Evaluational adjectives

This paper demarcates a theoretically interesting class of "evaluational adjectives." This class includes predicates expressing various kinds of normative and epistemic evaluation, such as predicates of personal taste, aesthetic adjectives, moral adjectives, and epistemic adjectives, among others. Evaluational adjectives are distinguished, empirically, in exhibiting phenomena such as discourse-oriented use, felicitous embedding under the attitude verb `find', and sorites-susceptibility in the comparative form. A unified degree-based semantics is developed: What distinguishes evaluational adjectives, semantically, is that they denote context-dependent measure functions ("evaluational perspectives")—context-dependent mappings to degrees of taste, beauty, probability, etc., depending on the adjective. This perspective-sensitivity characterizing the class of evaluational adjectives cannot be assimilated to vagueness, sensitivity to an experiencer argument, or multidimensionality; and it cannot be demarcated in terms of pretheoretic notions of subjectivity, common in the literature. I propose that certain diagnostics for "subjective" expressions be analyzed instead in terms of a precisely specified kind of discourse-oriented use of context-sensitive language. I close by applying the account to `find x PRED' ascriptions

Assessing social responsibility::A quantitative analysis of Appraisal in BP’s and IKEA’s social reports

A growing public awareness of the potential negative impacts of corporate activities on the natural environment and society compels large companies to invest increasing resources in the communication of their responsible conduct. This article employs Appraisal theory in a comparative analysis of BP’s and IKEA’s 2009 social reports, each company’s record of their non-financial performance. The main objective is to explore how, through Appraisal resources, BP and IKEA construct their corporate identity and relationship with their stakeholders. The analysis reveals two markedly different approaches to the construction of a responsible corporate identity. While BP deploys interpersonal resources to portray itself as a trustworthy and authoritative expert, IKEA discloses itself as a sensitive and caring corporation, engaged in a continual effort to improve. These differences are interpreted in light of the legitimization challenges the two companies face

'What is this corpus about?': Using topic modelling to explore a specialised corpus

This paper introduces topic modelling, a machine learning technique that automatically identifies 'topics' in a given corpus. The paper illustrates its use in the exploration of a corpus of academic English. It first offers the intuitive explanation of the underlying mechanism of topic modelling and describes the procedure for building a model, including the decisions involved in the model-building process. The paper then explores the model. A topic in topic models is characterised by a set of co-occurring words, and we will demonstrate that such topics bring us rich insights into the nature of a corpus. As exemplary tasks, this paper identifies the prominent topics in different parts of papers, investigates the chronological change of a journal, and reveals different types of papers in the journal. The paper further compares topic modelling to two more traditional techniques in corpus linguistics, semantic annotation and keywords analysis, and highlights the strengths of topic modelling.We believe that topic modelling is particularly useful in the initial exploration of a corpus

On Being Negative

This paper investigates the pragmatic expressions of negative evaluation (negativity) in two corpora: (i) comments posted online in response to newspaper opinion articles; and (ii) online reviews of movies, books and consumer products. We propose a taxonomy of linguistic resources that are deployed in the expression of negativity, with two broad groups at the top level of the taxonomy: resources from the lexicogrammar or from discourse semantics. We propose that rhetorical figures can be considered part of the discourse semantic resources used in the expression of negativity. Using our taxonomy as starting point, we carry out a corpus analysis, and focus on three phenomena: adverb + adjective combinations; rhetorical questions; and rhetorical figures. Although the analysis in this paper is corpus-assisted rather than corpus-driven, the final goal of our research is to make it quantitative, in extracting patterns and resources that can be detected automatically

Fracture surface characterization of epoxy-based GFRP laminates

Fractographic investigation has been carried out on glass fabric-epoxy composite laminates using scanning electron microscopy. Focusing on the flexural failure of lap shear specimens, some unique fracture features have been identified, and their likely origin suggested and explained. The influence of voids, present in the matrix, on the appearance of the fracture surface has been illustrated.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44706/1/10853_2004_Article_BF00576775.pd

Fracture behaviour of unmodified and rubber-modified epoxies under hydrostatic pressure

The fracture toughness and uniaxial tensile yield strengths of unmodified and CTBN-rubber-modified epoxies were measured under hydrostatic pressure. The purpose of these experiments was to learn how suppressing cavitation in rubber particles affects the deformation mechanisms and the fracture toughness of rubber-modified epoxy. It was found that the cavitation of CTBN-rubber could be suppressed at a relatively low pressure (between 30 and 38 M Pa). With cavitation suppressed, the rubber particles are unable to induce massive shearyielding in the epoxy matrix, and the fracture toughness of the rubber-modified epoxy is no higher than that of the unmodified epoxy in the pressure range studied. Unmodified epoxy shows a brittle-to-ductile transition in fracture toughness test. The reason for this transition is the postponement of the cracking process by applied pressure.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44734/1/10853_2005_Article_BF01154701.pd