18 results
Part V - Inequalities in health and wellbeing
- Edited by Jeff Evans, Middlesex University, Sally Ruane, De Montfort University, Leicester, Humphrey Southall, University of Portsmouth
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- Data in Society
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- Bristol University Press
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- 30 April 2022
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- 21 August 2019, pp 247-250
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Summary
Distributions of diseases, disorders and death have been a focus of investigation for many centuries and a core area of application of social statistics since the nineteenth century. Far from being purely social constructs, the different components of ‘health’ are nevertheless strongly shaped by the social environments people live in. This is, for example, due to the temporal and geographical distribution of diseases and the respective interventions; and the changing definitions of negative states of ‘health’ which, as a term, focuses on objective indicators and physical conditions. Note also the fact that parity of esteem is today sought for mental health. Relatedly, there is increasing recognition that ‘(mental) health’ is not only defined by the absence of diseases and disorders, but also by differing degrees of positive fulfilment and flourishing, which gives rise to contemporary international perspectives valuing wellbeing and quality of life both as individual and as societal goals.
The four chapters in Part V discuss contemporary aspects of these long-standing topics, all addressing existing and emerging inequalities.
Chapter 19 highlights some of the challenges associated with the framing and measurement of unjust and preventable differences in health. Some of these, the author points out, are statistical challenges, such as the need for sufficiently large samples to capture the experiences of small groups of interest in the population, and the need to appreciate the strengths and limitations of different ways of measuring outcomes between groups. Other challenges relate to how the measures and language used can affect the communities or groups of people whose health is being described, or how the framing of analyses can shape the responses proposed to address health inequalities. The chapter presents selected statistics illustrating inequalities in physical health outcomes and risks at three broad life stages: infancy and childhood, adolescence, and middle to later life. The author argues that our picture is limited by the paucity of data relating to other important forms of health inequality since data based on gender identity, sexual orientation, ethnicity and migration experience are notably absent from many statistics, on their own or in combination with socioeconomic status indicators.
Chapter 20 explores approaches to measuring wellbeing given the limitations of Gross Domestic (or National) Product and other economic approaches.
List of figures, tables and boxes
- Edited by Jeff Evans, Middlesex University, Sally Ruane, De Montfort University, Leicester, Humphrey Southall, University of Portsmouth
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- Data in Society
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- Bristol University Press
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- 30 April 2022
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- 21 August 2019, pp vii-viii
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Contents
- Edited by Jeff Evans, Middlesex University, Sally Ruane, De Montfort University, Leicester, Humphrey Southall, University of Portsmouth
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- Data in Society
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- Bristol University Press
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- 30 April 2022
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- 21 August 2019, pp iii-vi
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Part I - How data are changing
- Edited by Jeff Evans, Middlesex University, Sally Ruane, De Montfort University, Leicester, Humphrey Southall, University of Portsmouth
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- Data in Society
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- Bristol University Press
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- 30 April 2022
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- 21 August 2019, pp 9-12
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Summary
The fundamentals of information technology are not new: the first working electric telegraph was in 1816, and the speed of light was just as fast then as now; the first census to be analysed by machines was the US census of 1890, and statisticians were very routinely using digital computers 40 years ago. All that has really changed since then is everything has got cheaper – much cheaper: the costs of data processing, data storage and data transmission have all fallen by a factor of between 10,000 and 10 million. The ultimate driver was arguably Moore's law, the semiconductor industry's rule of thumb that the density of transistors doubled every two years: smarter electronics enable not just faster processing but also squeezing more data onto the same disk, or down the same optical fibre.
Cheaper computing means statisticians need no longer trek to remote mainframes, but the larger consequence is that vastly more data is recorded, assembled centrally and analysed: ‘big data’. For example, in the 1960s most shops had cash registers but they were not networked, and chains gathered in only the most basic summaries of transactions; today, a central database records every item sold, often identifying the individual customer, and the Economist magazine declares that ‘data is the new oil’: profits flow not out of the ground but from using data to design products and to target advertising at specific customers. The chapters in this part explore the implications for society of this vast expansion of data held about us, one central issue being who controls it: today, companies often know far more than governments. Another more technical consequence is that historically we could often only analyse a sample, hopefully representative; today we often have what is claimed to be ‘population data’, but some groups may still be excluded.
