Extant research on Hugh Grant’s star image routinely combines issues of masculinity, sexuality and national identity. Such work concludes that the stumbling, stammering English gent that he mastered for the character of Charles Thacker in Four Weddings and a Funeral or the dishonourable bounder and morally reprehensible cad that he played so brilliantly in Bridget Jones’s Diary is a perfect fit with the man himself. Either way, this article will consider the ways in which film critics and commentators have read and responded to Grant’s on-screen performances and off-screen persona in order to open up a dialogue about shifting iterations of masculinity. Grant is routinely at the forefront of changing definitions of modern manhood, morphing from New Man to New Lad before being constructed and circulated as a figurehead of post-feminist fatherhood. In short, Grant stands as a testament to the very fluid, flexible and shifting nature of the hegemonic hierarchy.
Pakistan’s survival, despite all the formidable odds, allows us to locate challenges to the polity since its inception where imbalances among pressure groups such as military leadership, clerical clusters and political sections have disallowed an overdue breakthrough for its inhabitants. Confronted with street politics led by Imran Khan, Pakistani society is immensely polarised across its width and breadth with constitutional politics put on hold and some people even predicting another spell of authoritarianism. This article argues that a growing middle-class society with youthful demographics has the potential to reassess its priorities and pathways to establish good governance through decentralisation, judicial reforms and regional cooperation, especially at a time when the climatic nightmare lurks in the shadow.
This paper explores practices of citizen bat conservation in the city through the lens of becoming-with animal. It draws on insights gained from practices related to bat conservation efforts through interviews and participant observation with bat advocates in the city of Groningen, Netherlands. We show how becoming-with happens and why it is significant to humans and bats. We argue that becoming-with is dynamic and contingent on the elements present in different human–bat networks, which comprise bodies, technologies, practices, forms of knowledge, and urban spaces and places and result in varied relations that bats and bat conservationists enter into. Also, we observed the various outcomes of local bat conservation efforts. We argue that each of these ways of becoming-with must be considered valid, and is needed, in the big picture of bat conservation efforts in the city.
Reflective supervision (RS) is a crucial component of social work practice but little is known about how RS works within the UK context and what the outcomes of RS are for social workers and their service users. A rapid literature review comprised searching four databases for academic and grey literature on the topic of social work RS. The Mixed Methods Appraisal Tool and the University College London’s literature assessment method were employed in an expedited quality appraisal for all included papers. Twenty-seven papers were included. Findings suggest that a supportive, available manager or a peer-group enables reflective practice. Regularity of supervisory sessions and acknowledgement of a social worker’s autonomy are seen as enablers of reflexivity. In contrast, task-oriented approach that is overly focused on accountability and hindered by the sparsity of resources proves problematic for both social workers and service users. Whilst theoretical papers were available, RS was not defined in a uniform fashion and there was limited evidence pertaining to supervisory practice. More research focusing on what works and what improvements are needed in RS, including adopting a participatory approach would help to bridge this gap and further inform policy and practice.
Prior to the COVID-19 pandemic, social work and social care practitioners had some the worst working conditions of any sector in the UK. During the pandemic, data revealed that social care occupations had higher COVID infection and mortality rates than the general population. The article reports the changing working conditions (measured via the Work-Related Quality of Life scale) and well-being (measured via the Short Warwich–Edinburgh Mental Well-being Scale) of UK social care and social workers across three timepoints between May 2020 and July 2021 through an online cross-sectional survey of working conditions and well-being. Analysis of variance demonstrated that both well-being and working conditions were significantly poorer in July 2021 (phase 3 [n = 1,606]) than the previous two phases (n = 2,523 and n = 2,424, respectively), suggesting that both working conditions and well-being worsened within the social care and social work workforce across the pandemic. Furthermore, each of career satisfaction, working conditions, control, general well-being and home–work interface predicted poorer well-being at Time 3. Whilst chronically poor working conditions can lead to poorer individual psychological and physiological health outcomes, our findings highlight continually poor conditions in this sector, with potential further impacts on organisations and the service users that social care workers support. It is therefore important that individuals, organisations and government develop mechanisms to support these critical workers during and following the pandemic.
