Choose your prompt carefully!

The need for fair and non-toxic generative artificial intelligence (GenAI) models is reflected in global regulation changes, algorithmic developments, debiasing techniques and prompt engineering. This paper aims to highlight the inconsistencies in GenAI text outputs and focus on template-based prompts as an example to provide evidence that prompt design choices also influence a non-toxic output. We utilise occupation and respect-related prompt templates with past and present tenses to develop prompts for a multicultural society. We analyse the text outputs from the curated prompts of several GenAI models, averaging across all demographic groups, to show that even changes in past vs present tense can result in toxic outputs. The next stage of this research is focusing on the impact of demographic groups on harmful outputs

Unpacking media narratives: Racism and problematic reasonings

In this research brief, we present summaries of four case studies of racism in mainstream and social media in Aotearoa. Through a series of carefully selected datasets sourced from TV episodes (Police TEN 7), print media such as news articles (including Northland checkpoints), and tweets (Three Waters reform), we outline how Māori are represented across these mediums. With an expert in language modelling on our team, we analysed large datasets that give us sufficient statistical power to infer specific Māori discourses on respective platforms. Further, we examined key themes that characterise how Māori are represented in the media and signal the scale of anti-Māori attacks. For instance, we found that the predominant discussion on Three Waters reform on Twitter focused on ‘conflict’ (distrust towards government; 33%) and ‘capability’ (questioning the credibility of the reform; 23%) rather than its core intention of promoting water ‘safety’ (7%). The modelling analysis was supplemented by in-depth qualitative analysis that integrates anti-Māori themes (Moewaka-Barnes et al., 2012) and problematic reasoning tactics (Sturgill, 2021) to elucidate how false, deficit-based rhetoric about Māori is deployed to fuel racism and disinformation. In summary, our findings reinforce Kupu Taea’s call for new media sectors to integrate Te Tiriti o Waitangi into their practices to safeguard Māori and other minoritised groups who are likely to be at the fore of racist attacks

Why standardised assessment doesn’t measure up?

Panel discussion with Dr Marta Estellés, Dr Jade Wrathall, and Lynda Stuart about the moves the Government is making to bring in standardised testing in schools. The Ministry of Education has issued a tender to purchase a standardised assessment tool for children between Year 3 and 10. We discuss why this policy introduced by stealth is so concerning. Drawing on national and international evidence, we will reflect on the implications of standardised assessment. You will learn why this new policy doesn’t measure up and it is no more than a reboot of National Standards

The Economic Contribution of Religious Charities to New Zealand.

This article considers religious charities from an original perspective, that of their economic contributions to society as an alternative argument to those who wish to see religious charities struck from the charity sector. This is timely because of recent national and international changes to charity law legislation and policies. In essence, the article has demonstrated that religious charities contribute significantly in economic terms to New Zealand society generally, and further, measuring the public benefit of religious charities through an economic lens may assist in determining the differing ways in which religious charities contribute to, and benefit, society

Looking back to look forward to the female gaze: An analysis on the foundational filmmakers and their female protagonists.

This thesis examines theories of the female gaze through recognizing the foundational filmmakers and screenwriters who have explored varying female experiences throughout cinema history. Theories of the gaze stemmed from Laura Mulvey’s fundamental 1975 essay, from which her argument posited that mainstream Hollywood cinema constructs male centred subjects who control the gaze of the narrative, whilst female characters are depicted as objects who cater to the desires of the male spectator. Since then, theorists and scholars have explored ideas of a female gaze from which female-centred narratives are explored by filmmakers. Such narratives are explored by female protagonists who control the gaze through techniques crafted by directors and/or screenwriters, reflecting key ideologies and issues that resonate with the female spectator. This research aims to discover how theories of the female gaze have been reconstructed throughout cinema history by female directors and/or screenwriters through the representation of their female protagonists. Through conducting comparative text analysis, this thesis analysed two films within four key periods in cinema including; the French New Wave, New Hollywood Cinema, the Blockbuster Age, and contemporary Independent Cinema, to explore a range of innovative and nuanced female protagonists who have represented various female experiences on screen. This analysis showcases the long-standing history of theories surrounding the female gaze, and identifies the socio-cultural contexts that influenced the reconstruction of the gaze by filmmakers across time and space. The results of this research highlights the different interpretations of the female gaze by key filmmakers and/or screenwriters, illustrates similarities and disparities between protagonists by filmmakers during similar periods, and reveals the importance of socio-cultural contexts that underpin various representations of female experiences throughout cinema history

