of 18,387 individual body and 1730 carcass weight records, as well as full pedigree information collected over four generations. Average selection response (per generation) in body weight at harvest (transformed to square root) estimated as the difference between the Selection line and the Control group was 7.4% calculated from least squares mean (LSMs), 7.0% from estimated breeding values (EBVs) and 4.4% calculated from EBVs between two consecutive generations. Favorable correlated selection responses (estimated from LSMs) were found for other body traits including: total length, cephalothorax length, abdominal length, cephalothorax width, and abdominal width (12.1%, 14.5%, 10.4%, 15.5% and 13.3% over three selection generations, respectively). Data in the second generation of selection showed positive correlated responses for carcass weight traits including: abdominal weight, exoskeleton-off weight, and telson-off weight of 8.8%, 8.6% and 8.8%, respectively. We conclude that body weight at harvest responded well to the application of combined (between and within) family selection and correlated responses in carcass weight traits were favorable.

Distinguishing between mean-field, moment dynamics and stochastic descriptions of birth-death-movement processes

Mathematical descriptions of birth–death–movement processes are often calibrated to measurements from cell biology experiments to quantify tissue growth rates. Here we describe and analyze a discrete model of a birth–death-movement process applied to a typical two–dimensional cell biology experiment. We present three different descriptions of the system: (i) a standard mean–field description which neglects correlation effects and clustering; (ii) a moment dynamics description which approximately incorporates correlation and clustering effects, and; (iii) averaged data from repeated discrete simulations which directly incorporates correlation and clustering effects. Comparing these three descriptions indicates that the mean–field and moment dynamics approaches are valid only for certain parameter regimes, and that both these descriptions fail to make accurate predictions of the system for sufficiently fast birth and death rates where the effects of spatial correlations and clustering are sufficiently strong. Without any method to distinguish between the parameter regimes where these three descriptions are valid, it is possible that either the mean–field or moment dynamics model could be calibrated to experimental data under inappropriate conditions, leading to errors in parameter estimation. In this work we demonstrate that a simple measurement of agent clustering and correlation, based on coordination number data, provides an indirect measure of agent correlation and clustering effects, and can therefore be used to make a distinction between the validity of the different descriptions of the birth–death–movement process.

Incorporating spatial correlations into multispecies mean-field models

In biology, we frequently observe different species existing within the same environment. For example, there are many cell types in a tumour, or different animal species may occupy a given habitat. In modelling interactions between such species, we often make use of the mean field approximation, whereby spatial correlations between the locations of individuals are neglected. Whilst this approximation holds in certain situations, this is not always the case, and care must be taken to ensure the mean field approximation is only used in appropriate settings. In circumstances where the mean field approximation is unsuitable we need to include information on the spatial distributions of individuals, which is not a simple task. In this paper we provide a method that overcomes many of the failures of the mean field approximation for an on-lattice volume-excluding birth-death-movement process with multiple species. We explicitly take into account spatial information on the distribution of individuals by including partial differential equation descriptions of lattice site occupancy correlations. We demonstrate how to derive these equations for the multi-species case, and show results specific to a two-species problem. We compare averaged discrete results to both the mean field approximation and our improved method which incorporates spatial correlations. We note that the mean field approximation fails dramatically in some cases, predicting very different behaviour from that seen upon averaging multiple realisations of the discrete system. In contrast, our improved method provides excellent agreement with the averaged discrete behaviour in all cases, thus providing a more reliable modelling framework. Furthermore, our method is tractable as the resulting partial differential equations can be solved efficiently using standard numerical techniques.

Back to the roots : mean-variance analysis of relevance estimations

Recently, mean-variance analysis has been proposed as a novel paradigm to model document ranking in Information Retrieval. The main merit of this approach is that it diversifies the ranking of retrieved documents. In its original formulation, the strategy considers both the mean of relevance estimates of retrieved documents and their variance. How- ever, when this strategy has been empirically instantiated, the concepts of mean and variance are discarded in favour of a point-wise estimation of relevance (to replace the mean) and of a parameter to be tuned or, alternatively, a quantity dependent upon the document length (to replace the variance). In this paper we revisit this ranking strategy by going back to its roots: mean and variance. For each retrieved document, we infer a relevance distribution from a series of point-wise relevance estimations provided by a number of different systems. This is used to compute the mean and the variance of document relevance estimates. On the TREC Clueweb collection, we show that this approach improves the retrieval performances. This development could lead to new strategies to address the fusion of relevance estimates provided by different systems.

Estimating present day extreme water level exceedance probabilities around the coastline of Australia : tides, extra-tropical storm surges and mean sea level

The occurrence of extreme water levels along low-lying, highly populated and/or developed coastlines can lead to considerable loss of life and billions of dollars of damage to coastal infrastructure. Therefore it is vitally important that the exceedance probabilities of extreme water levels are accurately evaluated to inform risk-based flood management, engineering and future land-use planning. This ensures the risk of catastrophic structural failures due to under-design or expensive wastes due to over-design are minimised. This paper estimates for the first time present day extreme water level exceedence probabilities around the whole coastline of Australia. A high-resolution depth averaged hydrodynamic model has been configured for the Australian continental shelf region and has been forced with tidal levels from a global tidal model and meteorological fields from a global reanalysis to generate a 61-year hindcast of water levels. Output from this model has been successfully validated against measurements from 30 tide gauge sites. At each numeric coastal grid point, extreme value distributions have been fitted to the derived time series of annual maxima and the several largest water levels each year to estimate exceedence probabilities. This provides a reliable estimate of water level probabilities around southern Australia; a region mainly impacted by extra-tropical cyclones. However, as the meteorological forcing used only weakly includes the effects of tropical cyclones, extreme water level probabilities are underestimated around the western, northern and north-eastern Australian coastline. In a companion paper we build on the work presented here and more accurately include tropical cyclone-induced surges in the estimation of extreme water level. The multi-decadal hindcast generated here has been used primarily to estimate extreme water level exceedance probabilities but could be used more widely in the future for a variety of other research and practical applications.