Kevin McConway (Chapter 1) explores the occupational landscape of the data professions. He compares traditional statisticians with the new breed of ‘data scientists’, and also examines how data journalists, campaigners and academics such as economists and psychologists work with statistics. He considers how these diverse approaches and orientations shape the discipline of statistics and how it is seen. He asks who presents the results to which audiences, arguing the manner of communication must reflect the audience.
Index
- Edited by Jeff Evans, Middlesex University, Sally Ruane, De Montfort University, Leicester, Humphrey Southall, University of Portsmouth
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- Data in Society
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- 21 August 2019, pp 381-393
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Part III - Statistics and the changing role of the state
- Edited by Jeff Evans, Middlesex University, Sally Ruane, De Montfort University, Leicester, Humphrey Southall, University of Portsmouth
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- Data in Society
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- Bristol University Press
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- 30 April 2022
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- 21 August 2019, pp 115-118
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Summary
In recent decades, alongside a greater propensity by governments to intervene in the affairs of foreign nations and greater international collaboration around matters of trade and supranational problems such as climate change and terrorism, we have seen significant changes in the nature of domestic state activity. These include withdrawal from certain areas of activity such as service provision, with implications for the cost, quality, accessibility and accountability of ‘public’ services; changes in the allocation of resources through taxation, public spending and regulatory mechanisms with marked effects on inequality; changing social relations within the state brought about by a shifting boundary between private and public sectors; and reductions in the powers of the Westminster-based government and its associated civil service in favour of expanded powers and responsibilities accruing to governments in Edinburgh, Cardiff and Belfast.
This Part speaks to some of these dimensions of the changing role of the state and highlights the political character of many data and statistics. Chapter 9 examines the changing governance of official statistics. David Rhind asks who controls official statistics, for whose benefit and how we can know whether they are fit for purpose. The chapter describes the evolution of UK Official Statistics over an 80-year period under the influence of personalities, politics and government policies, new user needs and changing technology. The author argues these have led to changing institutional structures and periodic oscillations in what statistics are created and the ease of their accessibility by the public. The chapter concludes with the impact of the first major statistical legislation for 60 years, the Statistics and Registration Service Act of 2007 which led to the creation of the UK Statistics Authority. The author argues that among its consequences have been major investment in quality assurance of National and Official Statistics and in professional resourcing and, equally importantly, the statutory specification of government statistics as a public good. The author points to further likely changes in what is collected and how, given the advent of new technologies.
Rhind notes the challenges posed by the decentralised character of UK statistics and Chapter 10 continues the focus on official statistics, this time exploring the consequences of devolution for the generation of statistics across the United Kingdom.
4 - Social media data
- Edited by Jeff Evans, Middlesex University, Sally Ruane, De Montfort University, Leicester, Humphrey Southall, University of Portsmouth
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- Data in Society
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- Bristol University Press
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- 30 April 2022
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- 21 August 2019, pp 47-60
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Summary
Introduction
As the ‘participatory’ Web 2.0 model has supplanted ‘publication’ on the World Wide Web, several rapidly evolving sites and applications, such as Twitter, Facebook, Flickr, Wikipedia and YouTube, have promoted the creation and enabled, to varying extents, the retrieval of increasingly large volumes of user-generated content. Some of these human-made digital artefacts consisting of text, shared web links, audio, image or video files are publicly posted allowing widespread, although seldom free, access to potentially huge volumes of material. Social media data are rarely numerical, but many statistical techniques are now deployed to analyse these newfound sources of ‘Big Data’. Chang and colleagues (2014) have suggested that a ‘paradigmatic shift’ has resulted from these technological advances, leading to a new type of computational social science, a development which, relying largely on quantitative and inductive methodologies, has not been universally welcomed (Fuchs, 2017a; Wyly, 2014). This chapter describes the characteristics of social media data, methods of data collection and analysis and argues that, with several inherent peculiarities, social media data must be embraced, but approached cautiously, by statisticallyminded researchers.
