Book Review : Beyond criminology : taking harm seriously edited by Paddy Hillyard, Christina Pantazis, Steve Tombs and Dave Gordon (2004)

Hillyard et al.'s Beyond Criminology: Taking Crime Seriously is an innovative collection that attempts to take criminology beyond state definitions of crime to discourses involving harm, or what the editors refer to as ‘zemiology’, or what could be called ‘social harm theory’. The central theme of the book is that ‘it makes no sense to separate out harms, which can be defined as criminal, from all other types of harm’ (p. 2). At long last, ‘harm’ is discussed with the theoretical and practical integrity it deserves as an academic and intellectual narrative. For too long it has been ignored or omitted from the criminological lexicon. This book ensures that it captures centre stage within analyses that refocus the agenda to deleterious acts not always covered by the state legislature...

Beyond here-and-now : extending shared physical experiences to shared conceptual experiences

For robots to use language effectively, they need to refer to combinations of existing concepts, as well as concepts that have been directly experienced. In this paper, we introduce the term generative grounding to refer to the establishment of shared meaning for concepts referred to using relational terms. We investigated a spatial domain, which is both experienced and constructed using mobile robots with cognitive maps. The robots, called Lingodroids, established lexicons for locations, distances, and directions through structured conversations called where-are-we, how-far, what-direction, and where-is-there conversations. Distributed concept construction methods were used to create flexible concepts, based on a data structure called a distributed lexicon table. The lexicon was extended from words for locations, termed toponyms, to words for the relational terms of distances and directions. New toponyms were then learned using these relational operators. Effective grounding was tested by using the new toponyms as targets for go-to games, in which the robots independently navigated to named locations. The studies demonstrate how meanings can be extended from grounding in shared physical experiences to grounding in constructed cognitive experiences, giving the robots a language that refers to their direct experiences, and to constructed worlds that are beyond the here-and-now.

Learning domain-specific sentiment lexicons for predicting product sales

Generic sentiment lexicons have been widely used for sentiment analysis these days. However, manually constructing sentiment lexicons is very time-consuming and it may not be feasible for certain application domains where annotation expertise is not available. One contribution of this paper is the development of a statistical learning based computational method for the automatic construction of domain-specific sentiment lexicons to enhance cross-domain sentiment analysis. Our initial experiments show that the proposed methodology can automatically generate domain-specific sentiment lexicons which contribute to improve the effectiveness of opinion retrieval at the document level. Another contribution of our work is that we show the feasibility of applying the sentiment metric derived based on the automatically constructed sentiment lexicons to predict product sales of certain product categories. Our research contributes to the development of more effective sentiment analysis system to extract business intelligence from numerous opinionated expressions posted to the Web

Jabberwocky : the complexities of mathematical English

Mathematical English is a unique language based on ordinary English, with the addition of highly stylised formal symbol systems. Some words have a redefined status. Mathematical English has its own lexicon, syntax, semantics and literature. It is more difficult to understand than ordinary English. Ability in basic interpersonal communication does not necessarily result in proficiency in the use of mathematical English. The complex nature of mathematical English may impact upon the ability of students to succeed in mathematical and numeracy assessment. This article presents a review of the literature about the complexities of mathematical English. It includes examples of more than fifty language features that have been shown to add to the challenge of interpreting mathematical texts. Awareness of the complexities of mathematical English is an essential skill needed by mathematics teachers when teaching and when designing assessment tasks.

Lingodroids : learning terms for time

For humans and robots to communicate using natural language it is necessary for the robots to develop concepts and associated terms that correspond to the human use of words. Time and space are foundational concepts in human language, and to develop a set of words that correspond to human notions of time and space, it is necessary to take into account the way that they are used in natural human conversations, where terms and phrases such as `soon', `in a while', or `near' are often used. We present language learning robots called Lingodroids that can learn and use simple terms for time and space. In previous work, the Lingodroids were able to learn terms for space. In this work we extend their abilities by adding temporal variables which allow them to learn terms for time. The robots build their own maps of the world and interact socially to form a shared lexicon for location and duration terms. The robots successfully use the shared lexicons to communicate places and times to meet again.

