Critical reflections on emancipatory partnerships in transition research: discerning perspectives of New Zealand Students on the autism spectrum

Transition from school involves different perspectives. Those most silenced in the process are transitioning students with significant disability, and similarly, they are alienated from the conduct of research. In this empirical project, three young men with complex autism conditions in Aotearoa New Zealand reclaimed their position as experts on their own transitions, and moreover, their contributions to research on the subject. Over a six-month ethnography, unique methodological adaptions were used to access personal insights and capabilities through emancipatory partnerships. The research forged collaborations that have the potential to be mirrored in future practices applicable to a transition with dignity.     

Dynamic multilevel governance for sustainable transformation as postnational configuration

Modern societies are increasingly having to cope with profound socio-political transformations, such as the transition from fossil energy production and consumption to more sustainable energy systems. Transformations ignite dynamics, processes, and forces, which induce new challenges for traditional structures and orders because major changes in society and politics are shifting from established manners, customs, and modes of behavior to new norms and values. Transformations cause epistemological uncertainty and complexity and challenge ontological fundaments and ethical convictions. National structures alone are not adequate to the task of handling the corresponding challenges because the capacity of domestic politics and regulations is too weak to achieve eligible political outcomes that can guide and structure transformations. In this light, I argue for a form of dynamic multilevel governance as a postnational configuration that has the capability and power to reform and transfigure institutions, structure and agency, hierarchies, cultural fabrics, socio-technical systems, and infrastructures toward new social and political orders. I theoretically and normatively conceptualize and justify three major governance framework conditions as hallmarks of dynamic multilevel governance, namely inclusiveness, adaptiveness, and distributed and differentiated deliberation. These capabilities produce reflexive authority with transformative and structuring power to tackle transformation issues. My notion of dynamic multilevel governance relies on thoughts in new institutionalism, network theory, deliberative democracy theory, discourse ethics, and different concepts of governance. I combine theory, normative justification, and institutional feasibility.     

Social scientists as technicians,advisors and meaning producers

In this paper, we are addressing three issues that are at the core of scholarly reflections about the societal role of social science knowledge: (1) Social scientists tend to follow – although this is not always a deliberate choice – one of three models that describe their role as the producers of practical knowledge. For the sake of simplicity we have called the three models the “model of the technician”, the “model of the advisor” and the “model of the meaning producer”. (2) Due to the need for social inquiry to adopt a particular, restrictive perspective of its domain, useful knowledge is a complicated matter. Hence the need to put into question a widely supported notion at least among social scientists: When asked about the reasons for the limited “power” of social science knowledge the response frequently is that the adequacy and practical usefulness of social science knowledge is a function of its capturing the full complexity of what indeed are complex social phenomena. (3) Social scientists often tend to lament the marginal impact their intellectual efforts have on society, and they look with great envy across the divide of the so-called two cultures, wondering how and when they will be able to achieve the same kind of success and prestige the natural sciences and technology appear to enjoy in most societies. However, this unhappy view systematically understates the actual power of social science knowledge, in particular its role as a mind maker or meaning producer.     

Financial insecurity and risk experiences of justice involved persons with severe mental illness

More information is needed about the financial experiences of justice-involved persons with severe mental illness. Qualitative and quantitative methods were used to examine the financial resources, financial risk experiences, and financial literacy of a random sample of 12 mental health court participants. Mental health court participants had limited financial resources, frequently ran out of money, and had engaged very few financial tools to manage their money. Justice-involved persons with severe mental illness need financial management interventions to help develop strategies for managing depleted resources and to develop the financial resources needed to live in community settings.     

Bootstrap Bartlett correction in inflated beta regression

The inflated beta regression model aims to enable the modeling of responses in the intervals (0, 1], [0, 1), or [0, 1]. In this model, hypothesis testing is often performed based on the likelihood ratio statistic. The critical values are obtained from asymptotic approximations, which may lead to distortions of size in small samples. In this sense, this article proposes the bootstrap Bartlett correction to the statistic of likelihood ratio in the inflated beta regression model. The proposed adjustment only requires a simple Monte Carlo simulation. Through extensive Monte Carlo simulations the finite sample performance (size and power) of the proposed corrected test is compared to the usual likelihood ratio test and the Skovgaard adjustment already proposed in the literature. The numerical results evidence that inference based on the proposed correction is much more reliable than that based on the usual likelihood ratio statistics and the Skovgaard adjustment. At the end of the work, an application to real data is also presented.     

