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Civility and Environmental Politics
No full textIn this article, we offer a normative analysis of environmental politics through the lens of civility. First, we explain what civility is by identifying its three key dimensions: civility as politeness, moral civility and justificatory civility. We then examine various instances of environmental politics and activism through the lens of civility, by focusing on the complex intersections between its three dimensions as well as the hierarchical relationship that exists between them, with moral civility taking precedence over justificatory civility and the latter over civility as politeness. This analysis, we argue, can help us to formulate more nuanced judgements about the desirability of different instances of civil and uncivil environmental politics and activism, and to develop educational strategies for preparing policymakers, environmental activists and citizens more generally to be civil participants in environmental politics.</p
Consulting the experts:young people's experiences of a school-based mental health literacy program
No full textObjective: The prevalence of mental health problems among youth is high, and help seeking behaviour is low. Mental health literacy (MHL) has been suggested as a factor to enhance mental health knowledge and increase help seeking and coping behaviours. Schools have been recognised as an ideal environment for MHL programs to be delivered to reach a wide range of youth. This study aimed to understand the perspectives and experiences of secondary school students after participating in a MHL program, and how findings aligned with the theoretical model the program is based on. Method: Thirty-eight participants aged 12–16 years provided feedback through an open-ended questionnaire. The questionnaire comprised seven items to gather participants’ experiences and perspectives on the MHL program, including usefulness, ideas for program improvement, impact, and coping strategies. This study was preregistered on the Australian New Zealand Clinical Trials Registry, Registration Number: ACTRN12621000325808. Results: Reflexive thematic analysis generated three themes and three subthemes from the findings: 1) A safe environment, 2) Perceived positive impact, 2.1) Attitudes towards mental health, 2.2) Coping strategies, 2.3) Need for MHL, and 3) Suggestions for program improvement. Conclusions: These findings indicate that the school-based program meets the current MHL needs of young people, aligns with the MHL Child Focused theoretical model, and was viewed as beneficial to be incorporated into the education system in future.</p
A dual-image fusion instance segmentation model for pavement patch detection
No full textAccurate patch detection is essential for reliable pavement condition evaluation and life cycle assessment. However, this task remains challenging due to variations in patch morphology, visual similarity to the background, and the limited availability of comprehensive patch datasets. This paper presents a novel patch detection method that pioneers the use of instance segmentation techniques to obtain more detailed patch information and fuses dual-image data from the Laser Crack Measurement System (LCMS) to capture richer features for enhanced precision. Furthermore, the proposed method goes beyond conventional approaches that focus solely on basic detection by incorporating a patch counting method, enabling accurate patch quantification and area measurement across different road section lengths. Experimental results show that the proposed patch detection model (FuPatch) outperforms baseline models while maintaining comparable efficiency. Additionally, the patch counting method effectively quantifies both the number and area of patches. These findings demonstrate that the developed model not only effectively detects patches but also provides detailed spatial insights and performs accurate patch counting, making it highly applicable for real-world pavement condition assessments.</p
Academic capitalism and precarity in the neoliberal university:job insecurity and stress in two liberal market economies
No full textThis study analyses the relationship between academic capitalism and employment precarity. Drawing on two cross-national sources of survey data, we compare academics' experiences with job insecurity and related stress in Australian and Canadian universities during the COVID-19 pandemic. Although these two countries are similar liberal market economies, Australian higher education has embraced academic capitalism to a greater extent than in Canada. Against this backdrop, our study focuses on the moderating role of ‘soft income’ from international tuition fees and the use of contingent labour in explaining cross-country differences. We find that international tuition played a role in heightening job insecurity and associated stress, particularly in the Australian universities due to their greater reliance on this source of income. However, these outcomes converged for ‘permanent’ and ‘casual’ academics in Australia but diverged in Canada. We contend that the cross-national differentiation is likely due to the weaker job protections afforded to permanent academics in Australia.</p
Investor reactions to climate change disclosures:joint effects of disclosure focus and controllability
No full textWhen evaluating the potential financial effects of climate change, investors demand disclosures of the climate-related risks and opportunities that companies need to manage. We examine how and why management control over climate change performance affects investors' evaluations of such disclosures. In a series of experiments, we find that investors believe that managerial optimism is beneficial and, thus, are more willing to invest when climate-related disclosures focus on opportunities rather than risks. This effect, however, occurs only when management has high control over the company's future climate change performance. When that control is low, investors believe that managerial realism is beneficial and, thus, are more willing to invest when these disclosures focus on risks rather than opportunities. Our study has implications for companies and standard setters considering the consequences of focusing on either risks or opportunities in climate change reporting and the conditions under which one focus or the other may be beneficial.</p
