Measuring children’s metalinguistic awareness

Research into young learners’ metalinguistic awareness has led to both definitions of the construct and key findings about its role in children’s cognitive and linguistic development. I briefly summarise this research before introducing two established theoretical models that can help us understand the concept of metalinguistic awareness more broadly: E. Bialystok’s classic dichotomy of analysis of knowledge and control of processing, and R. Ellis’ notion of explicit (second language) knowledge. This is followed by an overview of measures of metalinguistic awareness that have been used in empirical studies to date as well as an illustration and critique of selected measures. As a result, I propose a model which combines features of the two previous frameworks by conceptualising knowledge representations and processes in terms of (1) how implicit/explicit and (2) how specific/schematic they are. I explain this model to illustrate how it can serve as a useful thinking tool. In particular, I argue that the model not only allows us to theorise measures of metalinguistic awareness more clearly and easily, but that it can also capture tasks aimed at assessing other linguistic and cognitive abilities. The paper concludes with a brief outlook on future research into metalinguistic awareness

The 'phantasy sibling transference': only-child adults and finding a 'position' in the therapeutic setting.

This study originated from my experience of an unusual transference with my only-child adult patients and in my own psychotherapy. I wanted to explore the idea that only-child adults may create a transference in the therapeutic setting which mimics a sibling transference. Juliet Mitchell provides a valuable framework in which to understand the intersecting and yet distinct lateral and vertical dimensions of psychic life suggesting that on the arrival of a sibling, the infant is thrown into disarray and must negotiate a new position both with the parents and within the sibling group. This propels the infant into a complex and fraught challenge around the issue of identity which, according to Jeanine Vivona, can only be resolved through the gaining of validation and recognition on the lateral dimension with siblings, enabling the infant to know who they are and where they stand in the sibling group. This is later reflected in the world of peers. I suggest the only-child adult, having missed out on these psychological challenges in relation to siblings, is left without a ‘position’ and without an identity in the lateral world. This research attempts to investigate this potential phenomenon through the interviewing of psychoanalytic and psychodynamic psychotherapists who have worked with only-child adult patients. Analysing the data through reflective thematic analysis and developing themes from their countertransference, the results suggest the only-child adult does enact a ‘phantasy sibling transference’. Finally, understanding the inner world of the only-child adult may enable an attempt at resolution of this sibling conflict within the therapeutic setting with the discovery of the only-child adult’s identity on the lateral dimension

Methods that make us feel safer? Challenging the effect of sexism confrontation and holding measures of violence against women up to scrutiny

This thesis critically evaluates key claims in sexism and violence against women research, addressing the question: ‘Are past research methods and measures painting a distorted picture of sexism and its manifestations that uphold violence against women?’ This is timely, considering the need for a more robust evidence base post-replication crisis and rising backlash against gender equality, particularly among younger men. We explore three potentially misleading claims: that challenging sexism mitigates its negative outcomes; that women’s fear of crime is generally unfounded; that rape myth acceptance is declining. In Chapter 2, in three experimental studies, we examine whether challenging sexism mitigates its negative outcomes. By correcting methodological flaws in previous studies, such as the lack of a non-sexist control and failure to control for baseline sexism, we found that the supposed benefits of challenging sexism disappear. Chapter 3 examines the gender-fear ‘paradox’, which suggests that women's fears of victimisation are disproportionate to their risk, demonstrated in crime statistics. The study reveals that women significantly restrict behaviours more than men to avoid victimisation, indicating that crime statistics do not represent the true extent of the risks women face. Moreover, both men and women show low trust in police to report crimes. Chapter 4 challenges the narrative of declining rape myth acceptance. We argue that in using the term ‘rape’, these measures evoke archetypal rape scripts not representative of most cases. In two experimental studies, we replaced the word ‘rape’ with behaviour-specific descriptions, finding higher scores of rape myth acceptance and stronger correlations with victim-blaming and perpetrator exoneration, compared with the original scale. These findings suggest that societal attitudes may not be improving as previously thought, highlighting the need for more accurate measurement tools. This thesis underscores the necessity of refining research methodologies to inform effective policies and counteract the illusion that sexist and rape cultures are diminishing

Global data empires: Analysing artificial intelligence data annotation in China and the USA

As the two leading countries in the development of artificial intelligence (AI) systems, China and the United States largely rely on separate AI infrastructure and data annotation ecosystems. Studies have focussed almost exclusively on data annotation associated with American and European companies, limiting our understanding of how this contrasts with the Chinese development of AI. This article provides a comparative analysis of the political economy of the Chinese and American/European AI data annotation ecosystems, focusing on the role of the state and the practice of outsourcing to data annotation institutions. It finds that while the US state plays a protectionist role concerning AI infrastructure such as semiconductors and data centres, it adopts a laissez-faire approach to data annotation. The Chinese state, however, understands it has a comparative advantage in data and invests heavily in its own data ecosystem while maintaining stringent regulations for Chinese tech companies. Secondly, many US companies outsource data annotation work to business process outsourcing centres and digital platforms, whereas Chinese companies maintain these activities in-house or, through a process of ‘inland-sourcing’, send this work to ‘third-tier’ cities in Chinese provinces to data labelling bases, often jointly managed by local government and private companies