Comparison of confidence intervals for the Behrens-Fisher problem

The Behrens–Fisher problem concerns the inferences for the difference between means of two independent normal populations without the assumption of equality of variances. In this article, we compare three approximate confidence intervals and a generalized confidence interval for the Behrens–Fisher problem. We also show how to obtain simultaneous confidence intervals for the three population case (analysis of variance, ANOVA) by the Bonferroni correction factor. We conduct an extensive simulation study to evaluate these methods in respect to their type I error rate, power, expected confidence interval width, and coverage probability. Finally, the considered methods are applied to two real dataset.     

Optimization of problems with multivariate multiple functional responses: A case study in air quality

Optimization of multi-response problems is a popular subject in the literature. However, the problem becomes complicated when the responses are functional due to the existence of signal factors. In this article, we have proposed a combined index to optimize multivariate multiple functional responses by considering functional specification limits and a target. The relation among the responses and controllable factors is characterized by polynomial equations to consider the curvature of the response functions. The validity of the proposed method is checked by a simulation example. To show the applicability of the proposed method, a real case about Tehran air quality is analyzed. Latitude and longitude are considered to be signal factors, and different pollutant values are responses of the experiment. Government policies in each time interval are considered as controllable factors. Finally, an optimization algorithm is used to find the best decisions for government policies.     

Using multivariate time series methods to estimate location and climate change effects on temperature readings employed in electricity demand simulation

Long‐term historical daily temperatures are used in electricity forecasting to simulate the probability distribution of future demand but can be affected by changes in recording site and climate. This paper presents a method of adjusting for the effect of these changes on daily maximum and minimum temperatures. The adjustment technique accommodates the autocorrelated and bivariate nature of the temperature data which has not previously been taken into account. The data are from Perth, Western Australia, the main electricity demand centre for the South‐West of Western Australia. The statistical modelling involves a multivariate extension of the univariate time series ‘interleaving method’, which allows fully efficient simultaneous estimation of the parameters of replicated Vector Autoregressive Moving Average processes. Temperatures at the most recent weather recording location in Perth are shown to be significantly lower compared to previous sites. There is also evidence of long‐term heating due to climate change especially for minimum temperatures.     

The propensity of third sector organisations to borrow money in the UK

In recent years there has been much policy interest in the development of social investment initiatives. Many such proposals depend upon third sector organisations (TSOs) loaning working capital in order to bridge gaps in cash flow. Existing studies on the willingness of TSOs to borrow have tended to used selective samples, which may have led to an exaggeration of market demand. This article explores, with reference to robust evidence on the attitudes and behaviours of representative samples of TSOs from the Third Sector Trends Study in Northern England, the extent of interest in borrowing for a range of purposes including to buy or upgrade property, buy equipment or facilities, or borrow working capital. The article makes observations on current and future market demand for loans in light of the way that TSO leaders’ balance their dependence on given, earned and borrowed money.     

The use of length‐biased distributions in statistical monitoring

Statistical process monitoring (SPM) has been used extensively recently in order to assure the quality of the output of industrial processes. Techniques of SPM have been efficiently applied during the last two decades in non‐industrial processes. A field of application with great interest is public health monitoring, where a pitfall with which we have to deal is the fact that available samples are not random in all cases. In the majority of cases, we monitor measurements derived from patient admissions to a hospital against control limits that were calculated using a sample of data taken from an epidemiological survey. In this work, we bridge the gap of a change in the sampling scheme from Phase I to Phase II, studying the case where the sampling during Phase II is biased. We present the appropriate methodology and then apply extensive numerical simulation in order to explore the performance of the proposed methodology, for measurements following various asymmetrical distributions. As the simulations show, the proposed methodology has a significantly better performance than the standard procedure.