TY - JOUR
AU - Farrall, Stephen
AB - Abstract Exploring long-term trends in crime and criminal justice is a multifaceted exercise. This article introduces the construction and methodological benefits of a series of new data sets that amalgamate approximately 30 years of public data on crime, victimization, fear of crime, social and political attitudes with national socio-economic indicators in England and Wales. The data operate at both an aggregate and individual level and will be available for public use (and modification) from autumn 2015. Here, we outline the contours and contents of the data set and highlight the importance of using longitudinal data in exploring theoretical and empirical questions about crime, victimization and social attitudes. Introduction This article describes the availability, methodological advantages and challenges of a series of new longitudinal data sets that combine data on crime, victimization, fear of crime and social attitudes to crime, collated from a range of existing but separate sources—integrating aggregate and individual-level data. These data have enabled us to undertake a multi-disciplinary long-term evaluation of the impact of Thatcherite social and economic policies on crime rates in England and Wales—an intellectual project that has been funded by the Economic and Social Research Council (ESRC) and the British Academy (see Farrall and Hay 2014 and ESRC award numbers ES/K006398/1 and RES000222688). We anticipate that the data sets will be of use to researchers working in criminology and criminal justice who wish to explore long-term trends relating to crime. Here, we outline the importance of understanding long-term trends in crime and attitudes towards crime, the contents and organization of the data and how they might be used in future research. Given that the technical documentation supplied with the data sets will focus on practical issues such as recoding and weighting of variables and the provenance of the data, our aim in this study is to outline some of the important theoretical and empirical questions that might be addressed with the data sets and also to discuss some of the limitations associated with data of this sort. The Long View: Identifying the Long Shadow of Thatcherism on Crime Few would doubt that Margaret Thatcher’s period as Prime Minister (from May 1979 to November 1990) was one of considerable social and economic turbulence. De-industrialization, which can be traced back to the 1960s, accelerated, vast parts of the British economy were comprehensively restructured (manufacturing declined by about a half, putting many out of work, decimating whole communities and leading to a stark rise in economic inequality); new sectors of the economy (especially banking, insurance and the service sector) became core to domestic economic output (Crafts 1991; Glennerster 1994). In addition, and as has been well-documented elsewhere, council houses were sold off, local governments’ control of schooling and other public services challenged, and trade union powers were significantly contracted (Walker and Walker 1997). Rules relating to who and what could be claimed from the social security system were also modified (Walker 1993). Perhaps unsurprisingly, officially recorded crime rates—self-reported victimization rates too—rose significantly and consistently (Morgan 2014).1 Studies have since shown that as levels of unemployment and inequality rose, so too did rates of property crime (Morgan 2014). More surprisingly, however, although Thatcher spoke out about crime and ‘law and order’, her government did not pass the draconian acts one might have expected given her electoral rhetoric and that of successive British governments since 1979, despite rising crime rates. In her final 1979 general election broadcast, she referred to citizens needing to feel ‘safe in the streets’ (cited in Riddell 1985: 193). She also repeatedly stated that she was in favour of capital punishment (Thatcher 1993: 307). Although social science research has gone some way to broadening our understanding of the long-term impact of Thatcherite public policy, other crucial questions remain unanswered. For example, what happened to those parts of England, Wales and Scotland in which de-industrialization had been most rampant? Were rises in property crime higher in certain areas of England and Wales than others? Was fear of crime linked to the marked incidence of property crime? How did such changes alter social attitudes not just towards the treatment of offenders, but towards those associated with crime in the popular imagination, such as welfare recipients? Did these tumultuous changes create a new set of social attitudes for young people who grew up during the 1980s—and who are now a growing part of the electorate? We know relatively little beyond the national picture in terms of the economy-crime link. But what is the picture when one explores violent crime or other forms of social harm (such as non-accidental deaths and alcoholism)? Notably, scholars from related branches of social policy have also begun to conduct allied longitudinal investigations in housing policy (Dorling 2014), opiate drug-use (Morgan 2014), education policy (Berridge et al. 2001) and social attitudes (Duffy et al. 2013; Natcen 2014), highlighting