Improving finite sample estimates of principal components

Principal Component Analysis (PCA) is a method of compressing high-dimensional data into a lower-dimensional format that captures the essence of the original structure. PCA is a matrix decomposition technique based on eigen decomposition. It quantifies relationships between variables using covariance matrices, captures the shape of the data distribution, and evaluates the importance of directions using eigenvalues. Therefore, the accuracy of the variance-covariance estimation is crucial for reliable PCA. In high-dimensional settings where the number of observations (n) is much smaller than the number of variables (p) (i.e., n << p), the conventional Maximum Likelihood Estimator (MLE) of covariance becomes poorly conditioned and yields unreliable principal components. To address these limitations, we propose a novel estimation framework called Pairwise Differences Covariance (PDC), along with four regularized extensions: Standardized PDC (SPDC), Local Scaled PDC (LSPDC), Maximum Absolute Scaled PDC (MAXPDC), and Range Scaled PDC (RPDC). These estimators increase the effective sample size by utilizing all pairwise differences within the data, thereby enhancing estimation stability without requiring additional data collection. Extensive experiments on synthetic and real datasets demonstrate that the proposed estimators, particularly SPDC, significantly reduce the over-dispersion of the first principal component and improve directional accuracy. On average, SPDC reduced cosine similarity error by approximately 10–30% and narrowed eigenvalue spread by 10–20% compared to MLE and Ledoit-Wolf estimators in n << p HDLSS scenarios. Real-world applications confirm the practical utility and robustness of these methods for analyzing high-dimensional data

Exploring the impact of rainfall intensity on the attenuation-rainfall relationship

The attenuation of electromagnetic waves due to rainfall is a critical factor in radar and telecommunication systems, particularly in frequency bands above 10 GHz, which is increasingly utilised for data transfer. This study addresses the gaps in understanding how these attenuation effects vary across different rainfall intensities and Drop Size Distributions (DSD). By analytically investigating the irregularities in the cross-sections of raindrops within the 1 to 30 GHz frequency range, the study mentions significant peaks in attenuation at frequencies below 10 GHz, which are more pronounced as DSD changes with rainfall intensity. Using the extinction and efficiency cross-sections of raindrops in 1–30 GHz microwave transmission, the coefficients of rainfall-attenuation correlation were derived for each sector of rainfall intensity of 1–300 mm/hr. Building on these findings, we propose an enhanced rainfall-attenuation relationship, incorporating dynamic coefficients, varying with both factors, DSD and rainfall intensity. Unlike previous models that only suggest calibration of the attenuation-rainfall relationship with DSD, our results indicate that the coefficients should also dynamically adjust based on rainfall intensity. We further demonstrate how these varying coefficients differ from the ITU's recommendations, providing detailed graphical comparisons. This advancement allows for more accurate calculations of rainfall intensity, improving the precision of telecommunication and radar systems in diverse weather conditions

An efficient process to designing robotic end effectors for high value crops: Application on robotic apple fruitlet thinning

