Crime Data

‘The Early Criminal Record on the Boundary of Entertainment: Thomas F. Byrnes’ Professional Criminals of America and the Spectacle of Criminal Identification’ by Charles F Brackett in (2022) 20(2) Surveillance & Society 157-171 comments

While the proliferation of criminal records has received much recent attention, the origin of the criminal record in the United States itself is relatively obscure. This article examines an episode in the development of criminal record keeping and lateral surveillance in the United States, the publication and reception of Thomas F .Byrnes’ Professional Criminals of America ([1886] 1969). I argue that Professional Criminals of America developed a cultural purchase well beyond its relatively modest circulation. By exploiting anxieties about mobility, anonymity, and the decline of class distinction, Byrnes’ book sold itself as a tool to develop regimes of lateral surveillance, enlisting regular citizens to support the police by spying on one another. 

 Brackett argues 

 The proliferation of criminal records in the US and the resulting handicaps for people who have them are topics of increasing concern for scholars and policymakers (e.g., Lageson 2020; Jacobs 2015). While the stigma of a criminal record has been the subject of extensive study, scholars are only beginning to study the extensive use of records (e.g., Jacobs 2015; Lageson 2020; Thacher 2008). Meanwhile, the emergence of the criminal record in the United States has received almost no sustained study. Drawing on theories of surveillance technology as both practical and imaginary (Cole 2001; Bunn 2012), and testing theories of the emergence of “risk society” and lateral surveillance (e.g., Beck 1992; Andrejevic 2002), I examine Detective Thomas F. Byrnes’ 1886 book Professional Criminals of America ([1886] 1969). Specifically, Byrnes’ entertaining volume, which sold more than ten thousand copies in its first printing (Brooklyn Daily Eagle 1886), merged entertainment with new technologies of crime control and sought to produce a type of lateral surveillance. Byrnes used his own charisma and public fascination with criminality to turn Professional Criminals into a significant cultural object in the turn-of-the-century United States. In doing so, Byrnes ([1886] 1969) sought to introduce a tool that would provide any citizen the information they needed to be their own detective. … 

Late-twentieth and twenty-first century scholarship on security and surveillance has emphasized the supposed emergence of “risk”as a dispositif for the management of diverse populations of people, events, or probabilities (e.g., Foucault 2008b; Bigo 2012). Since the 1980s, a growing body of surveillance and security literature has come to emphasize the role of disembodied data (e.g., Gandy 1983; Lyon, ed. 2003; Haggerty 2001; van Dijck 2014), algorithmic and predictive practices (Aradau and Blanke 2017, 2018), and the technologies of data-driven risk management in both security practices and governance more broadly (e.g., Lageson 2020; Eubanks 2018; Noble 2018). 

Studies of risk often position the rise of risk as a de facto rupture in the social order (e.g., Beck 1992 and Giddens 1990). Briefly stated, risk society theories posit the emergence of a new social form governed less by traditional class conflict and competitive governance than by the technocratic assessment and management of various social risks (Giddens 1998). Or, as Beck(1992: 223) argues, “[p]olitics is no longer the only or even the central place where decisions are made on the management of the political future.” Perhaps the best example of this shift for criminal punishment can be found in Ericson and Haggerty’s (1997) argument that law enforcement’s main function today is the production of data. 

A central aspect of this conceptualization of risk and risk management is the role of state institutions in the production of supposedly objective knowledge. In his study of criminal justice statistics, for example, Haggerty (2001: 191–192) argues that one of the main functions of statistical institutions is their claim to represent “objective rationality.” This formulation is substantively reproduced in multiple examinations of the risk society and the proliferation of risk management practices (e.g., Aradau and Blanke 2017). Challenges to the risk society formulation have tended to critique the claim of newness, both implicitly and explicitly (e.g., Rigakos and Hadden 2001). Others implicitly challenge Beck’s (1992) and Giddens’ (1998) claim to the declining salience and value of contentious politics, for example with a call reexamine the importance of “agonism” in democratic politics (e.g., Mouffe 2005; Wenman 2013). 