the need to build an integrated model of analysis. Moreover, research has demonstrated that how individuals relate to their environment and community can impact upon their feelings about crime (Farrall et al. 2009) as well as the rate of reporting crimes (Goudriaan et al. 2006) and perception of neighbourhood disorder (Sampson and Raudenbush 2004). And finally, taking a longitudinal approach, we might expect to see lifecycle, cohort and period effects (Ryder 1965); so we asked ourselves whether or not we were witnessing the emergence of ‘Thatcher’s Children’2 in terms of attitudes towards law and order and social welfare (Duffy et al. 2013; Perchard 2013). Put simply, the analyses undertaken so far provide us with few answers to these theoretically exciting and methodologically important questions. Building an Integrated Set of Data Sets Relating to Crime, Criminal Justice and Social Attitudes In order to explore these questions in more detail, we have created a series of data sets drawn from national-level surveys (which incorporate demographic markers such as age, education, household income, region and gender) and official statistics. Specifically, these adapt and integrate individual- and aggregate-level data sources, and can be linked through common variables, most notably the observed time period (i.e. by year) but also categories of respondent (e.g. by age, ethnicity, income, region, and employment status). Features of the content and structure of the data sets are described below (we do not report full details of the survey items, but identify some important components), and summarized in Table 1. Table 1 Summary of individual-level data . BCS/CSEW . BSA . BES-CMS . Selected questions Victimization (multiple categories) Role of government General crime situation Fear of crime Unemployment vs. inflation Government/opposition handling of crime Common local problems Duty to obey the law Emotions towards crime Confidence in police/ criminal justice system Death penalty Sought crime assistance Attitudes on sentencing Attitudes on sentencing Satisfied with assistance Burglar/car alarm Likelihood of riots Importance of crime as an issue Attitudes on welfare state People trustworthy Trust in government Demographics Age Age Age Gender Gender Gender Ethnicity Ethnicity Ethnicity Income Income Income Education Education Education Region Region Region Marital status Marital status Marital status House type House type Housing tenure Receipt of benefits Housing tenure Years at address Social class Social class Inner city Newspaper readership Newspaper readership Employment status Employment status Employment status Number of variables 109 80 63 Number of respondents 599,517 89,466 124,110 Period 1981–2013 1983–2012 2004–13 . BCS/CSEW . BSA . BES-CMS . Selected questions Victimization (multiple categories) Role of government General crime situation Fear of crime Unemployment vs. inflation Government/opposition handling of crime Common local problems Duty to obey the law Emotions towards crime Confidence in police/ criminal justice system Death penalty Sought crime assistance Attitudes on sentencing Attitudes on sentencing Satisfied with assistance Burglar/car alarm Likelihood of riots Importance of crime as an issue Attitudes on welfare state People trustworthy Trust in government Demographics Age Age Age Gender Gender Gender Ethnicity Ethnicity Ethnicity Income Income Income Education Education Education Region Region Region Marital status Marital status Marital status House type House type Housing tenure Receipt of benefits Housing tenure Years at address Social class Social class Inner city Newspaper readership Newspaper readership Employment status Employment status Employment status Number of variables 109 80 63 Number of respondents 599,517 89,466 124,110 Period 1981–2013 1983–2012 2004–13 Open in new tab Table 1 Summary of individual-level data . BCS/CSEW . BSA . BES-CMS . Selected questions Victimization (multiple categories) Role of government General crime situation Fear of crime Unemployment vs. inflation Government/opposition handling of crime Common local problems Duty to obey the law Emotions towards crime Confidence in police/ criminal justice system Death penalty Sought crime assistance Attitudes on sentencing Attitudes on sentencing Satisfied with assistance Burglar/car alarm Likelihood of riots Importance of crime as an issue Attitudes on welfare state People trustworthy Trust in government Demographics Age Age Age Gender Gender Gender Ethnicity Ethnicity Ethnicity Income Income Income Education Education Education Region Region Region Marital status Marital status Marital status House type House type Housing tenure Receipt of benefits Housing tenure Years at address Social class Social class Inner city Newspaper readership Newspaper readership Employment status Employment status Employment status Number of variables 109 80 63 Number of respondents 599,517 89,466 124,110 Period 1981–2013 1983–2012 2004–13 . BCS/CSEW . BSA . BES-CMS . Selected questions Victimization (multiple categories) Role of government General crime situation Fear of crime Unemployment vs. inflation Government/opposition handling of crime Common local problems Duty to obey the law Emotions towards crime Confidence in police/ criminal justice system