Alcohol consumption in young adults : the role of multisensory imagery

Little is known about the subjective experience of alcohol desire and craving in young people. Descriptions of alcohol urges continue to be extensively used in the everyday lexicon of young, non-dependent drinkers. Elaborated Intrusion (EI) Theory contends that imagery is central to craving and desires, and predicts that alcohol-related imagery will be associated with greater frequency and amount of drinking. This study involved 1,535 age stratified 18–25 year olds who completed an alcohol–related survey that included the Imagery scale of the Alcohol Craving Experience (ACE) questionnaire. Imagery items predicted 12-16% of the variance in concurrent alcohol consumption. Higher total Imagery subscale scores were linearly associated with greater drinking frequency and lower self-efficacy for moderate drinking. Interference with alcohol imagery may have promise as a preventive or early intervention target in young people.

Teachers as researchers : a ‘fair dinkum’ learning legacy

As we encounter a policy landscape where increasingly the education lexicon includes keywords such as data, evidence, quality, standards, it is interesting to revisit Garth Boomer's contribution regarding teachers as researchers. As an early-career classroom teacher in the mid-1970s, I was inspired by Boomer's provocation to engage with research as a practitioner seeking evidence of learning (or not learning). Since that time, convinced of the power of teacher research in enhancing both student and teacher learning, I have devoted a good deal of my academic life to finding ways of supporting teachers to engage in research - from finding funds to facilitate teacher-researcher networks, through designing research projects with teacher-researchers as key collaborators, to embedding practitioner inquiry in university courses wherever possible pre- and in-service.

Automated species recognition in environmental recordings

Faunal vocalisations are vital indicators for environmental change and faunal vocalisation analysis can provide information for answering ecological questions. Therefore, automated species recognition in environmental recordings has become a critical research area. This thesis presents an automated species recognition approach named Timed and Probabilistic Automata. A small lexicon for describing animal calls is defined, six algorithms for acoustic component detection are developed, and a series of species recognisers are built and evaluated.The presented automated species recognition approach yields significant improvement on the analysis performance over a real world dataset, and may be transferred to commercial software in the future.

Efficiency of lexical access in children with autism spectrum disorders : does modality matter?

The provision of visual support to individuals with an autism spectrum disorder (ASD) is widely recommended. We explored one mechanism underlying the use of visual supports: efficiency of language processing. Two groups of children, one with and one without an ASD, participated. The groups had comparable oral and written language skills and nonverbal cognitive abilities. In two semantic priming experiments, prime modality and prime–target relatedness were manipulated. Response time and accuracy of lexical decisions on the spoken word targets were measured. In the first uni-modal experiment, both groups demonstrated significant priming effects. In the second experiment which was cross-modal, no effect for relatedness or group was found. This result is considered in the light of the attentional capacity required for access to the lexicon via written stimuli within the developing semantic system. These preliminary findings are also considered with respect to the use of visual support for children with ASD.

Predicting sense convergence with distributional semantics : an application to the CogALex-IV 2014 shared task

This paper presents our system to address the CogALex-IV 2014 shared task of identifying a single word most semantically related to a group of 5 words (queries). Our system uses an implementation of a neural language model and identifies the answer word by finding the most semantically similar word representation to the sum of the query representations. It is a fully unsupervised system which learns on around 20% of the UkWaC corpus. It correctly identifies 85 exact correct targets out of 2,000 queries, 285 approximate targets in lists of 5 suggestions.

Teaching persuasive texts : building a language of evaluation through hedging and moderated intensification

We identify two persuasive writing techniques – hedging and intensification – that pose difficulty for students in the middle years. We use examples of student writing from 3000 work samples collected as part of a larger Australian Research Council Linkage Project, URLearning (2009–2013). To realise the effective power of rhetorical persuasion, students need to be explicitly taught a range of hedging techniques to use to their advantage, and an expanded lexicon that does not rely on intensifiers. Practical teaching tips are provided for teachers.