Even critical scholars tend to take for granted that risk-based surveillance technologies are founded upon a logic of science and gain legitimacy from their patina of objectivity or rationality. This comes despite a rich trove of research that highlights the important role of spectacle in the growth and legitimization of surveillance. Several scholars have examined the interpenetration of spectacle with surveillance, either in legitimizing surveillance society (Gold and Revill 2003) or spectacular uses of surveillance itself (Kammerer 2012). Scholars including Loic Wacquant (2012), Barry Glassner (2000), and Jonathan Simon (2007) have examined the role of spectacular media coverage of crime and terrorism in legitimizing and expanding surveillance practices. Brucato (2015) has problematized the ideology of “objectivity”in police use of bodycams, while a long social-scientific tradition has focused on the role of charismatic authority (Weber [1919] 1947,[1922] 1946) in legitimacy, as well as problematizing objectivity as a social reality (e.g., Foucault 2013; Galison 2000). 

How we understand the social management of risk and the resultant surveillant practices, then, has much to do with how we analyze the interaction of scientism and spectacle in the framing of both risk and its management. As much as a large insurance company may appreciate the multiplicity of statistics available to manage suspect populations and “dangerous” areas through Big Data, everyday citizens are more likely to frame their relationship to risk through lurid news coverage or the television show 24. 

Further, while the risk society is consistently positioned as a development of Late Capitalism or Neo-Liberalism (e.g., Beck 1992), such a framing threatens to disappear the long history of risk. Scholars from across the political spectrum have pointed to risk’s role in creating capitalism itself, either celebrating (Bernstein 1998), analyzing (Foucault 2008a, or critiquing (Rigakos and Neocleous, eds. 2011) this relationship. 

In examining Thomas Byrnes’ Professional Criminals of America ([1886] 1969), as well as its public reception, then, I seek to frame two basic questions at a micro-level. First, how did Byrnes’ work function as a melding of charisma and scientific authority, and what was its contribution to public acceptance of large-scale data collection?

Cost of Serious/Organised Crime Statistics

The Australian Institute of Criminology report 'Estimating the costs of serious and organised crime in Australia, 2020–21' -

estimates the cost of serious and organised crime in Australia for the 2020–21 financial year. It was not possible to undertake new empirical research to provide accurate baseline data to support the estimated costs. Instead, the most recent reported statistics for individual crime types or public and private expenditure were used as baseline indicators of incidence. The corresponding unit cost estimates were uprated using the RBA (2021) inflation calculator. Where more recent unit cost estimates were available, these were used in preference to uprating to account for inflation. .... 

As indicated above, it is estimated that 6.5 percent of the proceeds of crime actually laundered would be paid as commission to professional facilitators of laundering, representing a loss to the economy. In some cases, proceeds of crime are simply spent on lifestyle, enabling them to remain within the economy. 

Taking into consideration the observations above concerning the problematic nature of making comparisons between cost estimates over time, and bearing in mind changes in the societal influences on crime, changing crime control measures that have been implemented and changes in statistics and estimation methodologies present in current and previous research, Figure 1 presents the total costs of the higher level of serious and organised crime involvement for each loss category in respect of the years 2016–17 and 2020–21. The changes should not, however, be interpreted as necessarily reflecting a change in the net amounts of each cost category as the costing methodologies used have developed over time, and some new crime types have been included and different techniques of estimation applied based on new sources of information becoming available. To indicate how the totals changed between 2016–17 and 2020–21 because of changes in methodologies of measurement, an estimate was made of the higher-level costs presented in Table 21 that related to the counting of new forms of serious and organised crime, not previously counted, and new ways in which costs were calculated. From Figure 1, it is apparent that changes in costing methodologies increased the estimated costs of only some categories of crime. In the case of other crime types, the increase was predominantly due to changes in net actual costs. ...