Social media big data
Characteristics
Social media datasets are widely accessed and used in government, corporate and academic environments. Applications include the surveillance and monitoring of citizens (Fuchs, 2017b), business brand and reputation management (Grabher and Konig, 2017) and wide-ranging investigations in social and information systems research (Kapoor et al, 2018). Many digital records of human societal interaction, typically sourced from the billions of messages created every day by users of popular online social networks such as Facebook and Twitter, are now accessible. Social media data are time-stamped, allowing temporal sequencing while individual records are often packaged for access, with metadata, in one of the ‘semi-structured’ interchange formats of the web, such as XML or JSON, not always familiar to statisticians. Some social media data, for example Flickr images or Twitter tweets, hold Latitude and Longitude coordinates allowing straightforward mapping of ‘geotagged’ phenomena. Key demographic or address information, including age, sex, street, town or postcode are not, for privacy reasons, available in social media data although some, such as gender, may be imputed with varying levels of success by examining language usage in text. Exceptionally, where users grant ‘read access’ to third-party social media applications, these variables may become visible to ‘app’ developers.
Notes on contributors
- Edited by Jeff Evans, Middlesex University, Sally Ruane, De Montfort University, Leicester, Humphrey Southall, University of Portsmouth
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- Data in Society
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- 21 August 2019, pp ix-xiv
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Part VI - Advancing social progress through critical statistical literacy
- Edited by Jeff Evans, Middlesex University, Sally Ruane, De Montfort University, Leicester, Humphrey Southall, University of Portsmouth
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- Data in Society
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- Bristol University Press
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- 30 April 2022
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- 21 August 2019, pp 303-306
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Summary
The previous Parts of the book have examined how new technologies, globalisation, the changing role of the state and economic life, and inequalities in health and wellbeing have influenced data and statistics. In this Part, we point to resources and methods for promoting progressive change.
We begin with the Radical Statistics Group, a facilitator of this book project, and a longstanding independent network which supports members and allies in critical analysis of statistics and research. Jeff Evans and Ludi Simpson (Chapter 23) trace the Group's development, through the early years, during the post-1990 reaction to Thatcherism, and since 2000. Nowadays, discussion takes place via email lists and social media, and in small, usually ad hoc working groups, where personal connections and the established ethos of the group facilitate working relationships. Thus the group promotes ‘critical statistical literacy’, simultaneously supporting action related to issues of public policy and governance.
One case study of the use of RadStats resources comes from a group of patients, researchers, statisticians and medics campaigning for the recognition of, and further research into, Lyme disease, a hitherto relatively poorly understood condition caused by tick bites. Kate Bloor (Chapter 24) explains how a multidisciplinary health movement has harnessed critical statistical thinking to challenge various aspects of Lyme disease treatment, including prevention, initial health service response, testing and diagnosis. This case study illustrates the role of patients in challenging disease categories, creating new evidence, relating evidence to policy making, and thereby challenging healthcare policy. It shows how patient researchers, as ordinary citizens, can work with statistics experts to understand science's methodologies as well as its limitations.
Another case study of statistical activism comes from an examination of ‘precarious’ employment in Australian universities. In the last two decades, insecure work in universities in many countries has grown exponentially, alongside the rapid marketisation of higher education, in turn reflecting the neoliberal ideal of a flexible workforce. In Australia most university teaching is now done by hourly paid employees. This structural dependence poses a reputational problem for universities, and limits the pursuit of industrial justice. Universities respond by obfuscating the statistical evidence. Nour Dados, James Goodman and Keiko Yasukawa (Chapter 25) report on their efforts to estimate the levels of precarity, within academic trade union campaigns.