Analysing children’s persuasive texts : the use of hedging and intensification

Research Quality This is a dialogue between two Australian literacy scholars about two persuasive writing techniques that posed difficulty for the students in our research. This dialogue flows from the analysis of Year 6 writing samples from an ARC Linkage Project, URLearning (2009-2013) - the focus of the symposium. We use vivid examples of writing from students’ handwritten persuasive texts on topics that were chosen by teachers. The persuasive structure in the texts followed the Toulmin (2003) model: a thesis statement, three arguments with evidence, and a conclusion. The findings show that to realise the effective power of rhetorical persuasion, students need an expanded lexicon that does not rely on intensifiers, and which employs a greater range of advanced hedging techniques to use to their advantage. National & International Importance The study is potentially of national and international relevance, given that argumentation or persuasion is a key life skill in many professional, personal, and discourses. It is also a requirement in the International English Language Testing Systems (IELTS) tests, which are a critical gateway for tertiary studies in many English-speaking countries (Coffin, 2004). Timeliness The research is timely given the Australian Curriculum English, in which persuasive texts figure prominently from Preparatory to Year 10 (ACARA, 2014). The recommendations are also timely in the context of educational policies in other parts of the world. For example, in the United States, the Common Core Standards: English Language Arts, mandates the teaching of persuasive texts (Council of Chief State School Officers & National Governors Association, 2013) Implications for practice/policy The findings of the study have specific practical implications for teachers, who can address the persuasive writing techniques of hedging and intensification with which children need targeted support and explicit instruction. The presentation is positioned at the nexus of teacher practice to better address the national priorities of the Australian Curriculum: English (ACARA, 2014), while having implications for applied linguistics research by identifying common problems in students' persuasive writing.

Estimating second language productive vocabulary size: A Capture-Recapture approach

This study provides validity evidence for the Capture-Recapture (CR) method, borrowed from ecology, as a measure of second language (L2) productive vocabulary size (PVS). Two separate “captures” of productive vocabulary were taken using written word association tasks (WAT). At Time 1, 47 bilinguals provided at least 4 associates to each of 30 high-frequency stimulus words in English, their first language (L1), and in French, their L2. A few days later (Time 2), this procedure was repeated with a different set of stimulus words in each language. Since the WAT was used, both Lex30 and CR PVS scores were calculated in each language. Participants also completed an animacy judgment task assessing the speed and efficiency of lexical access. Results indicated that, in both languages, CR and Lex30 scores were significantly positively correlated (evidence of convergent validity). CR scores were also significantly larger in the L1, and correlated significantly with the speed of lexical access in the L2 (evidence of construct validity). These results point to the validity of the technique for estimating relative L2 PVS. However, CR scores are not a direct indication of absolute vocabulary size. A discussion of the method’s underlying assumptions and their implications for interpretation are provided.

Are you on board? The role of design-led innovation in strengthening key partnerships within an Australian airport

A popular lexicon for announcing partnerships within aviation is being ‘on-board’. Like boarding a plane, business partnerships requires trust in the expertise and the philosophy of another organisation. This paper reports upon the process and findings from the completion of a customer engagement project within a leading Australian Airport, as part of the wider uptake of design-led innovation. The project was completed bilaterally with Airport Corporation and prominent retail business partner undertaking a design-led approach to collaboratively explore an observed market trend affecting the performance of both businesses. A design-led catalyst facilitated the completion of this project, working within the Airport Corporation to disseminate the skills and philosophy of design over an 18 month period using an action research method. Findings reveal that the working environment necessary for design to be utilised requires; trust in the design-led approach as a new and exploratory way of completing work; leadership within the execution and delivery of project deliverables, and; a shared intrinsic motivation to develop new skills through a design-led approach which challenges a business-as-usual mentality (BAU). Design-led innovation can be deployed specifically to strengthen business partnerships through collaborative and explorative customer engagement.

Deriving word association networks from text corpora

This article presents and evaluates a model to automatically derive word association networks from text corpora. Two aspects were evaluated: To what degree can corpus-based word association networks (CANs) approximate human word association networks with respect to (1) their ability to quantitatively predict word associations and (2) their structural network characteristics. Word association networks are the basis of the human mental lexicon. However, extracting such networks from human subjects is laborious, time consuming and thus necessarily limited in relation to the breadth of human vocabulary. Automatic derivation of word associations from text corpora would address these limitations. In both evaluations corpus-based processing provided vector representations for words. These representations were then employed to derive CANs using two measures: (1) the well known cosine metric, which is a symmetric measure, and (2) a new asymmetric measure computed from orthogonal vector projections. For both evaluations, the full set of 4068 free association networks (FANs) from the University of South Florida word association norms were used as baseline human data. Two corpus based models were benchmarked for comparison: a latent topic model and latent semantic analysis (LSA). We observed that CANs constructed using the asymmetric measure were slightly less effective than the topic model in quantitatively predicting free associates, and slightly better than LSA. The structural networks analysis revealed that CANs do approximate the FANs to an encouraging degree.