The additional costs due to changes in methodology and cost categories totalled $8,072m since the 2016–17 estimation was published. The difference between this and the total in Table 21 is $52,049m, which is 9.7 percent more than the total higher-level costs for 2016–17. This is graphically shown in column 3 of Figure 2 along with comparable totals for 2013–14. These are presented as both the total estimated cost as well as the total cost as a percentage of Australia’s gross domestic product (GDP; ABS 2022: Table 36, col H). From Figure 2, the total estimated cost of serious and organised crime has increased by 65 percent since 2013–14, while this cost as a percentage of GDP has increased by 41 percent (or 1.2 percentage points). Between 2016–17 and 2020–21, this increase as a percentage of GDP was only 17.6 percent (or 0.6 percentage points). Nonetheless, the final global estimates indicate the increasing, substantial economic impact of this form of criminality on the Australian economy over time.

The AIC states

This report estimates the cost of serious and organised crime in Australia in 2020–21 to be between $24.8b and $60.1b. This is the third in a series of reports undertaken for the Australian Criminal Intelligence Commission estimating the cost of serious and organised crime. It updates and improves on the methodology used in the previous report, which estimated the cost of organised crime in 2016–17. As with the previous research, this report considers the direct and consequential costs of serious and organised crime in Australia, as well as the costs to government entities, businesses and individuals associated with preventing and responding to serious and organised crime. While the current estimates were undertaken during the COVID-19 pandemic and may reflect changes in criminality resulting from the pandemic, the full economic impact of serious and organised criminal offending committed during the pandemic will not be known for some time. It is clear, however, that the impact of serious and organised crime on the Australian economy is substantial. 

This Statistical Report provides an estimate of the cost of serious and organised crime in Australia for the year 2020–21. This is the third in a series of reports undertaken for the Australian Crime Commission (2015a, 2015b) and the Australian Criminal Intelligence Commission (ACIC; Smith 2018a) and draws on a methodological approach first developed by Mukherjee and Walker at the Australian Institute of Criminology (AIC) in the 1980s to estimate the size and cost of all crime in Australia (Mukherjee et al. 1987). The present study is the eighth iteration of the original cost of crime research design, with each report demonstrating improvements in the scope and sophistication of the methodology. 

Crime, of course, is continually evolving and adapting to changes in society, the economy and the criminal justice system. Since the last report was written (Smith 2018a), Australia and the world have been subject to the global coronavirus pandemic, which has not only affected the health and wellbeing of individuals but also changed the way in which social relations take place and how business and government operate. The pandemic has also provided many opportunities for criminality to occur (Levi & Smith 2021) and, although some of these have been taken up, the full economic impact of offending committed during the pandemic will not be known for some time. 

Accordingly, the estimate of the cost of serious and organised crime for 2020–21 reflects some changes evident in the incidence of crime during the pandemic but is unlikely to show the full impact of such crime identified at the time of writing. It would therefore be inappropriate to attribute any changes in the costs of crime presented in this report, compared with those costs presented in earlier reports, solely to the influence of the pandemic. Further research on individual crime types is required to determine the exact ways in which, and the extent to which, costs have changed from previous estimations. 

As with the previous research, this report examines the direct and consequential costs of serious and organised crime and the costs associated with preventing and responding to serious and organised crime by government entities, businesses and individuals or households. The estimated total cost for 2020–21 was between $24.8b (low), $39.9b (medium) and $60.1b (high) and comprised the following cost categories. 

Direct serious and organised crimes were estimated to cost up to $37.3b in 2020–21. These are crimes that have a clear and direct link with serious and organised crime (eg illicit drug trafficking, human trafficking and organised financial crime). 

Consequential serious and organised crimes were estimated to cost up to $6.4b in 2020–21. These are conventional crimes committed as a consequence of serious and organised crimes. They are crimes that generate funds used to support involvement in serious and organised criminal activities (in particular, the crimes illicit drug users commit to finance drug purchases), crimes that result from involvement in serious and organised crime-related activities (eg violence, sexual assaults and burglaries committed by those using illicit drugs), or conventional crimes committed by organised crime groups (eg organised shop theft) or committed to facilitate serious and organised criminal activities (eg using violence to intimidate businesses or using identity crime to facilitate financial fraud). 

Prevention and response costs were estimated to be up to $16.4b in 2020–21. These include costs incurred by law enforcement, the criminal justice system, other government agencies, the private sector and individuals in the community in preventing and responding to crime. 