High value crops continue to rely extensively on manual labour for labour intensive and expensive tasks like harvesting and thinning. Robotics is increasingly being investigated as a solution to combat labour shortages which threaten the sustainability and growth of the horticultural sector. However, the seasonal nature of high value crops offers only a short window of a few weeks to field tests one robotic end effector per season using the conventional process. This hinders the research and development timeline of robotic end effectors. This thesis presents an efficient design process, modified from existing design methods, to overcome this limitation by capitalising the remainder of the off-season window within a year, and thus reduces the robotic end effector development time. The efficient design process starts with co-design workshops involving growers and field visits to gather requirements, understand crop physiology, and determine the specific needs for identified crop management tasks. This information guides the development of several end effector concepts. Concepts with feasible potential are selected to progress to the prototype stage, which then undergo laboratory testing and comparative evaluations during off-season. The off-season investigation can only be possible by creation of an artificial crop structure that replicates the crop's physiology and is capable of testing the prototype's core mechanism principles repetitively. This structure is also optimised with enhancements and design optimisation of the end effectors, such that field testing time can be maximised to address issue unique to field conditions. This process then allows for extensive testing of various end effectors within a single year, significantly reducing the development duration. The process prioritises the generation of multiple viable end effector concepts while integrating feedback from growers. The efficient design process was implemented to develop robotic end effectors for apple fruitlet thinning. The design requirements for thinning fruitlets to 1 or 2 fruitlets from a cluster were identified after consultation with growers and a visit to the apple orchard. Nine concepts were generated and preliminarily tested in the field and consulted with growers. Four distinct concepts were then selected: 1) cutting that cuts the stalk, 2) suction based on grasping and rotating, 3) paraboloid based on grasping and rolling, and 4) piercing end effector based on spear piercing and rotate. These concepts were further developed into fully functional end effectors for laboratory evaluation, enabled by the development of an artificial structure that allows interchangeable fruitlets of all sizes and accommodating repetitive testing of the end effectors core mechanism principles. After an iterative process of testing, optimisation, and modifications of end effectors and artificial fruitlet structures, a comparative evaluation was performed to benchmark and quantify the capability of each end effector was conducted. A computer vision system and path planning systems were developed and integrated with the end effectors to facilitate this evaluation. This shows that the vacuum suction end effector consistently reached a 100\% success rate from 90° pitch angle on single fruitlets, and also maintained this success rate at a 90° pitch angle in a fruitlet cluster in all positions, followed by cutting and paraboloid with 80\% success rate on a single fruitlet. In contrast, the spear piercing mechanism consistently under performed and was excluded from the field testing. The field test in apple orchards under real world conditions indicated that the suction end effector achieved the highest success rate, reaching 70\%, followed by cutting end effector with 44\% and paraboloid with 26\%, showing trends consistent with lab evaluations. The primary causes of failure are positioning errors and occlusion. Thus, the efficient design process developed the suitable suction end effector to be integrated with the overall robotic platform for further development within a single year, compared to a minimum of two years using a conventional process

Applying the perceived creepiness of technology scale to social robots

Designing positive robot experiences requires an understanding of users' perceptions and meeting their needs in an ethical manner. However, despite best intentions, users have strong positive or negative reactions to robots, either finding them ''cute'' or ''creepy''. The Perceived Creepiness of Technology Scale (PCTS) was designed for evaluating how creepy a technology appears to a user on first encounter. In this paper we applied the PCTS to a cross-section of social robots to measure their perceived creepiness and evaluate the strengths and weaknesses of PCTS when applied in a Human-Robot Interaction (HRI) context. We demonstrate that while a robot may not be perceived as creepy initially, it can have underlying unethical practices inherent in its design which is not well captured by the PCTS. This emphasises the need for better HRI practices to ensure creepiness is appropriately assessed in the social robot domain

Examining neuroplasticity as a function of errors during motor learning

Proficient motor learning is important for both athletes looking to improve their performance and patients learning daily living skills. Research has identified different methods for learning motor skills, focusing on two types: implicit and explicit learning. Implicit learning happens with little awareness, while explicit learning requires more conscious thought. Studies show that implicit learning is often more effective because it uses less mental effort and is more reliable under stress. This might be due to stronger neural connections in the brain formed during implicit learning. However, it is unclear whether implicit learning leads to more brain changes, known as neuroplasticity, than explicit learning. Neuroplasticity is the brain's ability to adapt and form new memory networks in response to experiences. This study aims to investigate differences in neuroplastic changes resulting from implicit versus explicit learning of a traditional Dutch shuffleboard game (Sjoelbak). We used baseline electroencephalography (EEG) to measure changes in brain activity before and after practice to assess neuroplasticity. We examined the effects of errorless and errorful learning protocols on task performance and neural connectivity. Both strategies improved accuracy from pretest to posttest, indicating effective skill acquisition. However, participants struggled to transfer skills to new contexts, as shown by decreased performance in the transfer test. Despite expectations of greater neuroplastic changes as a function of errorless learning, resting-state beta connectivity analyses showed no significant interactions. However, no significant differences were evident in the overall error rates between the groups during the learning phase, suggesting that implicit motor learning may not have occurred for the errorless learning condition. This suggests that neural adaptations are more complex than initially hypothesized