Death penalty Sought crime assistance Attitudes on sentencing Attitudes on sentencing Satisfied with assistance Burglar/car alarm Likelihood of riots Importance of crime as an issue Attitudes on welfare state People trustworthy Trust in government Demographics Age Age Age Gender Gender Gender Ethnicity Ethnicity Ethnicity Income Income Income Education Education Education Region Region Region Marital status Marital status Marital status House type House type Housing tenure Receipt of benefits Housing tenure Years at address Social class Social class Inner city Newspaper readership Newspaper readership Employment status Employment status Employment status Number of variables 109 80 63 Number of respondents 599,517 89,466 124,110 Period 1981–2013 1983–2012 2004–13 Open in new tab Individual-level variables and data sets Victimization Officially recorded crime statistics have been held in suspicion by many criminologists (Maguire 2007). Our data incorporate self-reported data on victimization from the British Crime Survey (BCS), now known as the Crime Survey for England and Wales (CSEW).3 This records respondents’ experiences, within the preceding 12 months, of most forms of crime (albeit with some omissions).4 In addition to measures of victimization, the BCS includes a series of questions on topics such as fear of crime, perceptions of anti-social behaviour in the local area, confidence in the police and criminal justice system and attitudes towards punishment. Because over time there is drift in some response categories, such as household income and ethnicity (in the former case, inflation leads to changes in the categories, whereas in the latter, the number of categories increases over time reflecting increasing diversity of the population), the data are recoded where necessary to create continuous measures over time. This is not possible in instances where a survey question changes, for example, from a four-point to a five-point scale (as is the case with confidence in local police, which used a four-point scale between 1982 and 2003, and a five-point scale since 2003). Instead, new variables are created (with names incorporating the time period) to make these discontinuities clear to users. In total, the BCS data set consists of 599,517 respondents and over 100 variables (though not all survey items are asked in every year, and some are only asked a couple of times during the 30-year period). Social attitudes Our data on public attitudes toward crime and criminal justice, and other domains of social and economic life, is drawn from two main sources. Firstly, we have drawn on the 28 waves of the British Social Attitudes Survey5 (BSA) between 1983 and 2012. This provides attitudinal data, for example, on popular attitudes towards the role of the government in society, attitudes about income inequality and redistribution, and whether benefits for the unemployed are too high or too low. The BSA also includes questions about whether the death penalty should be reinstated, the need for people to obey the law, whether or not lawbreakers should be given stiffer sentences and the degree to which welfare recipients ‘fiddle’ benefits. These survey items provide measures of social attitudes towards sentencing, punitiveness and the image of those on welfare. The BSA data set consists of 80 variables (not including demographic markers) and a total of 89,466 respondents over the period between 1983 and 2012. Secondly, we use the British Election Study’s Continuous Monitoring Survey (BES-CMS) to construct a data set of socio-political attitudes, including perceptions of the crime situation and satisfaction with the criminal justice system, salience of the issue, evaluations of government/party handling of crime and emotions about crime. The survey also includes standard questions on political attitudes (e.g. partisanship, government and prime ministerial approval, vote intention) as well as on broader questions about social and political trust, participation and civic behaviours. This consists of a series of monthly waves over the period between 2004 and 2013, with a total of 124,110 respondents and 63 variables (not including demographic markers). Aggregate-level and contextual variables and data sets Many of the longitudinal processes that we are interested in require us to examine trends over time. Using individual-level data such as the BCS or BSA, it is possible to account for variation in identified dependent variables over time with simple time (typically year) control variables. However, to fully understand dynamic interrelationships between social/economic change and crime, and attitudinal shifts, it is important observe and model both rates of change and lagged processes. To do this, our individual-level data sets are also collapsed to aggregate level (and further broken down by particular demographic markers such as age, ethnicity or region). All data sets can at a minimum be aggregated at the annual level, and additionally the BCS (between 2002 and 2013) and BES-CMS (between 2004 and 2013) data sets can be aggregated to monthly intervals, to observe finer-grained trends and changes in victimization, fear of crime and attitudes towards crime. These are especially useful for looking at the impact of events and media coverage. Many of the key