Interestingly, the upper estimate of total direct costs, including consequential costs, of serious and organised crime in 2020–21 ($43.7b) was only slightly less than the total recurrent expenditure of all government agencies with some responsibility for serious and organised crime control in Australia in the same year ($45.1b). 

The methodology adopted in this report seeks to estimate costs for the financial year 2020–21. Where data were not available for this period, the Reserve Bank of Australia (RBA; RBA 2021) inflation calculator was used to uprate estimated costs from earlier periods to reflect changes in the cost of living, where appropriate.

CensusFail

Realists don't expect government agencies to be perfect. They do however expect agencies to learn from mistakes. That's a legitimate expectation. It's thus disquieting to see the ANAO report Planning For The 2021 Census, which implies the ABS has not taken on board the lessons of what people identified through the #CensusFail hashtag in 2016. 

The ANAO states 

1. The Census of Population and Housing (the Census), undertaken by the Australian Bureau of Statistics (ABS), is Australia’s largest statistical collection. The purpose of the Census is to accurately measure the number and key characteristics of all people in Australia, Norfolk Island, and the Territories of Cocos (Keeling) Islands and Christmas Island on Census night every five years. 

2. The 2016 Census was the first Census to be ‘digital first’, whereby the ABS sought to obtain 65 per cent of responses through an online eCensus form. On Census night on 9 August 2016, there was a failure of multiple information technology (IT) controls, particularly for the online eCensus form, which resulted in the closure of the Census webpage for two days. 

3. The Senate, the Department of Prime Minister and Cabinet, and the ABS initiated reviews into the events on Census night, ABS governance and the broader implications for cyber security across the Australian Public Service. In total, the reviews made 36 recommendations, 29 of which were directed at the ABS and agreed.

4. The failure of multiple IT controls during the 2016 Census reinforced the need for the ABS to implement robust planning arrangements for the 2021 Census including for cyber security, procurement, and review recommendations. An audit of the ABS’ preparedness for the 2021 Census would provide assurance on whether the ABS is on track to delivering its objectives for the Census. 

5. The objective of the audit was to assess whether the ABS is effectively preparing for the 2021 Census. 

6. In assessing this objective, the following three high-level criteria were adopted: Has the ABS established appropriate oversight frameworks for the Census? Is the ABS taking appropriate steps in developing IT systems for the Census? Is the ABS addressing key Census risks and implementing Census recommendations? 

7. The ABS’ planning for the 2021 Census is partly effective. 

8. The ABS has established largely appropriate planning and governance arrangements for the Census. The risk framework is compromised by weaknesses in the assurance arrangements. 

9. The ABS is partly effective in its development of IT systems for the 2021 Census. Generally appropriate frameworks have been established covering the Census IT systems and data handling, and the procurement of IT suppliers. The ABS has not put in place arrangements to ensure that improvements to its architecture framework, change management processes and cyber security measures will be implemented ahead of the 2021 Census. 

10. The ABS has been partly effective in addressing key Census risks, implementing past Census recommendations and ensuring timely delivery of the 2021 Census. Further management attention is required on the implementation and assessment of risk controls. 

11. The planning and governance arrangements for the Census are appropriate, except that the ABS does not have an overarching plan to coordinate activity plans and enable a clear view of progress against planned activities. 

12. The ABS largely complies with the Commonwealth Risk Management Policy and has established a risk management plan for the 2021 Census. While the ABS has engaged an external program assurer to report to its Census Executive Board, their assurance activities are not well aligned with the identified Census risks. The Audit Committee has not been well positioned to provide consistent risk oversight or assurance on the Census. 

13. The ABS has been implementing largely appropriate project management practices from December 2019. It has established monitoring processes and in July 2020 finalised arrangements to assess and approve changes to the Census project. 

14. The ABS has an efficiency measure for the Census. The ANAO was unable to provide assurance on the validity and reliability of the measure, however, it is consistent with a proxy measure developed by the ANAO from published ABS information. A report by the United Nations Economic Commission for Europe ranks Australia’s cost per capita as just under the average of a group of countries with similar Census methods. 