Part IV - Economic life
- Edited by Jeff Evans, Middlesex University, Sally Ruane, De Montfort University, Leicester, Humphrey Southall, University of Portsmouth
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- Data in Society
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- Bristol University Press
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- 30 April 2022
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- 21 August 2019, pp 183-186
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Summary
Even if we no longer see ‘statistics’ as by definition about the state, the most available statistics still come from and largely concern government; and this was reflected in Part III. In fact, most of the earliest quantitative data, before the first census, were financial, especially records of the tax system, but over the last hundred years these have often been the almost exclusive domain of economists, frequently arguing particular pro-free market positions. Economic debates tend to focus on theory; data, to the extent that they are involved at all, tend to be presented as unproblematic. In this Part we show how basic economic data are often simply lacking. Thus, for example, the lack of reliable data on financial derivatives, notably securitised mortgages, was at least partly responsible for the 2008 crash; and we often need detailed investigation to unearth how exactly data sources and methodologies shape our knowledge of economic fundamentals, such as income distributions and unemployment.
The first two chapters focus on the economic lives of individuals and households. Stewart Lansley (Chapter 14) addresses arguably the most basic of economic questions, the distribution of incomes. He argues that the recent political emphasis on the extremes of inequality, epitomised by the Occupy movement's campaigning against ‘the one per cent’, was made possible only by new and detailed academic research. Specifically, and shedding an interesting light on the discussion of administrative data in Part I, a focus on the differences in earnings between the top and bottom fifths, measured by sample surveys, was supplanted by a focus on the growing gulf between the top 1%, and even the top 0.1%, and everyone else, measurable only through large-scale analysis of tax returns. Lansley then focuses on trends post-2008 in the UK, showing that government claims that inequality is declining are based on cherry-picking data.
Paul Bivand (Chapter 15) then looks in more detail at traditional labour market statistics, and in particular at how we measure the unemployment rate and wage inflation. He shows how the former is based on particular definitions of who is ‘employed’, who ‘unemployed’ and who ‘economically inactive’, all of which are informed by economic theory and open to challenge. Similarly, earnings data exclude large parts of the workforce.
Data in Society
- Challenging Statistics in an Age of Globalisation
- Edited by Jeff Evans, Sally Ruane, Humphrey Southall
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- Published by:
- Bristol University Press
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- 30 April 2022
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- 21 August 2019
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This book analyses societal trends and controversies related to developments in data ownership, access, construction, dissemination and interpretation, looking at the ways that society interacts with and uses statistical data.
Preface
- Edited by Jeff Evans, Middlesex University, Sally Ruane, De Montfort University, Leicester, Humphrey Southall, University of Portsmouth
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- Data in Society
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- Bristol University Press
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- 30 April 2022
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- 21 August 2019, pp xix-xx
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Summary
We are grateful to the members of the Radical Statistics Group for their support and encouragement from the start, and to the Troika for covering travel costs for preliminary brain-storming meetings and for subsequent editorial meetings. John Bibby and Jan Bohnke played key roles in originating the project. We are thankful to those who reviewed chapters. Some reviewers are among the book's contributors; others include Simon Briscoe, Madeline Drake, Dave Drew, Craig Duncan, John Grahl, Richard Hall, Donald Houston, Anne Humbert, Dougal Hutchison, Paul Jackson, David Jarrett, Mark Johnson, Orthodoxia Kyriacou, Tony O’Sullivan, Jon Macnicol, Adrian Sinfield, Grahame Thompson, Stephan Tietz, Liz Twigg, David Webster. We have also benefitted from the comments of the publisher's reviewers both at the proposal stage and after the initial submission of the manuscript.
All these suggestions and observations helped us to reinforce our attempts to produce a book which is readable and accessible to a broad range of people, including undergraduate students and interested members of the public. We also thank our academic, technical and administrative colleagues at our several institutions (Middlesex University, De Montfort University and Portsmouth University) for help on various occasions.
We are especially grateful to those who have given permission to use their cartoons and illustrations to cheer up the book's material: to Melanie Schoelhammer for the illustration preceding the introduction to the book; to Russell Ecob (on behalf of Tinikke Treffers) for those on the title pages of Parts I and V; to Tim Hunkin, for those on the title pages of Parts II, III and IV; to Claire Calman (on behalf of Mel Calman) for the cartoon for the Part VI title page; and to xkcd.com for the cartoon on the Epilogue title page.
