A Case Study in Policy Delivery:Examining Social Inclusion through Interpretation and Practice

The current body of literature regarding social inclusion and the arts tends to focus
on two areas: the lack of clear or common understanding of the terminology involved
(GLLAM, 2000) and the difficulty in measuring impact (Newman 2001). Further, much
of the literature traces the historical evolution of social inclusion policy within the arts
from a political and social perspective (Belfiore & Bennett, 2007), whilst others
examine the situation in the context of the museum as an institution more generally
(Sandell, 2002b). Such studies are essential; however they only touch on the
importance of understanding the context of social inclusion programmes. As each
individual’s experience of exclusion (or inclusion) is argued to be different (Newman
et al., 2005) and any experience is also process-based (SEU 2001), there is a need
for more thorough examination of the processes underpinning project delivery
(Butterfoss, 2006), particularly within a field that has its own issues of exclusion, such
as the arts (Bourdieu & Darbel, 1991). This paper presents case study findings of a
programme of contemporary arts participation for adults with learning difficulties
based at an arts centre in Liverpool. By focusing on practice, the paper applies
Wenger’s (1998) social theory of learning in order to assert that rather than search
for measurable impacts, examining the delivery of programmes within their individual
contexts will provide the basis for a more reflective practice and thus more effective
policy making.

Politeness and honesty contribute additively to the interpretation of scalar expressions

Scalar terms have been the focus of much recent attention. People can interpret such terms narrowly, for example, interpreting A or B to convey A or B but not both, on the grounds that a speaker would have explicitly used a more informative term (i.e., and) had he or she been in a position to do so; or they can interpret such terms broadly (A or B or both). Examined here are the effects of politeness contexts and self-rated honesty on people’s interpretation of the scalar connective or. In two experiments, it is shown that participants are less likely to adopt the narrow interpretation when the communicative context is face threatening, and that regardless of context, participants high in self-rated honesty adopt the narrow interpretation to a greater extent than those low in self-rated honesty. These results are consistent with the claim that an assumption of honesty underlies certain pragmatic inferences and suggest that personality may be an important source of individual differences in language interpretation.

How does Oyster work? The simple interpretation of Oyster mathematics

Oyster® is a surface-piercing flap-type device designed to harvest wave energy in the nearshore environment. Established mathematical theories of wave energy conversion, such as 3D point-absorber and 2D terminator theory, are inadequate to accurately describe the behaviour of Oyster, historically resulting in distorted conclusions regarding the potential of such a concept to harness the power of ocean waves. Accurately reproducing the dynamics of Oyster requires the introduction of a new reference mathematical model, the “flap-type absorber”. A flap-type absorber is a large thin device which extracts energy by pitching about a horizontal axis parallel to the ocean bottom. This paper unravels the mathematics of Oyster as a flap-type absorber. The main goals of this work are to provide a simple–yet accurate–physical interpretation of the laws governing the mechanism of wave power absorption by Oyster and to emphasise why some other, more established, mathematical theories cannot be expected to accurately describe its behaviour.

Masks as methodology and the phenomenological turn: issues of interpretation

The purposes of this chapter are to argue for (i) the heuristic value of the concept of mask and masking in research which has its basis in psychodynamic theory but relating it to socio-cultural theory as means to understanding self-experience (ii) the value of creating and performing masks as one valuable methodological ‘embodied’ form in social and educational research that represent individuals’ richly textured self-other constructions and allow for the interrogation of any simplistic dichotomies associated with notions of ‘inside’ ‘outside’ categories (iii) exploring possibilities and dilemmas of interpretation within this frame

Palynological perspectives on vegetation survey: a critical step for model-based reconstruction of Quaternary land cover

1. Quantitative reconstruction of past vegetation distribution and abundance from sedimentary pollen records provides an important baseline for understanding long term ecosystem dynamics and for the calibration of earth system process models such as regional-scale climate models, widely used to predict future environmental change. Most current approaches assume that the amount of pollen produced by each vegetation type, usually expressed as a relative pollen productivity term, is constant in space and time.
2. Estimates of relative pollen productivity can be extracted from extended R-value analysis (Parsons and Prentice, 1981) using comparisons between pollen assemblages deposited into sedimentary contexts, such as moss polsters, and measurements of the present day vegetation cover around the sampled location. Vegetation survey method has been shown to have a profound effect on estimates of model parameters (Bunting and Hjelle, 2010), therefore a standard method is an essential pre-requisite for testing some of the key assumptions of pollen-based reconstruction of past vegetation; such as the assumption that relative pollen productivity is effectively constant in space and time within a region or biome.
3. This paper systematically reviews the assumptions and methodology underlying current models of pollen dispersal and deposition, and thereby identifies the key characteristics of an effective vegetation survey method for estimating relative pollen productivity in a range of landscape contexts.
4. It then presents the methodology used in a current research project, developed during a practitioner workshop. The method selected is pragmatic, designed to be replicable by different research groups, usable in a wide range of habitats, and requiring minimum effort to collect adequate data for model calibration rather than representing some ideal or required approach. Using this common methodology will allow project members to collect multiple measurements of relative pollen productivity for major plant taxa from several northern European locations in order to test the assumption of uniformity of these values within the climatic range of the main taxa recorded in pollen records from the region.