15. The IT framework that the ABS has established for the 2021 Census is largely appropriate. However, the ABS’ implementation of its IT framework is not complete. The ABS has not established a systematic process for managing risks associated with non-compliance. Census systems do not fully align with the ABS enterprise IT framework giving rise to risks in relation to system integration and compliance with legislation and ABS policy. The ABS has not established a process to mitigate the risk of unauthorised changes being implemented across systems supporting the Census. 

16. The ABS is establishing partly appropriate data handling practices for the 2021 Census. The ABS has designed controls and arrangements to manage risks relating to data quality and protection of privacy. The ABS has not fully implemented controls for managing the quality and protection of 2021 Census data and does not have in place appropriate arrangements to monitor control implementation. 

17. The ABS has established partly appropriate cyber security measures for the 2021 Census. The high-level measures and controls in the ABS’ cyber security strategy for the 2021 Census are sound. However, the strategy has not been fully implemented. 

18. The ABS has established IT supplier contracts that support value for money outcomes. The ABS has largely met key legal requirements for its Census IT procurements of $1 million or more. 

19. The ABS has been partly effective in addressing key Census risks. The ABS has identified, reviewed and reported risk in accordance with its Risk and Issues Management Plan and the broader ABS framework, and has mostly embedded risk management in its key business processes. The ABS has not consistently implemented key risk controls and has not fully assessed control effectiveness as required in its Risk and Issues Management Plan. 

20. ANAO analysis indicates that the ABS’ post-review activities align with 27 out of the 29 agreed recommendations. In the absence of effective governance oversight arrangements to monitor and report on the implementation of recommendations, the ABS does not have sufficient assurance that it has appropriately addressed the identified issues. 

21. Since January 2020, the ABS has been largely effective at monitoring the progress of activities for the 2021 Census. ABS Census projections in 2018 and 2019 were generally ‘on track’. Throughout 2020 the Census has been ‘at risk’. ANAO testing of 17 key tasks indicated that four were reported complete at least three months prior to actual completion. The ABS has accurately reported key activities, decisions and issues to the Minister in a timely manner. Public reporting on progress with the Census is accurate but could cover a wider range of topics.

The ANAO recommendations are -

R no.1   The Australian Bureau of Statistics strengthen its planning and governance arrangements for the 2021 Census by: establishing a high-level plan of the Census integrating the objectives, activities, and their dependencies; and ensuring that the required reporting is provided to the Census Executive Board. 

ABS response: Agreed. 

R no.2   To assist the Australian Bureau of Statistics in complying with section 16 EA of the Public Governance, Performance and Accountability Rule 2014, the Australian Bureau of Statistics: include an efficiency measure in its performance framework; and develop procedures to support the validity and reliability of the existing Census efficiency measure. 

Australian Bureau of Statistics response: Agreed. 

R no.3  The Australian Bureau of Statistics strengthen its IT framework for the Census by: assessing the impact of non-compliance with Australian Bureau of Statistics standard architectures, including the impact on meeting legislative and policy requirements; and establishing appropriate controls for mitigating unauthorised and inappropriate system changes, specifically focussing on developers that have access to migrate their own changes to Census-related systems. 

ABS response: Agreed. 

R no.4  The Australian Bureau of Statistics obtain an appropriate level of assurance that the systems supporting the 2021 Census are meeting legal and Australian Bureau of Statistics policy requirements on data quality and privacy. 

ABS response: Agreed. 

R no.5  The Australian Bureau of Statistics: define timeframes and responsibilities for implementing the 2021 Census Security Strategy and the Essential Eight Uplift Program, especially for areas that are required prior to the 2021 Census; and ensure contracted services meet Australian Bureau of Statistics specific design and cyber security requirements, and performance of security controls are regularly assessed. 

ABS response: Agreed. 

R no.6  The Australian Bureau of Statistics implement its risk controls and regularly and consistently monitor the effectiveness of those controls. 

ABS response: Agreed. 

R no.7  The Australian Bureau of Statistics: establish oversight arrangements to monitor the progress of the implementation of agreed recommendations from external reviews; and assure itself that it has fully implemented all agreed recommendations. 

ABS response: Agreed.