The Market Antinomy

The moral status of the modern market economy is contested amongst philosophers and social theorists. Some argue that it is a moral order; others argue that it is not a moral order. In Frankfurt School critical theory, the former argument is defended by Axel Honneth, and the latter by Jürgen Habermas and Joseph Heath. In this paper, I review the strengths and weaknesses of both arguments and suggest a novel way forward. I conceive of the contradictory arguments as thesis and antithesis of an antinomy akin to Kant’s antinomy of freedom and determinism in the Critique of Pure Reason. I argue that valuable insights can be gained by “remaining within” the space of the antinomy and considering it the result of a genuine contradictory experience: we do conceive the market economy as a moral order and as not a moral order, depending on the standpoint we take. However, in the final section of the paper, I argue that a resolution of the antinomy is possible, and that we must attend to people’s reactive attitudes to market processes and outcomes to find it

A Distributed Data-Driven and Machine Learning Method for High-Level Causal Analysis in Sustainable IoT Systems

A causal relationship forms when one event triggers another’s change or occurrence. Causality helps to understand connections among events, explain phenomena, and facilitate better decision-making. In IoT systems, massive consumption of energy may lead to specific types of air pollution. There are causal relationships among air pollutants. Analyzing their interactions allows for targeted adjustments in energy use, like shifting to cleaner energy and cutting high-emission sources. This reduces air pollution and boosts energy sustainability, aiding sustainable development. This paper introduces a distributed data-driven machine learning method for high-level causal analysis (DMHC), which extracts general and high-level Complex Event Processing (CEP) rules from unlabeled data. CEP rules can capture the interactions among events and represent the causal relation- ships among them. DMHC deploys a two-layer LSTM attention mechanism model and decision tree algorithm to filter and label data, extracting general CEP rules. Afterward, it proceeds to generate event logs based on general rules with heuristic mining (HM), extracting high-level CEP rules that pertain to causal relationships. These high-level rules complement the extracted general rules and reflect the causal relationships among the general rules. The proposed high-level methodology is validated using a real air quality dataset

Neurocontrol for Fixed-Length Trajectories in Environments with Soft Barriers

In this paper we present three neurocontrol problems where the analytic policy gradient via back-propagation through time is used to train a simulated agent to maximise a polynomial reward function in a simulated environment. If the environment includes terminal barriers (e.g. solid walls) which terminate the episode whenever the agent touches them, then we show learning can get stuck in oscillating limit cycles, or local minima. Hence we propose to use fixed-length trajectories, and change these barriers into soft barriers, which the agent may pass through, while incurring a significant penalty cost. We demonstrate that the presence of soft barriers can have the drawback of causing exploding learning gradients. Furthermore, the strongest learning gradients often appear at inappropriate parts of the trajectory, where control of the system has already been lost. When combined with modern adaptive optimisers, this combination of exploding gradients and inappropriate learning often causes learning to grind to a halt. We propose ways to avoid these difficulties; either by careful gradient clipping, or by smoothly truncating the gradients of the soft barriers’ polynomial cost functions. We argue that this enables the learning algorithm to avoid exploding gradients, and also to concentrate on the most important parts of the trajectory, as opposed to parts of the trajectory where control has already been irreversibly lost

Bayesian semiparametric multivariate realized GARCH modeling

This paper introduces a novel Bayesian semiparametric multivariate GARCH framework for modeling re- turns and realized covariance, as well as approximating their joint unknown conditional density. We extend existing parametric multivariate realized GARCH models by incorporating a Dirichlet Process mixture of countably infinite normal distributions for returns and (inverse-)Wishart distributions for realized covariance. This approach captures time-varying dynamics in higher-order conditional moments of both returns and realized covariance. Our new class of models demonstrates superior out-of-sample forecasting performance, providing significantly improved multiperiod density forecasts for returns and realized covariance, and competitive covariance point forecasts

NHS Mental Healthcare Staff Experiences of Working with Service-Users Displaying Hoarding Behaviours – A Thematic Analysis

Background: Hoarding Disorder (HD) became its own clinical entity in 2013 and, since then, it has gained more research attention. Evidence suggests that professionals responding to the complex needs of service-users displaying hoarding behaviour lack relevant expertise and highlight hoarding as notoriously difficult to treat. Multi-agency approaches are becoming increasingly popular in the management of hoarding; however, little is known about the treatment of hoarding in UK-based National Health Service (NHS) mental healthcare services. Aim: The aim of the current study was to qualitatively explore NHS mental healthcare staff experiences of working with adult service-users across the lifespan displaying hoarding behaviours. This was to gain a greater understanding of the condition, and to explore how staff respond to the needs of service-users within the context of the NHS. Method: Fifteen mental healthcare staff were recruited from six NHS Trusts in England. Semi-structured interviews were conducted, and the six steps of Reflexive Thematic Analysis were followed. Results: Five themes and fifteen subthemes were identified: (1) How staff understand hoarding behaviour: “The stuff is rarely the issue”; (2) Staff frustrations, challenges and systemic constraints; (3) Treatment approaches for hoarding; (4) Updating practice: Seeing hoarding as a diagnosis; (5) Service-users’ experiences of help. Conclusion: The results of this study highlight how mental healthcare staff attempt to understand hoarding by considering the numerous contributing factors associated with its onset and maintenance. There was ambiguity amongst staff regarding appropriate treatment for this population; however, adopting multi-agency approaches was seen to support service- users’ needs effectively. Staff reflect on the complexities of undertaking this work and consider the impact this has upon service-users and accessing help. Difficulties relating to staff role, service constraints and the lack of staff training are explored. Clinical and policy implications, including the development of best practice guidelines are discussed. Recommendations for future research are proposed