Magistrates' decision-making: personality, process and outcome

The thesis examined personality and socio-demographic characteristics of individuals and their relationship to the way in which magistrates approach the sentencing of offenders and the choices they make. It was based on a review of the theoretical approaches to models of decision-making and the concept of individual differences. A pluralistic methodology was adopted combining a quasi-experimental approach in the first study, with two further qualitative studies. Study 1 reported the profile data for the participants, all practising magistrates, and their responses to case study vignettes. Study 2 considered participants' perception of the sentencing process and the factors that influenced their decisions using an interpretative phenomenological approach, while Study 3 applied content and discourse analysis to transcripts of a sentencing training exercise in which magistrates had participated. Analyses of the first study were mostly correlational. Modest associations between Locus of Control and Legal Authoriarianism with severity of sentence were demonstrated and also small gender differences in sentencing choice. The study concluded that there was no support for hypotheses linking other personality trait measurements with the severity of sentence or the approach adopted, using an algebraic model to represent the process. In the subsequent studies, evidence emerged to suggest a more holistic approach to sentencing, guided by advice on structured decision-making, while accommodating the influences of probation service reports, diverse sentencing aims and the advice of the legal professionals. The impact of group interactions was also apparent. This varied with individual characteristics and acquired competences necessary for satisfactory appraisal. The interpretation of 'roles' on a sentencing Bench and their potential effects on the process and outcome of sentencing was observed

Evolution and turnover in scaling systems

Scaling has been discovered in the long tails of size distributions characterizing a variety of diverse systems, many of which evolve in terms of the size of their components through competition. Such time-invariant macro distributions, however, often obscure the micro-dynamics of change, such as continual turnover in the rank order of the constituents. Here we show how a model drawn from evolutionary theory can explain this change, such that the time spent in the top ranked constituents is finite and also characterized by longtailed distributions. To show the broad applicability of this model, we compare typical model runs to real-world examples including US boys’ names, UK Number One for pop albums, journal article keywords, and city sizes

Econophysics and the social sciences: Challenges and opportunities

The discipline of econophysics is now some 15 years old. The purpose of this article is to consider the challenges which it faces in gaining broader scientific acceptance in the social sciences and especially within economics

Mean Field Voter Model of Election to the House of Representatives in Japan

In this study, we propose a mechanical model of a plurality election based on a mean field voter model. We assume that there are three candidates in each electoral district, i.e., one from the ruling party, one from the main opposition party, and one from other political parties. The voters are classified as fixed supporters and herding (floating) voters with ratios of $1-p$ and $p$, respectively. Fixed supporters make decisions based on their information and herding voters make the same choice as another randomly selected voter. The equilibrium vote-share probability density of herding voters follows a Dirichlet distribution. We estimate the composition of fixed supporters in each electoral district and $p$ using data from elections to the House of Representatives in Japan (43rd to 47th). The spatial inhomogeneity of fixed supporters explains the long-range spatial and temporal correlations. The estimated values of $p$ are close to the estimates obtained from a survey.Comment: 11 pages, 7 figure

Why bad ideas are a good idea

What would happen if we wrote an Abstract that was the exact opposite of what the paper described? This is a bad idea, but it makes us think more carefully than usual about properties of Abstracts. This paper describes BadIdeas, a collection of techniques that uses ???bad??? or ???silly??? ideas to inspire creativity, explore design domains and teach critical thinking in interaction design. We describe the approach, some evidence, how it is performed in practice and experience in its use.published or submitted for publicationis peer reviewe

Theory of Gaussian variational approximation for a Poisson mixed model

Likelihood-based inference for the parameters of generalized linear mixed models is hindered by the presence of intractable integrals. Gaussian variational approximation provides a fast and effective means of approximate inference. We provide some theory for this type of approximation for a simple Poisson mixed model. In particular, we establish consistency at rate m -1/2 +n-1, where m is the number of groups and n is the number of repeated measurements

Theory of Gaussian Variational Approximation for a Poisson Mixed Model

Likelihood-based inference for the parameters of generalized linear mixed models is hindered by the presence of intractable integrals. Gaussian variational approximation provides a fast and effective means of approximate inference. We provide some theory for this type of approximation for a simple Poisson mixed model. In particular, we establish consistency at rate m−1/2 + n−1, where m is the number of groups and n is the number of repeated measurements

