Unpaid Care in Tower Hamlets

Tower Hamlets, a vibrant borough in the heart of London, stands as a microcosm of diversity, where socio-economic, cultural, and spatial dynamics intertwine to shape community life. Within this intricate tapestry, the provision of unpaid care emerges as a vital yet multifaceted phenomenon, reflecting the intertwined threads of familial responsibility, societal support structures, and geographical disparities. This research endeavours to dissect the landscape of unpaid care provision within Tower Hamlets, employing a multidimensional approach that combines geospatial, quantitative, and qualitative methodologies. By harnessing the power of these diverse methods, we aim to unravel the complex interplay of factors that underpin variations in unpaid care provision across the borough. Geospatial methods serve as a cornerstone of this investigation, facilitating the spatial mapping and analysis of care provision patterns across Tower Hamlets. Through Geographic Information Systems (GIS) technology, we will determine spatial clusters of caregiving activity and explore the distribution of unpaid care resources. Quantitative methodologies will complement geospatial analysis by providing numerical insights into the demographics within Tower Hamlets. Census data and Statistical analyses will be utilised to quantify the scale of unpaid care, profile caregivers and care recipients, and elucidate the socio-economic factors driving disparities in care provision. Qualitative methods will enrich our understanding by delving into the lived experiences, perceptions, and challenges faced by caregivers and care recipients in Tower Hamlets. Through the use of discourse analysis, we will uncover the nuanced narratives that illuminate the intricacies of unpaid care provision, capturing the opinions of those effected by the caregiving community in the Tower Hamlets.

To comprehensively assess the evolution of unpaid care provision, I performed a Mann-Whitney U test on census datasets from 2011 and 2021. This form of analysis was chosen due to the non-normal distribution of the data and the sample size being less than 30, rendering traditional parametric tests inappropriate (MacFarland et al, 2016). Utilizing a two-tailed Mann-Whitney U test, I investigated potential differences between the two-time points, considering that this non-parametric approach is robust in accommodating non-normally distributed data. To confirm the absence of normal distribution, I visually inspected the data through a histogram plot, affirming its non-normative nature.

H0: There is no change in the provision of unpaid care across the Tower Hamlets

H1: There has been a change in the provision of unpaid care across the Tower Hamlets

⍴<0.05 | 73<87

The P value is less than 0.05 (0.025 with two-tailed considered at each side), therefore we have sufficient evidence to reject H0, which suggests that there is no change in the provision of unpaid care across the Tower Hamlets and we can accept H1.

There has been a change to the provision of unpaid care in Tower Hamlets from the Mann Whitney U conducted. However, the direction of this change can be determined through the box plot (fig 2). The depicted trend suggests an overall reduction in the provision of unpaid care. This deduction is substantiated by the observed decrease in median values, dropping from 1,130 in 2011 to 968 in 2021. Additionally, the shift in the spread of data down the y-axis further underscores this trend. Notably, the altered range depicted in the box plot implies a convergence toward more uniform levels of care provision among the unpaid caregiving population in Tower Hamlets. This contrasts with previous disparities where certain boroughs exhibited notably higher levels of care provision compared to others.

I conducted discourse analysis on three distinct texts sourced from various outlets such as local plans, support networks etc. concerning the provision of unpaid care in Tower Hamlets. Initially, I employed inductive coding to generate codes directly from the data (Ward & Hastings , 2014), allowing for the emergence of relevant themes. Subsequently, these initial codes served as a foundation for deductive coding applied to the remaining two texts. This transition was motivated by the interconnectedness observed among the codes across different texts, facilitating a systematic analysis of recurring themes in the discourse surrounding unpaid care provision.

• Figure 4, a code trend created from my analysis indicates there is a strong usage of statistics in this text, coupled with the themes of Money and the Economy.
• The use of statistics exacerbates the effect of unpaid care on the local economy in Tower Hamlets and more broadly on the London economy. This was seen, through the continuous referencing of the predicted value of unpaid care "£56.9 billion in 2015" (Sahot, pg. 7) and similar statistics.
• Emphasising this elicits a response from those who aren't necessarily unpaid carers but who feel that this opportunity cost to the economy will affect them.
• Relative to the other pieces of data, the commentary on the social impacts such as the hours worked ,and gender distribution alongside any demographic patterns are smaller. This suggests that this article was not written for the carers themselves but rather for those who seek to rectify any economic leakages that have arisen as a result of unpaid care in Tower Hamlets. Thus contributing to some political undertones that are felt throughout the text.

• This piece of data focused on the social implications of Unpaid care and was aimed at Unpaid carers or people who may be unpaid carers. I compiled a Word Trend (fig 6 ) in which we can see the following five words have the largest frequency Carer, support, work, care, trust and fund.
• Furthermore the codes of Time and the hours unpaid carers provide were more prominent in this text
• This suggests a larger emphasis on the social wel-lbeing of unpaid carers

• In contrast to the first set of discourse analyses I conducted, the use of statistics here can be viewed as a method to minimise the issues of Unpaid carers by comparing it to the London Average, whilst failing to make comparisons based on the Population size of the bororugh and the level of Unpaid care they face
• The placement and formatting of the figures depicting a real increase in the number of carers can be viewed as strategic and emphasises this idea of covering up the issue of Unpaid care, as it is located significantly lower down in the page where residents, policymakers or casual viewers are more unlikely to read it
• The formatting of this text was difficult to interpret, with it being written with complex terminology and littered with stats which suggests that it was not written with locals in mind
• Whilst there are attempts to minimise the fact that unpaid care will be a prevalent issue the text does offer insights into the social toll that it is having on the community by conveying the hours and demographics most affected
• This contributed to an overall neutral narrative

This study has shed light on the nuanced landscape of unpaid care provision within Tower Hamlets, offering valuable insights into its spatial, quantitative, and qualitative dimensions. Through integrating these three approaches several key findings have emerged. Firstly, the geospatial methods employed highlighted Stepney Green and St Dunstan's as areas with the highest percentage provision of unpaid carers, underscoring the spatial disparities within the borough. Moreover, quantitative analysis revealed a discernible decrease in the provision of unpaid care across Tower Hamlets. However, it is essential to acknowledge the potential skewing of this data due to changes in ward boundaries, necessitating caution in interpretation. Additionally, the qualitative exploration of attitudes towards unpaid care illuminated its perceived trajectory as an issue likely to worsen, with significant economic concerns and social implications. This highlights the urgent need for comprehensive support mechanisms and policy interventions to address the evolving landscape of unpaid care provision in Tower Hamlets. Overall, this research underscores the complex interplay of socio-economic, spatial, and attitudinal factors shaping unpaid care provision in Tower Hamlets.