This research examines the implications of professional vulnerability (PV) during physical literacy (PL) teacher professional development, through the lens of structural and micropolitical theory in the United Kingdom (U.K.). The research was conducted over a twelve-week period with qualified teachers across primary and secondary school contexts, within the U.K. Semi-structured interviews were used to capture the professional development journey of each teacher. Thematic analysis and pen profiles were used to analyse and present the findings of the semi-structured interviews. The results explore expressions of teacher vulnerability through the structural and micropolitical realities experienced during PL professional development. Structural realities were categorised using the political (macro), organisational (meso) and structural (micro) levels with the micropolitical realities categorised using the power dynamics of power over, with and through. This paper calls for the contextual element of professional development to be given as much consideration as the content itself. Professional development can be more effective by connecting the ‘what’ and ‘how’ alongside an understanding of the ‘where’ and ‘who’. Structural and micropolitical theory and PV offer glimpses into this contextual world, revealing a different but equally important narrative around the wider context of successful and meaningful PL teacher professional development. Finally, the study identifies aspects of transferability into the wider domains of sport coaching and sport development where PL is becoming increasingly visible.
This research explores the working conditions of social workers around the globe, using a mixed-methods approach. A survey of working conditions and wellbeing was distributed to social workers via email and social media. Results subsequently informed the interview schedule for individual semi-structured interviews with social work leaders from across the world. Results confirm that social workers have among the most difficult working conditions of all equivalent professions, with detrimental effects on services for individuals and communities due to burnout and retention. Suggested solutions include legal recognition of the social work profession, improved management support and better pay and conditions.
p>The Coronavirus pandemic has caused significant disruption and change in most aspects of society, and there are concerns that disabled people may be particularly disadvantaged. This article, written by disabled activists and non‐disabled allies, shares data extrapolated from focus groups regarding the lived experiences of twelve disabled people and disability allies during the Covid‐19 pandemic, eleven of whom were based in the UK, and one based in Iraq. We describe the key issues and learning points from this data, arguing that the measures taken by the government and organisations to protect the public during the pandemic have instead brought to the fore long‐standing ableist narratives regarding which bodies are valuable in society. This ableist agenda has acted to control and silence the voices of disabled people by objectifying disability and defining “pre‐existing health conditions” as being more expendable, and therefore less worthy of attention during the pandemic. In presenting our position for change and call to action, we will argue that it is only when disabled people’s experiences and voices are heard in decision‐making that policymakers can begin to learn from the inequalities that have been demonstrated through the pandemic. Here, we will introduce our Wellcome Trust‐funded “We Are the People” Disability Research Collective programme (2021–2026). This programme develops a new disability activist‐led research network, whereby disabled people can conduct research into topics that are important to them.</p
The emergence of technology in psychology research makes it important for psychologists to demonstrate programming skills to keep up on the edge of employability. Python can be used for many other purposes; people create computer games with it, some build web applications and others for still different purposes. The primary goal of this chapter is to introduce you to Python programming for data analysis – in as easy and shortcut method as possible. Because I am aware that you might be already a bit hesitant or scared about the whole idea of learning to code. You might perceive it difficult. But believe me, it’s easy. On the other hand, the bulk of things to learn about Python programming is gigantic. Being a Python programmer alone could be someone’s career. But you don’t want that much. Do you? If you are anything like me or my students, you would like to cut to the chase and learn just as much as a psychologist might need to know to analyse data. That’s exactly what this chapter is trying to do. This chapter is far from being a comprehensive study material. There are dozen of other books for that purpose. You will learn only as much as you need to get done with most of your data analysis needs. In fact, you don’t even have to write Python code scripts from scratch. There are plenty of open-access Python scripts on the Internet that students can borrow for their own purpose instead of writing from scratch. By the end of this chapter, the students will be able to identify each element of a Python code script (what means what). They will understand “why” the codes were written in a particular sequence. More importantly, students will be able to “edit” and “modify” existing sample scripts on the Internet (and in this book) and customise those scripts for their own needs. More serious learners are expected to take on additional advanced courses on Python to become able to create their scripts from scratch – although that is not required in most scenarios as the coding requirement of a psychologist in research is minimum. If you are shy, scared and busy – just hoping to learn this and get over it soon as possible – then you are at the right place.