Ecological indicators for abandoned mines, Phase 1: Review of the literature

Mine waters have been identified as a significant issue in the majority of Environment Agency draft River Basin Management Plans. They are one of the largest drivers for chemical pollution in the draft Impact Assessment for the Water Framework Directive (WFD), with significant failures of environmental quality standards (EQS) for metals (particularly Cd, Pb, Zn, Cu, Fe) in many rivers linked to abandoned mines. Existing EQS may be overprotective of aquatic life which may have adapted over centuries of exposure. This study forms part of a larger project to investigate the ecological impact of metals in rivers, to develop water quality targets (alternative objectives for the WFD) for aquatic ecosystems impacted by long-term mining pollution. The report reviews literature on EQS failures, metal effects on aquatic biota and effects of water chemistry, and uses this information to consider further work. A preliminary assessment of water quality and biology data for 87 sites across Gwynedd and Ceredigion (Wales) shows that existing Environment Agency water quality and biology data could be used to establish statistical relations between chemical variables and metrics of ecological quality. Visual representation and preliminary statistical analyses show that invertebrate diversity declines with increasing zinc concentration. However, the situation is more complex because the effects of other metals are not readily apparent. Furthermore, pH and aluminium also affect streamwater invertebrates, making it difficult to tease out toxicity due to individual mine-derived metals. The most characteristic feature of the plant communities of metal-impacted systems is a reduction in diversity, compared to that found in comparable unimpacted streams. Some species thrive in the presence of heavy metals, presumably because they are able to develop metal tolerance, whilst others consistently disappear. Effects are, however, confounded by water chemistry, particularly pH. Tolerant species are spread across a number of divisions of photosynthetic organisms, though green algae, diatoms and blue-green algae are usually most abundant, often thriving in the absence of competition and/or grazing. Current UK monitoring techniques focus on community composition and, whilst these provide a sampling and analytical framework for studies of metal impacts, the metrics are not sensitive to these impacts. There is scope for developing new metrics, based on community-level analyses and for looking at morphological variations common in some taxa at elevated metal concentrations. On the whole, community-based metrics are recommended, as these are easier to relate to ecological status definitions. With respect to invertebrates and fish, metals affect individuals, population and communities but sensitivity varies among species, life stages, sexes, trophic groups and with body condition. Acclimation or adaptation may cause varying sensitivity even within species. Ecosystem-scale effects, for example on ecological function, are poorly understood. Effects vary between metals such as cadmium, copper, lead, chromium, zinc and nickel in order of decreasing toxicity. Aluminium is important in acidified headwaters. Biological effects depend on speciation, toxicity, availability, mixtures, complexation and exposure conditions, for example discharge (flow). Current water quality monitoring is unlikely to detect short-term episodic increases in metal concentrations or evaluate the bioavailability of elevated metal concentrations in sediments. These factors create uncertainty in detecting ecological impairment in metal-impacted ecosystems. Moreover, most widely used biological indicators for UK freshwaters were developed for other pressures and none distinguishes metal impacts from other causes of impairment. Key ecological needs for better regulation and management of metals in rivers include: i) models relating metal data to ecological data that better represent influences on metal toxicity; ii) biodiagnostic indices to reflect metal effects; iii) better methods to identify metal acclimation or adaptation among sensitive taxa; iv) better investigative procedures to isolate metal effects from other pressures. Laboratory data on the effects of water chemistry on cationic metal toxicity and bioaccumulation show that a number of chemical parameters, particularly pH, dissolved organic carbon (DOC) and major cations (Na, Mg, K, Ca) exert a major influence on the toxicity and/or bioaccumulation of cationic metals. The biotic ligand model (BLM) provides a conceptual framework for understanding these water chemistry effects as a combination of the influence of chemical speciation, and metal uptake by organisms in competition with H+ and other cations. In some cases where the BLM cannot describe effects, empirical bioavailable models have been successfully used. Laboratory data on the effects of metal mixtures across different water chemistries are sparse, with implications for transferring understanding to mining-impacted sites in the field where mixture effects are likely. The available field data, although relatively sparse, indicate that water chemistry influences metal effects on aquatic ecosystems. This occurs through complexation reactions, notably involving dissolved organic matter and metals such as Al, Cu and Pb. Secondly, because bioaccumulation and toxicity are partly governed by complexation reactions, competition effects among metals, and between metals and H+, give rise to dependences upon water chemistry. There is evidence that combinations of metals are active in the field; the main study conducted so far demonstrated the combined effects of Al and Zn, and suggested, less certainly, that Cu and H+ can also contribute. Chemical speciation is essential to interpret and predict observed effects in the field. Speciation results need to be combined with a model that relates free ion concentrations to toxic effect. Understanding the toxic effects of heavy metals derived from abandoned mines requires the simultaneous consideration of the acidity-related components Al and H+. There are a number of reasons why organisms in waters affected by abandoned mines may experience different levels of metal toxicity than in the laboratory. This could lead to discrepancies between actual field behaviour and that predicted by EQS derived from laboratory experiments, as would be applied within the WFD. The main factors to consider are adaptation/acclimation, water chemistry, and the effects of combinations of metals. Secondary effects are metals in food, metals supplied by sediments, and variability in stream flows. Two of the most prominent factors, namely adaptation/ acclimation and bioavailability, could justify changes in EQS or the adoption of an alternative measure of toxic effects in the field. Given that abandoned mines are widespread in England and Wales, and the high cost of their remediation to meet proposed WFD EQS criteria, further research into the question is clearly justified. Although ecological communities of mine-affected streamwaters might be over-protected by proposed WFD EQS, there are some conditions under which metals emanating from abandoned mines definitely exert toxic effects on biota. The main issue is therefore the reliable identification of chemical conditions that are unacceptable and comparison of those conditions with those predicted by WFD EQS. If significant differences can convincingly be demonstrated, the argument could be made for alternative standards for waters affected by abandoned mines. Therefore in our view, the immediate research priority is to improve the quantification of metal effects under field circumstances. Demonstration of dose-response relationships, based on metal mixtures and their chemical speciation, and the use of better biological tools to detect and diagnose community-level impairment, would provide the necessary scientific information