Gig Economy Statistics

Counting gigs: How can we measure the scale of online platform work? by Agnieszka Piasna (European Trade Union Institute Working Paper 6/2020) comments 

The potential transformation of labour markets by the emergence of online labour platforms has triggered an intense academic, media and policy debate, but its true scale remains speculation. Nevertheless, adequate policy responses hinge on a good understanding of dynamics – something that will only grow in importance with the labour market crisis created by the COVID-19 pandemic. With technologically enabled remote work, growing demand for services such as food delivery or care, as well as rising unemployment and the financial strain on many workers, platform work may resume its rapid growth. Therefore, there is a need for good quality data on the prevalence of platform and other forms of precarious work in society. 

This working paper provides a critical assessment of different approaches to counting gigs; that is, estimating the scale of engagement in platform work in the general population. The aim is to examine the main obstacles encountered in previous studies, the reasons for surprising or contradictory results and possible sources of error, but also the lessons that can be learned for future research. This is illustrated with key research in this area, ranging from large projects conducted by national statistical offices to smaller scale independent research, from national to (nearly) global scale.  

Piasna notes 

 Over recent years, the emergence of online labour platforms that use digital technologies to match workers with clients on a per-task basis has sparked an intense debate about their economic and social implications. Research in this area has exploded equally rapidly, primarily in the form of qualitative or case study investigations, on the issues that are most captivating of the imagination, such as algorithmic management, extremely flexible work models, the dismantling of long fought-for worker protections, legal cases or worker struggles (for example, Berg and De Stefano 2017; Drahokoupil and Piasna 2019; Graham et al. 2017; Vandaele et al. 2019; Wood et al. 2019). However, little is still known about the true scale of the phenomenon of platform work which is especially puzzling given that, as opposed to the traditional informal sector, all transactions mediated by online platforms are digitally recorded. Thus, questions on the proportion of workers engaged in platform work, whether they differ from the general workforce and the countries in which they are more common, remain largely unanswered (Codagnone and Martens 2016; Healy et al. 2017). Existing official labour market statistics are not well- suited to measuring the online platform economy as they are generally not sufficiently sensitive to capture sporadic or secondary employment, while they also fail to distinguish it from other economic activities. Ad hoc modules added to national employment surveys tend to use very different questions and are thus difficult to compare, while rare cross-national surveys provide such divergent results that they raise even more questions than they set out to answer (see discussion in Piasna and Drahokoupil 2019). 

This paper provides a critical assessment of the different approaches to counting gigs, seeking to come to an estimation of the scale of engagement in platform work within the general population (see also Piasna 2021). The aim is to examine the main obstacles which have previously been encountered, the factors which explain surprising or contradictory results, and the potential errors involved, but also to explore the lessons learned for future research. This is illustrated with key research studies in this area, conducted by national statistical offices and independent researchers, and on a national and (nearly) global scale. The analysis ranges from various examples of the use of secondary data, produced in abundance by simple virtue of the operations of the platforms, to the collection of primary data through dedicated surveys. It is not an exhaustive review of all the studies carried out to date, but rather an analytical review of various approaches illustrated with a selection of examples. 

The paradox in measuring the platform economy is that, although its opera- tions generate a wealth of data, with all transactions being digitally recorded, one of the biggest unknowns is still the scale of platform work (Codagnone et al. 2016). Every gig mediated by online labour platforms leaves a digital trace containing information such as the nature of the task, the compensation pro- vided, the number of hours worked or tasks completed, and the identity both of the requester or client and of the worker. A good starting point for a review of methods for measuring the platform economy are thus initiatives that have attempted to access such data, either directly from the platforms themselves or by tapping into other sources of big data generated by their operations. 

In general, platforms are highly protective of their proprietary databases on work and compensation flows and thus research that uses such data is scarce. One of the early examples is a study by Hall and Krueger (2018), who used anonymised administrative data from Uber on the number of drivers and their work histories, schedules and earnings covering the period 2012–2014 in the US market. Its strength undoubtedly lies in charting in great detail the extent of work for one of the largest platforms. However, as the study was carried out at Uber’s request and one of the authors worked for Uber Technologies at the time, it remains unattainable for independent researchers to replicate such an analysis over time or in other countries. Another example of the use of administrative data is a study of Deliveroo riders in Belgium carried out by Dra- hokoupil and Piasna (2019). In this case, a rare opportunity to access comprehensive administrative records containing information on hours worked and the pay, age, gender and student status of workers was based on co-operation with SMart, an additional intermediary that hired Deliveroo riders and billed the platform on their behalf. However, Deliveroo ended its agreement with SMart soon after the research was carried out, so such data collection cannot now be repeated. 