contextual variables considered in longitudinal studies of crime, such as income inequality (typically measured using the Gini coefficient6) or unemployment, are largely treated and measured as national-level constructs. These are macro-level indicators that predict changes in aggregated patterns of behaviour, e.g. crime rates. Our individual-level data are, therefore, integrated with indices of a range of socio-economic conditions, statistics on performance of the criminal justice system and national trends in social attitudes (especially where historical survey data have not survived in individual-level form). We have collated over a hundred time series (most at annual level but a few at quarterly and/or monthly intervals), which we describe here and are summarized in Table 2, which are integrated with both the individual- and aggregate-level BCS, BSA and BES data sets. Some of these series are disaggregated by demographic markers, which enable researchers to further explore how longitudinal processes unfold for particular subsets of the population. Table 2 Summary of aggregate data . Crime and criminal justice . Employment . Macroeconomics . Welfare/other . Politics/policy . Selected data series Official recorded statistics (total/ violent/property) Unemployment rate (national/ by region/males 16–17; 18–24) Interest rates Total benefit expenditure (real/ nominal terms/% of GDP) Queen’s speech Convictions (total/as % of recorded crimes) Economic activity rate Public spending Unemployment/ incapacity/housing benefit (real/nominal terms/caseload) Acts of Parliament Prison population Claimant count (national/ by region) GDP Suicide rates Parliamentary questions (e.g. referring to ‘crime rate’, ‘burglary’, ‘anti- social behaviour’) Police force strength Average weekly earnings Inflation Children in care Labour disputes (days lost) Inequality Council house sales Poverty Truancy and school expulsions Child poverty Drug addicts . Crime and criminal justice . Employment . Macroeconomics . Welfare/other . Politics/policy . Selected data series Official recorded statistics (total/ violent/property) Unemployment rate (national/ by region/males 16–17; 18–24) Interest rates Total benefit expenditure (real/ nominal terms/% of GDP) Queen’s speech Convictions (total/as % of recorded crimes) Economic activity rate Public spending Unemployment/ incapacity/housing benefit (real/nominal terms/caseload) Acts of Parliament Prison population Claimant count (national/ by region) GDP Suicide rates Parliamentary questions (e.g. referring to ‘crime rate’, ‘burglary’, ‘anti- social behaviour’) Police force strength Average weekly earnings Inflation Children in care Labour disputes (days lost) Inequality Council house sales Poverty Truancy and school expulsions Child poverty Drug addicts Open in new tab Table 2 Summary of aggregate data . Crime and criminal justice . Employment . Macroeconomics . Welfare/other . Politics/policy . Selected data series Official recorded statistics (total/ violent/property) Unemployment rate (national/ by region/males 16–17; 18–24) Interest rates Total benefit expenditure (real/ nominal terms/% of GDP) Queen’s speech Convictions (total/as % of recorded crimes) Economic activity rate Public spending Unemployment/ incapacity/housing benefit (real/nominal terms/caseload) Acts of Parliament Prison population Claimant count (national/ by region) GDP Suicide rates Parliamentary questions (e.g. referring to ‘crime rate’, ‘burglary’, ‘anti- social behaviour’) Police force strength Average weekly earnings Inflation Children in care Labour disputes (days lost) Inequality Council house sales Poverty Truancy and school expulsions Child poverty Drug addicts . Crime and criminal justice . Employment . Macroeconomics . Welfare/other . Politics/policy . Selected data series Official recorded statistics (total/ violent/property) Unemployment rate (national/ by region/males 16–17; 18–24) Interest rates Total benefit expenditure (real/ nominal terms/% of GDP) Queen’s speech Convictions (total/as % of recorded crimes) Economic activity rate Public spending Unemployment/ incapacity/housing benefit (real/nominal terms/caseload) Acts of Parliament Prison population Claimant count (national/ by region) GDP Suicide rates Parliamentary questions (e.g. referring to ‘crime rate’, ‘burglary’, ‘anti- social behaviour’) Police force strength Average weekly earnings Inflation Children in care Labour disputes (days lost) Inequality Council house sales Poverty Truancy and school expulsions Child poverty Drug addicts Open in new tab Criminal justice system For comparison against the BCS data on victimization, and also for enabling a longer-term view of crime that dates to earlier than the 1970s, our data include official recorded statistics on the annual number of different categories of crimes for England and Wales as reported in the Home Office’s (2012; 2014),Recorded Crime Statistics for England and Wales 1898–2001/02 and Recorded Crime Statistics for England and Wales 2002/03–2013/14 data sets. There is also annual data on the number of convictions (plus the per capita and per crime conviction rates), obtained from Mitchell’s (2003),British Historical Statistics, combined with data from the Annual Abstract of Statistics for later time periods. Annual data on the