The Holocene vegetation cover of Britain and Ireland: overcoming problems of scale and discerning patterns of openness

The vegetation of Europe has undergone substantial changes during the course of the Holocene epoch, resulting from range expansion of plants following climate amelioration, competition between taxa and disturbance through anthropogenic activities. Much of the detail of this pattern is understood from
decades of pollen analytical work across Europe, and this understanding has been used to address questions relating to vegetation-climate feedback, biogeography and human impact. Recent advances in modelling the relationship between pollen and vegetation now make it possible to transform pollen
proportions into estimates of vegetation cover at both regional and local spatial scales, using the Landscape Reconstruction Algorithm (LRA), i.e. the REVEALS (Regional Estimates of VEgetation Abundance from Large Sites) and the LOVE (LOcal VEgetation) models. This paper presents the compilation and analysis of 73 pollen stratigraphies from the British Isles, to assess the application of the LRA and describe the pattern of landscape/woodland openness (i.e. the cover of low herb and bushy vegetation) through the Holocene. The results show that multiple small sites can be used as an effective replacement for a single large site for the reconstruction of regional vegetation cover. The REVEALS vegetation estimates imply that the British Isles had a greater degree of landscape/woodland openness at the regional scale than areas on the European mainland. There is considerable spatial bias in the British Isles dataset towards wetland areas and uplands, which may explain higher estimates of landscape openness compared with Europe. Where multiple estimates of regional vegetation are available from within the same region inter-regional differences are greater than intra-regional differences, supporting the use of the REVEALS model to the estimation of regional vegetation from pollen data.

Technology, work organisation and job quality in the service sector: an introduction’

This special issue volume is concerned with how technology is changing the nature of work and working conditions while generating new products and new forms of service delivery. The five articles included in this volume cover service work, from the routine and clerical through to highly credentialed and professional work. Although some of the established challenges concerning the impact of Information and Communication Technology (ICT) on work and workplaces are evident in the articles, it is also clear that new service delivery processes demand new skills and training to some extent. Overall findings indicate that while ICT competencies are important, they need to be supplemented by the soft skills that are crucial for effective customer interactions and more open work systems with greater autonomy and participation whereby flexible work teams can have a positive impact on job quality outcomes. This introductory article examines technology and the changing nature of work through three strands of interpretation, prior to introducing the five articles in this special issue.

Interpretation of electrochemical measurements made during micro-scale abrasion-corrosion

This paper brings together and analyzes recent work based on the interpretation of the electrochemical measurements made on a modified micro-abrasion-corrosion tester used in several research programmes. These programmes investigated the role of abradant size, test solution pH in abrasion-corrosion of biomaterials, the abrasion-corrosion performance of sintered and thermally sprayed tungsten carbide surfaces under downhole drilling environments and the abrasion-corrosion of UNS S32205 duplex stainless steel. Various abrasion tests were conducted under two-body grooving, three-body rolling and mixed grooving-rolling abrasion conditions, with and without abrasives, on cast F75 cobalt-chromium-molybdenum (CoCrMo) alloy in simulated body fluids, 2205 in chloride containing solutions as well as sprayed and sintered tungsten carbide surfaces in simulated downhole fluids. Pre- and post-test inspections based on optical and scanning electron microscopy analysis are used to help interpret the electrochemical response and current noise measurements made in situ during micro-abrasion-corrosion tests. The complex wear and corrosion mechanisms and their dependence on the microstructure and surface composition as a function of the pH, abrasive concentration, size and type are detailed and linked to the electrochemical signals. The electrochemical versus mechanical processes are plotted for different test parameters and this new approach is used to interpret tribo-corrosion test data to give greater insights into different tribo-corrosion systems. Thus new approaches to interpreting in-situ electrochemical responses to surfaces under different abrasive wear rates, different abrasives and liquid environments (pH and NaCl levels) are made. This representation is directly related to the mechano-electrochemical processes on the surface and avoids quantification of numerous synergistic, antagonistic and additive terms associated with repeat experiments. (C) 2010 Elsevier Ltd. All rights reserved.

Effective grain size distribution analysis for interpretation of tidal-deltaic facies: West Bengal Sundarbans

Research over the past two decades on the Holocene sediments from the tide dominated west side of the lower Ganges delta has focussed on constraining the sedimentary environment through grain size distributions (GSD). GSD has traditionally been assessed through the use of probability density function (PDF) methods (e.g. log-normal, log skew-Laplace functions), but these approaches do not acknowledge the compositional nature of the data, which may compromise outcomes in lithofacies interpretations. The use of PDF approaches in GSD analysis poses a series of challenges for the development of lithofacies models, such as equifinal distribution coefficients and obscuring the empirical data variability. In this study a methodological framework for characterising GSD is presented through compositional data analysis (CODA) plus a multivariate statistical framework. This provides a statistically robust analysis of the fine tidal estuary sediments from the West Bengal Sundarbans, relative to alternative PDF approaches.

Predicting forest attributes In southeast Alaska using artificial neural networks

Artificial neural network (ANN) methods are used to predict forest characteristics. The data source is the Southeast Alaska (SEAK) Grid Inventory, a ground survey compiled by the USDA Forest Service at several thousand sites. The main objective of this article is to predict characteristics at unsurveyed locations between grid sites. A secondary objective is to evaluate the relative performance of different ANNs. Data from the grid sites are used to train six ANNs: multilayer perceptron, fuzzy ARTMAP, probabilistic, generalized regression, radial basis function, and learning vector quantization. A classification and regression tree method is used for comparison. Topographic variables are used to construct models: latitude and longitude coordinates, elevation, slope, and aspect. The models classify three forest characteristics: crown closure, species land cover, and tree size/structure. Models are constructed using n-fold cross-validation. Predictive accuracy is calculated using a method that accounts for the influence of misclassification as well as measuring correct classifications. The probabilistic and generalized regression networks are found to be the most accurate. The predictions of the ANN models are compared with a classification of the Tongass national forest in southeast Alaska based on the interpretation of satellite imagery and are found to be of similar accuracy.

Interpretation of Section 17 Employment Protection Act in the light of ECJ case law and under consideration of the cases pending before the Federal Labour Court

This article analyses the relevance of the ECJ ruling in Junk for German labour law.