Language diversity and teaching practices:Japanese high school teachers of English
No full textIn Japan, as in many Asian countries, English is still widely taught in schools in standardised forms that are attributed to ‘native speakers’. However, scholarship on linguistic diversity is well-established in the field of Teaching English to Speakers of Other Languages (TESOL), and teachers’ conceptualisation of language can influence their teaching in different ways. In this article we discuss the relationship between six Japanese high school teachers’ understanding of English and their reported teaching practices. Data collected via individual interviews and email exchanges were analysed, and the findings revealed various conceptualisations of language diversity, ranging from a focus on Inner Circle varieties to World Englishes, English as a ‘tool’ for communication, and translanguaging. These ways of thinking about language were found to align with different kinds of reported classroom activities.</p
Acoustic-to-hyper-spectral:real-time perimeter intrusion detection system monitoring through learnable filters and hyper-spectral image generation from distributed acoustic sensing systems
No full textThis paper presents an integrated distributed acoustic sensing (DAS) system with artificial intelligence to provide real-time system monitoring for fence perimeter and buried system applications. The DAS system is a Rayleigh backscatter based fibre optic sensing system that has been deployed in two real-world, commercial applications to detect acoustic wave propagation and scattering along perimeter lines, and classify intrusions accurately. What we believe to be three novel signal processing methods are proposed to train filters for automatically selecting frequency bands from the power spectrum and generating hyper-spectral images from the data gathered by the DAS system without expert knowledge. The hyper-spectral images are analyzed by a neural network based object detection model. The system achieves 81.8% accuracy on a fence perimeter installation and 60.4% accuracy on a buried system application in detecting and classifying various intrusion events. The evaluation interval of the integrated DAS system framework between event sensing and detection does not exceed 5 s.</p
ShareFlows:Seamless Knowledge Capture and Proactive Push for Efficient Teacher Workflows in Higher Education
No full textHigh staff turnover in higher education often burdens teachers with laborious handovers of teaching tasks every semester. To boost teachers' workflow efficiency, we present an innovative knowledge management tool that allows experienced teachers to seamlessly capture task steps (i.e., denoted as ShareFlow) that can be subsequently recommended to novices via proactive push, all happening during teachers' natural workflow to minimize disruptions. We conducted a controlled experiment with 30 participants and compared our tool against a state-of-the-art baseline knowledge management system powered by a large language model (Claude 3 Haiku). We found that our knowledge management tool reduced task completion time and improved task quality (with statistical significance). Feedback from the participants also indicated the high usability of our tool, suggesting its strong potential for practical adoption for improving teacher workflows.</p
Stirring young children into friendships:constraints and enablers during the transition to an international school
No full textFriendship provides space for young children (aged 5 years) to develop their emotion regulation, social skills and a sense of belonging, all foundational dimensions for learning about how social relations work. To further understand the significance of friendship for young children from global middle-class families who frequently transition countries, we use friendship as a lens and draw on the Theory of Practice Architectures to explore practices that shape and are shaped by their context. Kemmis et al. argues there is a need to focus on the interaction between cultural-discursive (sayings), material-economic (doings) and social-political (relatings) dimensions of practice. Through narratives that provide a glimpse into, two children, two parents’ and two teachers’ perspectives, we analyse practices that enable and/or constrain young children transitioning into a new country and school, with a focus on how friendship is initiated. Findings indicate that there are clear differences in the way children and adults understand friendship. Children show active engagement initiating their own friendship, whereas teachers encourage children to play with everyone and mothers’ privilege close sibling bonds and reminisce about children’s past friendships.</p
Co-Manifold learning for semi-supervised medical image segmentation
No full textIn this study, we investigate jointly learning Hyperbolic and Euclidean space representations and match the consistency for semi-supervised medical image segmentation. We argue that for complex medical volumetric data, hyperbolic spaces are beneficial to model data inductive biases. We propose an approach incorporating the two geometries to co-train a variational encoder–decoder model with a Hyperbolic probabilistic latent space and a separate variational encoder–decoder model with a Euclidean probabilistic latent space with complementary representations, thereby bridging the gap of co-training across manifolds (Co-Manifold learning) in a principled manner. To capture complementary information and hierarchical relationships, we propose a Latent Space Loss aimed at maximizing disagreement between embeddings across manifolds. Additionally, we employ adversarial learning to enhance segmentation performance by guiding the network in hyperbolic latent space using confident regions identified by the network in Euclidean space. Conversely, the network in Euclidean space is informed by hyperbolic uncertainty, creating a dual uncertainty-aware framework that enables the two spaces to collaboratively learn confident regions from each other. Our proposed method achieves competitive results on two benchmarks for semi-supervised medical image segmentation on medical scans. The code is publicly available at: https://github.com/himashi92/Co-Manifold.</p