size of the prison population are taken from the Ministry of Justice’s (2013) caseload statistics. Socio-economic indicators A large amount of data on the state of economy and society are included in our aggregate-level data set. This includes standard measures of inflation and unemployment rates, the claimant count and rate, economic inactivity, average earnings, labour disputes and GDP drawn from official statistics of the Office for National Statistics (www.ons.gov.uk). Data are also included on levels of inequality, poverty and incomes from the Institute for Fiscal Studies (www.ifs.org.uk). Data on annual benefits expenditure (and specific categories of benefits) are taken from the Department of Work and Pensions (2014). We have collated data on truancy from the Youth Cohort Study7 from around 1985 and school expulsions from the late 1990s. In addition, we have included data from the Home Office Addicts Index, which records new heroin addicts notified to the police (for the period from 1977 to 1997), suicide rates (from Office for National Statistics 2012) and council house sales (from Department for Communities and Local Government 2013, with the latter also disaggregated by region). To complete our measures of social conditions, we have data on the number of children in care dating back to the 1960s. Policy and politics Our data sets also include measures of political attention and on policy action on crime. We draw on data from the UK Policy Agendas Project (www.policyagendas.org.uk) to capture the amount of attention given to crime, and law and order, in the statement of policy intentions set out in the Queen’s Speech and in Acts of Parliament (between 1945 and 2012). We have generated our own data on the frequency of mention of crime rates and specific crime-related issues (such as anti-social behaviour) in all parliamentary debates over the period between 1900 and 2004 using the Hansard Prototype archive of parliamentary debates (http://hansard.millbanksystems.com/). Public opinion Finally, we have been able to collect a number of aggregate-level measures of public opinion over an extended time period, enabling a long-term view of attitudinal shifts. Firstly, this includes survey data on the ‘most important problem’ facing the country, as collected by the Gallup Organization between 1944 and 2001 (and the ‘most important issue’, as collected by Ipsos-MORI between 1974 and 2014). This measure indicates the prominence of crime as an issue on the public’s mind (see Jennings and Wlezien 2011). In addition, we include data on the public’s preferences for left or right public policy (‘public policy mood’), from Bartle et al. (2011), and have constructed our own measure of public punitiveness using survey items on capital punishment, sentencing and other aspects of criminal justice, using a method developed by Stimson (1991) and applied by Enns (2014) in the US. The data have been collated and stored in a manner we hope conducive to its use by other researchers. It has been ‘preserved’ so that it is possible to use at both individual and aggregate levels. This should provide users with flexibility to adapt the data sets for their own purposes—either integrating additional contextual variables or collapsing the data by specific demographic markers. Each survey can be analyzed as a large ‘stand-alone’ data set. The BCS has almost 600,000 respondents over the period from 1981 to 2013 (the oldest year of birth is 1885), allowing for robust analyses of particular items where responses or subgroups may be rare, for example, male victims of domestic violence (Gadd et al. 2002). It is also possible to ‘collapse’ these survey responses into annual aggregate observations (e.g. the rate of crime per capita, average fear of crime in the population) to measure trends over time and to undertake time-series modelling of the data (interpolating missing years in the BCS and BSA). This aggregate data can also be merged with contextual variables, so for example, survey items from the BSA can be used to explore the degree to which social attitudes shift as crime rises and falls, based on self-reported rates of victimization from the BCS. Another potential use of the data is to repeat the above analyses disaggregating regions of England and Wales.8 This allows one to check for the structural invariance of national-level processes at the regional level—and may highlight unique behavioural or cultural processes taking place in particular localities. A further technique that can be employed with this longitudinal data is age-period-cohort analysis (Ryder 1965; Grasso 2014), which allows exploration of the unique contributions of three types of time-related variations, namely age, period and cohort effects. Distinguishing these variations is critical for testing individual or social mechanisms that may influence variation in behaviour and attitudes across age groups of the population. Specifically, age effects represent developmental changes in the life course; period effects arise via cultural and economic changes that are exclusive to the study period, whereas cohort effects are the core of social change and represent the effects of formative experiences (Ryder 1965). Limitations of the Data It is important, however, to acknowledge the limitations of any