We are indebted to the team at Policy Press, especially Shannon Kneis, Victoria Pittman, Kathryn King, Phylicia Ulibarri-Eglite and Bahar Celik Muller, for valuable guidance and support. Above all, we thank the authors who have contributed chapters and responded to several deadlines and multiple requests for clarification and further details – and Danny Dorling for writing the Foreword.
For further insight into the aims and activities of the Radical Statistics Group, please see Chapter 23 or www.radstats.org.uk.
General introduction
- Edited by Jeff Evans, Middlesex University, Sally Ruane, De Montfort University, Leicester, Humphrey Southall, University of Portsmouth
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- Data in Society
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- Bristol University Press
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- 30 April 2022
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- 21 August 2019, pp 1-8
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Summary
Origins of this book
This book is the third in a series of critical reflections on the state of statistics supported by the Radical Statistics Group, following on from Demystifying Social Statistics (Irvine et al, 1979) and Statistics in Society (Dorling and Simpson, 1999). Both earlier books were mainly concerned with UK official statistics, as tools for understanding and sometimes changing the economy and society. In the 20 years since Statistics in Society appeared, a far wider range of data sources have gained influence, so this book must be concerned not just with ‘official statistics’ but with administrative data from many different parts of the state, data produced and owned by companies, and data ‘harvested’ from social media.
Our language has also changed. We now often talk about ‘data’ produced by data scientists, not ‘statistics’ produced by statisticians. Traditional statistical methods are grounded in probability theory, which assumes data are random samples, or ‘behave’ similarly, so requiring formal hypothesis testing. The new data science ignores much of this and requires instead a familiarity with computer programming, often accessing live ‘data feeds’ via ‘APIs’ (Application Programming Interfaces) such as those provided by Twitter – or Transport for London. Rather than test hypotheses, these new approaches create machine learning models, using methods which minimise the importance of representative sampling, and the distinction between causal relations and mere correlations.
This Introduction, and the chapters in this book, relate these and other changes in statistics and data to key trends in society. In these we include the 2007–08 financial crisis; the subsequent ‘austerity’ regimes in the UK and elsewhere; uneven economic and financial performance; crises of governance at local, national and international levels; and longer term trends of increasing inequality and deepening globalisation.
We introduce individual chapters at the start of each Part. In Part I, we consider recent challenges to traditional ways of doing statistics, sources of data and methods of analysis. Part II considers some consequences of an increasingly globalised world. Parts III and IV review changes in how the state functions, and in the economy. Part V covers changes in health and health policy.
Epilogue: progressive ways ahead
- Edited by Jeff Evans, Middlesex University, Sally Ruane, De Montfort University, Leicester, Humphrey Southall, University of Portsmouth
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- Data in Society
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- Bristol University Press
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- 30 April 2022
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- 21 August 2019, pp 375-380
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Summary
How can our society's relationship with its data be improved? Our authors offer many pointers to the way ahead. We hope this book will make you better informed, but also help you develop types of action appropriate to your situation as you see it, as an active citizen.
One idea that has guided our activity, and has been a theme of this and the previous two books, Demystifying Social Statistics and Statistics in Society, is that data are a ‘social product’. This means that the wider context in which data are commissioned, captured, analysed, disseminated and interpreted is fundamental to the data's production; so we should ask who really owns or controls these phases in the production of data, how such power is deployed, and what the most fruitful responses in the current situation are. We discuss these issues here first for official statistics, then for commercial data, for social media data, and finally for data created by civil society.
Official statistics
Radical statisticians have tended to criticise government statistics, arguing for constant scepticism and vigilance. Many of our chapters exemplify and justify that vigilance, but we also need to oppose a pervasive cynicism about all statistics. As William Davies (2017) wrote, ‘antipathy to statistics has become one of the hallmarks of the populist right, with statisticians and economists chief among the various “experts” that were ostensibly rejected by voters in 2016’. Elements of the Brexit campaigns and the Trump administration have been marked by a general rejection of all numeric data in favour of anecdote and preconception, for example on counts of immigrants, or the supposed abuses of welfare systems used to justify ‘reforms’.