Much of quantitative research in psychology is dependent on analysing data. But what’s probably more important is to state that no matter how great your analytic technique or model is, if you throw in poor-quality of the data, the inferences or predictions you get will be poor as well. So, it is of paramount importance to refine the raw data just as you would refine crude oil in a refinery and turn it into petrol or diesel before pouring it into your car. Long story cut short, raw data is rarely useable for data analysis and therefore needs to be refined before that. This refinement process consists of three elements: cleaning, transforming and reducing the raw data. Together they are expected to consume the majority of your time in the data science project. I think doing the data analysis with machine learning is easy and quick. The most time-consuming, laborious and the most important part is refining the raw data into a useable form. That’s exactly what you will learn in this chapter. You will learn some of the most commonly used strategies to clean, transform and reduce the data. By the end of this chapter, you will be able to identify the steps that go into data pre-processing. More importantly, you will be able to edit the sample Python scripts presented in this chapter for data pre-processing appropriately on your dataset.
Psychology research is increasingly employing machine learning for data analysis to complement the traditional statistical methods. The reason is that machine learning can help you answer different types of research questions that were impossible with statistics. There are times when both overlap, but depending on the research goals, sometimes researchers favour machine learning over statistics because of their replicability, more accurate predictions and focus on “predicting the outcome” instead of “drawing inference”. The purpose of this chapter is to help you learn how to use some of the most popular machine learning techniques for data analysis and answer new types of research questions. By the end of this chapter, you will be able to identify what type of research questions can be addressed using machine learning. It is also expected that you will be able to analyse your existing datasets using machine learning models. Furthermore, you will be able to interpret the results. Finally, you will be able to design new research studies based on your knowledge of what sort of problems machine learning models can address and learn about human behaviour.
In England, Pupil Premium Plus is additional funding to help address the educational attainment gap experienced by looked after children. This paper explores the experiences of virtual school heads and designated teachers (n = 140) as they access Pupil Premium Plus-related information, guidance and training to support their practice; navigate the complexities of the Personal Education Plan (PEP) process; and measure the impact of Pupil Premium Plus-funded interventions. We explain professionals’ experiences using insights from social practice theories, and argue that the process of supporting the educational outcomes of looked after children via Pupil Premium Plus is made up of context- and audience-dependent ‘social practices’. When the social practices are aligned, virtual school heads and designated teachers may be effectively able to support looked after children, whereas barriers may emerge when social practices become disjointed. We conclude this paper by arguing that for Pupil Premium Plus to support educational outcomes of looked after children effectively, professionals need to reflect on their own cultures and practices.
This article proposes that loved ones supporting prisoners with experience of remand in England and Wales may use Sykes & Matza’s (1957) ‘techniques of neutralization’ by proxy. Adopting neutralisations may enable those in prison to be viewed not as those who have harmed, or bad people, but as those who themselves have been harmed. Potential benefits of these techniques are twofold: they help to reject stigma; and explain and enable continued contact. This framework may be a useful basis for work exploring familial contact and support for those affected by imprisonment.
Maternity services cannot be postponed due to the nature of this service, however, the pandemic resulted in wide-ranging and significant changes to working practices and services. This paper aims to describe UK midwives’ experiences of working during the COVID-19 pandemic. This study forms part of a larger multiple phase research project using a cross-sectional design based on an online survey. The online survey used validated psychometric tools to measure work-related quality of life, wellbeing, coping, and burnout as well as open-ended questions to further understand the experiences of staff working during the pandemic. This paper reports the qualitative data collected from the open-ended questions. The qualitative data were subjected to thematic analysis and the four main themes that emerged were ‘relentless stress/pressure’, ‘reconfiguration of services’, ‘protection of self and others’, and ‘workforce challenges’. The key conclusions were that midwives experienced a reduction in quality of working life and significant stress throughout the pandemic due to a range of factors including staffing shortages, restrictions placed on women’s partners, changes to services and management support, all of which compounded workforce pressures that existed prior to the pandemic. This research recommends consultation of front-line midwives in relation to possible changes in practice and workforce planning in preparation for crises such as a pandemic and to ensure equitable and supportive management with access to practical and psychological support.
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