data set of this kind. ‘Big Data’, to adopt the phrase in vogue at present, no matter how big or how well-honed, is not a magic bullet (cf. Savage and Burrows 2007; Manovich 2011). There are some factors that are relevant and likely important for understanding changes in victimization and social attitudes over this period (such as the experiences of homeless people and the growth of CCTV surveillance), but for which no quantitative data exists—and cannot be retrospectively constructed. As such, the experiences, behaviours and attitudes that researchers are able to analyze reflect preoccupations and concerns (not to mention question wording and research design) of an earlier generation of researchers. This is a perennial problem for secondary data analysis (Dale 2004). In our case, it means that, to return to the example we cite above, the degree to which homeless people were abused by passers-by in the street or had their possessions stolen cannot be subjected to analysis using the data that we have collated. A further consequence is that the choice of data and method will shape the story we can deduct—in this instance, for example, the unintended consequences of the ‘right to buy’ policies promoted by the Thatcher governments following the 1980 Housing Act (see Carlen 1996 for a more thorough exploration of this matter). Analogously, the psychological damage done to a young man’s sense of ‘self’ and of their place in society when facing long-term unemployment and the alternative ways in which they chose to assert their masculinity (Gadd and Farrall 2004), unfortunately, cannot be explored using this sort of data. Even though our collation of data provide a substantial overview of changes in victimization, fear of crime and social attitudes—as well as broader changes in the economy, society and politics—it does not offer an exhaustive appreciation of lived realities of social exclusion and engagement in crime. In sum, the priorities of researchers-past may limit the validity of conclusions drawn from today’s ‘Big Data’, which lack the ‘thick’9 descriptive accounts that ethnographic or qualitative data can provide. This is especially important given the emphasis that government and research councils increasingly place on maximizing the value and use of data and conducting secondary analysis. This trend towards the collection and use of large and integrated data sets will continue, providing opportunities for new empirical and methodological inroads. It also has the potential to facilitate strong interdisciplinary connections as researchers from related fields become aware of data that is relevant to them. But we must also be cautious about the intrinsic assumptions, values and biases involved in historical data and the knowledge that can be extracted from it. Future possibilities Our project is funded by the ESRC (award No. ES/K006398/1).10 All of the data that we have collated will be deposited at the UK Data Archive at the end of the project (in the autumn of 2015) for use by other researchers. We hope that the data sets we have generated will form the basis of projects undertaken by other researchers, which either supplements our data with additional variables, or with equivalent data collated from other countries for comparative analyses. These data sets can also be updated as new sweeps of the annual surveys are released. The data are designed to be a platform for others to build upon, modifying for their own research projects, PhD studentships and teaching purposes. Funding We would like to acknowledge the support of the Economic and Social Research Council, award numbers ES/K006398/1 and RES000222688. References Bartle J. Dellepiane-Avellaneda S. Stimson J. A . ( 2011 ), ‘The Moving Centre: Preferences for Government Activity in Britain, 1950–2005’, British Journal of Political Science , 41 : 259 – 85 . Google Scholar Crossref Search ADS WorldCat Berridge D. Brodie I. Pitts J. Porteous D. Tarling R . ( 2001 ), The Independent Effects of Permanent Exclusion from School on the Offending Careers of Young People RDS Occasional Paper No. 71 . Home Office . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Bolling K. Clemens S. Grant C. Smith P. Brown M . ( 2004 ), 2003–04 British Crime Survey (England and Wales): Technical Report . BMRB . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Carlen P . ( 1996 ), Jigsaw: A Political Criminology of Homelessness . Open University Press . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Crafts N. F. R . ( 1991 ), ‘Economic Growth’, in Crafts N. F. R. Woodward N ., eds, The British Economy Since 1945 . Clarendon Press . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Dale A . ( 2004 ), ‘Secondary Analysis of Quantitative Data’, in Lewis-Beck M. S. Bryman A Lioa T. F. eds, The Sage Encyclopedia of Social Science Research Methods , 1007–9. Sage . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC de Castelbajac M . ( 2014 ), ‘Brooding Over the Dark Figure of Crime: The Home Office and the Cambridge Institute of Criminology in the Run-up to the British Crime Survey’, British Journal of Criminology , 54 : 928 – 45 . Google Scholar Crossref Search ADS WorldCat Department for Communities and Local Government . ( 2013 ), ‘ Table 643: Financial Data on the Right to Buy Scheme, by Region’ , available online at https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/80772/Table_643_final.xls. Department for Work and Pensions . ( 2014 ), ‘ Benefit Expenditure and Caseload Tables ’, available online at https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/310483/outturn-and-forecast-budget-2014.xls. Dorling D . ( 2014 ), All That Is Solid: How the Great Housing Disaster Defines Our Times, and What We Can Do About It . Allen Lane . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Duffy B. Hall S. O’Leary D. Pope S . ( 2013 ), Generation Strains . Demos . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Enns P. K . ( 2014 ), ‘The Public’s Increasing Punitiveness and Its Influence on Mass Incarceration in the United States’, American Journal of Political Science , 58 : 857 – 72 . Google Scholar Crossref Search ADS WorldCat Farrall S. Hay C . (eds) ( 2014 ), The Legacy of Thatcherism: Exploring and Theorising the Long-term Consequences of Thatcherite Social and Economic Policies . Oxford University Press . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Farrall S. Jackson J. Gray E . ( 2009 ), Crime Politics and Insecurity: Experience and Expression in the Fear of Crime . Oxford University Press . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Gadd D. Farrall S . ( 2004 ), ‘Criminal Careers, Desistance and Subjectivity: Interpreting Men’s Narratives of Change’ , Theoretical Criminology , 8 : 123 – 55 . Google Scholar Crossref Search ADS WorldCat Gadd D. Farrall S. Dallimore D. Lombard N . ( 2002 ), Domestic Abuse Against Men in Scotland, Scottish Executive Central Research Unit Report . Scottish Executive . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Geertz C . ( 1973 ), The Interpretation of Cultures: Selected Essays . Basic Books . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Glennerster H . ( 1994 ), ‘Health and Social Policy’, in Kavanagh D. Seldon A. , eds, The Major Effect . Macmillan . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Goudriaan H. Wiiterbrood K. Nieuwbeerta P . ( 2006 ), ‘Neighbourhood Characteristics and Reporting Crime. Effects of Social Cohesion, Confidence in Police Effectiveness and Socio-Economic Disadvantage’ , British Journal of Criminology , 46 : 719 – 42 . Google Scholar Crossref Search ADS WorldCat Grasso M. T . ( 2014 ), ‘Age, Period and Cohort Analysis in a Comparative Context: Political Generations and Political Participation Repertoires in Western Europe’, Electoral Studies , 33 : 63 – 76 . Google Scholar Crossref Search ADS WorldCat Home Office . ( 2012 ), Recorded Crime Statistics for England and Wales 1898–2001/02 . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC ——. ( 2014 ), Recorded Crime Statistics for England and Wales 2002/03–2013/14 . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Howe N. Strauss W . ( 1992 ), Generations: The History of America’s Future 1584–2069 . Vintage Books . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Jennings W. Wlezien C . ( 2011 ), ‘Distinguishing Between Most Important Problems and Issues?’ Public Opinion Quarterly , 75 : 545 – 55 . Google Scholar Crossref Search ADS WorldCat Maguire M . ( 2007 ), ‘Crime Data and Statistics’, in Maguire M. Morgan R. Reiner R. eds, Oxford Handbook of Criminology , 4th edn, 241–301. Oxford University Press . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Manovich L . ( 2011 ), ‘Trending: The Promises and the Challenges of Big Social Data’, in Gold M. K. ed., Debates in the Digital Humanities , 460–75. The University of Minnesota Press . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Ministry of Justice . ( 2013 ), Offender Management Caseload Statistics, England and Wales. Table A1.1 Prison Population by Type of Custody, Age Group and Sex, 30 June 2002 to 30 June 2013, England and Wales . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Mitchell B. R . ( 2003 ), British Historical Statistics . Cambridge University Press . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Morgan N . ( 2014 ), The Heroin Epidemic of the 1980s and 1990s and Its Effect on Crime Trends – Then and Now. Research Report 79 . Home Office . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Natcen. ( 2014 ), ‘ British Social Attitudes 31’ , available online at http://www.bsa-31.natcen.ac.uk/media/38202/bsa31_full_report.pdf Office for National Statistics . ( 2012 ), ‘ Suicides in the United Kingdom1981 to 2012 ’, available online at http://www.ons.gov.uk/ons/rel/subnational-health4/suicides-in-the-united-kingdom/2012/ref-suicides-2012.xls Perchard A . ( 2013 ), ‘“Broken Men” and “Thatcher’s Children”: Memory and Legacy in Scotland’s Coalfields’ , International Labor and Working-Class History , 84 : 78 – 98 . Google Scholar Crossref Search ADS WorldCat Riddell P . ( 1985 ), The Thatcher Government , 2nd edn. Basil Blackwell . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Ryder N. B . ( 1965 ), ‘The Cohort as a Concept in the Study of Social Change’ , American Sociological Review , 30 : 843 – 61 . Google Scholar Crossref Search ADS PubMed WorldCat Ryle G . ( 1949 ), The Concept of Mind . Hutchinson . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Sampson R. J. Raudenbush S. W . ( 2004 ), ‘Seeing Disorder: Neighborhood Stigma and the Social Construction of “Broken Windows”’ , Social Psychology Quarterly , 67 : 319 – 42 . Google Scholar Crossref Search ADS WorldCat Savage M. Burrows R . ( 2007 ), ‘The Coming Crisis of Empirical Sociology’ , Sociology , 41.5 : 885 – 99 . Google Scholar Crossref Search ADS WorldCat Stimson J. A . ( 1991 ), Public Opinion in America: Moods, Cycles, and Swings . Westview Press . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Thatcher M . ( 1993 ), The Downing Street Years . HarperCollins . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Walker A. Walker C . ( 1997 ), Britain Divided: The Growth of Social Exclusion in the 1980s and 1990s . CPAG . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Walker C . ( 1993 ), Managing Poverty: The Limits of Social Assistance . Routledge . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Yitzhaki S . ( 1979 ), ‘Relative Deprivation and the Gini Coefficient’ , Quarterly Journal of Economics , 93 : 231 – 324 . Google Scholar Crossref Search ADS WorldCat 1 The BCS data show that both violent and acquisitive crime peaked between 1993 and 1995. Meanwhile, police recorded crime statistics reveal a similar picture; crime rose gradually in the 1980s, sharply during the early 1990s and has since seen a prolonged fall, mirroring trends in a number of other western countries (Morgan 2014). 2 Similar debates around what scholars and journalists have termed ‘Generation Y’ have emerged; Howe and Strauss (1992) posed a four-fold cycle of generational types and recurring mood eras in American history. Generation Y, also known as the ‘Millennials’ are generally accepted as those individuals born between 1980 or 1982 to 2000, although there are no fixed definitions. Ipsos-Mori have conducted analyses of the British Social Attitudes Survey on the basis of Strauss–Howe generational differences (Duffy et al. 2013). 3 First conducted in 1982, the BCS was commissioned by the UK government to measure the ‘dark figure’ of unreported crime incidents. The survey moved to an annual basis from 2001. As well as collecting information on victimization and fear of crime, it collects information on a range of attitudes towards the criminal justice system, causes of crime and demographic information about respondents. The survey sampling is structured to be representative of two groups, namely residential households in England and Wales, and adults (aged 16 years and over) living in those households (Bolling et al. 2004). The survey does not collect information from those living in residential institutions such as prisons, detention centres, military accommodation, care homes or university accommodation. Its name was changed to the ‘CSEW’ in 2012. See de Castelbajac (2014) for an outline of its origins. 4 The survey focuses mainly on various types of property and acquisitive crime, and physical, sexual and domestic interpersonal violence. 5 The BSA series began in 1983. It is based on an annual random probability, face-to-face survey of approximately 3,000 Britons. The series was designed to act as a counterpart to other large-scale government surveys such as the Labour Force Survey or the General Household Survey, which provide data on behavioural actions and tangible ‘facts’. It has been conducted every year since 1983, except in 1988 and 1992. 6 The Gini coefficient is a quantification of relative deprivation (Yitzhaki 1979). It takes a value of between 0 and 1, where the higher the value the higher is inequality. It is a widely respected measure of inequality in the distribution of household income. 7 The Youth Cohort Study commenced in 1985. It represents a key piece of longitudinal research designed to monitor behaviour of young people as they reach the minimum school leaving age and either stay on in education or enter the labour market. The sample is based on representative samples of young people aged 16 years onwards completing postal questionnaires. 8 Scotland is not covered by the BCS or the CSEW. However, it would be possible to supplement the database with data from the Scottish Crime and Justice Survey, which began formally in 1993 and runs to the present day. It is available through the UK Data Archive and could be used for shorter time-series analysis. 9 The term ‘thick’ description was first used by Ryle (1949) and later by Geertz (1973) who applied it in ethnography. Specifically, these authors highlighted accounts in which the researcher made explicit the patterns of cultural and social relationships and put them into context. 10 For further information on the project, see http://www.sheffield.ac.uk/law/research/projects/crimetrajectories. © The Author 2015. Published by Oxford University Press on behalf of the Centre for Crime and Justice Studies (ISTD). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. © The Author 2015. Published by Oxford University Press on behalf of the Centre for Crime and Justice Studies (ISTD).
TI - Collating Longitudinal Data on Crime, Victimization and Social Attitudes in England and Wales: A New Resource for Exploring Long-term Trends in Crime
JF - The British Journal of Criminology
DO - 10.1093/bjc/azv006
DA - 2015-09-01
UR - https://www.deepdyve.com/lp/oxford-university-press/collating-longitudinal-data-on-crime-victimization-and-social-jocb0Zuw2k
SP - 1005
EP - 1015
VL - 55
IS - 5
DP - DeepDyve
ER -