We need better statistics, not fewer. One safeguard has been the professional standards of statisticians, which mean that the official statistics have generally measured what they say they do, even if this is not necessarily what we would want; indeed, there are notable instances of statisticians resisting politicians’ manipulations (Langkjar- Bain, 2018). In Britain, as Chapter 9 documents, the principle has been established that the Office of National Statistics is independent of the government of the day.
Frontmatter
- Edited by Jeff Evans, Middlesex University, Sally Ruane, De Montfort University, Leicester, Humphrey Southall, University of Portsmouth
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- Book:
- Data in Society
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- Bristol University Press
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- 30 April 2022
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- 21 August 2019, pp i-ii
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19 - The urban labour market
- from Part IV - Getting and spending
- Edited by Martin Daunton, University of Cambridge
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- The Cambridge Urban History of Britain
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- 28 March 2008
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- 25 January 2001, pp 593-628
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Summary
Towns are often presented as market centres, but mainly as places for the buying and selling of goods, or for financial transactions. This chapter examines several of the most important sectors of the labour market, following the paths taken by individuals over their lives. It then explores the development of each of these sectors, developing an account of the changing nature of life-paths and career structures, and their implications for the developing urban system. The chapter discusses casual trades, skilled artisans, factory workers, miners, domestic service and white-collar work. Finally, it scrutinizes the interactions between the labour market processes and the form of the urban system, concentrating on spatial divisions of labour and the ways in which economic fluctuations altered the relationships between different sectors of the labour market and transformed the geography of towns and cities.
Suicide and unemployment in young people: Analysis of trends in England and Wales, 1921–1995
- David Gunnell, Tom Lopatatzidis, Daniel Dorling, Helen Wehner, Humphrey Southall, Stephen Frankel
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- The British Journal of Psychiatry / Volume 175 / Issue 3 / September 1999
- Published online by Cambridge University Press:
- 03 January 2018, pp. 263-270
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- September 1999
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Background
The influence of the macro-economic climate on suicide is unclear. During the recent recession, rates have increased in young males but declined in females.
AimsTo investigate associations between unemployment and suicide in 15 – to 44-year-old men and women over a period spanning two major economic recessions (1921–1995). To minimise confounding by changes in method availability, analyses are restricted to suicides using methods other than poisons and gases.
MethodTime-series analysis using routine mortality and unemployment data.
ResultsThere were significant associations between unemployment and suicide in both males and females. Associations were generally stronger at younger ages.
ConclusionsSecular trends in youth suicide may be influenced by unemployment or other factors associated with changes in the macroeconomic climate. These factors appear to affect women to the same extent as men. Although it is not possible to draw firm aetiological conclusions from time-trend data, our findings are in keeping with those of person-based studies.
7 - Poor Law statistics and the geography of economic distress
- Edited by James Foreman-Peck
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- New Perspectives on the Late Victorian Economy
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- 15 March 2010
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- 21 March 1991, pp 180-217
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Introduction
This chapter forms part of my continuing research on the antecedents of the ‘North-South’ divide in Britain, a division defined most commonly, in economic terms and for policy purposes, in terms of unemployment; it first became generally recognised in the form of the ‘depressed areas’ of the inter-war period. My earlier research has studied the regional distribution of unemployment between 1851 and 1914, using the records of trade union unemployment insurance schemes. These are arguably a very reliable source for trade union members, but clearly cover only a small fraction of the working population; existing analyses are further restricted to three principal trade unions: the Amalgamated Society of Engineers (ASE), the Amalgamated Society of Carpenters and Joiners (ASC&J), and the Friendly Society of Ironfounders (FSIF). The results of these studies point consistently to the concentration of high levels of unemployment in the north of England, contradicting various authors who have asserted that the First World War marked a turning point, and hence that the ‘Depressed Areas’ dated only from the inter-war period (Southall 1984, 1986, 1988).
Given the significance of these findings for an understanding of the genesis of the British regional problem, there is a need for confirmatory analyses of economic distress concerned with a larger part of the population. The Poor Law, in contrast with the trade unions, notionally provided relief for the entire population, and therefore provides the obvious base for such a wider study.