Insofar as access to the administrative records of one platform provides the precise number of workers on that particular platform, and usually allows the separation of registered users from active ones, it can serve as a basis for estimates of the size of the platform economy at national level. Nevertheless, such estimates are extremely rough. A complete picture of the platform workforce would require information from all platforms and some indication on the scale of overlap; that is, how many workers are registered on more than one platform (for example, Aleksynska et al. 2019 showed that, among platform workers in Ukraine, only about one-quarter of those registered were in fact active while many were registered on several platforms). As this is currently unattainable, other sources of data can be used to impute missing information. Kuek et al. (2015) complemented the publicly available data disclosed by online labour platforms with expert interviews; while Harris and Krueger (2015) supplemented data from Uber on the number of workers with the fre- quency of Google searches for the names of selected labour platforms. Their approach rested on the assumption that the number of workers providing services through a platform is proportionate to the frequency of its Google searches, even though the latter may be driven by a variety of factors, includ- ing media interest, litigation or academic research, and are likely to be skewed in favour of the most recognised platforms. Nonetheless, Harris and Krueger’s (2015) conclusion that labour platforms accounted for 0.4 per cent of total employment in the US was very close to the results from other studies of that period. 

Digitally mediated transactions also leave records outside the platform, such as in financial institutions or, at least in theory, in tax records. A rare example of the use of tax returns data is a study by Collins et al. (2019), tracing independent work mediated by the 50 biggest online labour platforms in the US between 2010 and 2016. It revealed that, by 2016, about one per cent of the US workforce registered income from platform work, even though it could not, by design, include informal revenues and those falling below a certain threshold. An interesting illustration of the use of financial records is a report by Farrell and Greig (2016) from JPMorgan Chase Institute. Having access to a full database of the clients of a major bank in the US, they counted how many accounts received any payments from one of 30 online platforms (ex- panded to include 128 platforms in a follow-up study by Farrell et al. (2018)). Their analysis revealed that, by 2015, one per cent of adults earned income from online platforms in the current month (0.4 per cent on labour platforms) and 4.2 per cent had done so in the past three years. The clear advantage of such approaches lies in the large number of platforms that can be included in the analysis and the possibility of replicating and repeating measurements over time. However, such studies will miss payments not coming directly from platforms’ accounts (i.e. through PayPal or Amazon vouchers) and, in the case of bank records, produce data not strictly at an individual level as families may have joint bank accounts, also raising ethical concerns where data are used without clients’ explicit consent. 

Another approach to gathering the data produced by platforms, which in principle is not contingent on access to exclusive sources such as banks and does not raise ethical concerns, is web ‘scraping’ – automatically accessing and downloading publicly available data from the platform’s web user inter- face. The most comprehensive initiative of this sort to date is probably the Online Labour Index (OLI) produced by the Oxford Internet Institute (Kässi and Lehdonvirta 2018). The index tracks in near-real time the number of new vacancies (i.e. projects or tasks) posted on five major English-speaking online labour platforms. It is possible to determine from which country the vacancy was posted and in which occupational category it falls, while continuous up-dating of the figures provides a consistent time series. However, as the OLI and other similar projects (see, for example, Ipeirotis 2010) count posted job offers and not the number of workers completing them, they might confuse an increasing fragmentation of tasks for an increase in the size of the plat- form economy. It is also difficult to grasp the actual extent of platform work without information on compensation for posted tasks, as single tasks can vary greatly in the amount of labour input required and pay levels, while some tasks might also be completed by multiple workers. Finally, the authors of the OLI acknowledge that this measure of online labour utilisation is incomplete as it fails to capture all new vacancies, and thus they choose to present it as an indexed trend rather than in terms of the absolute numbers of vacancies. Consequently, while valuable in mapping trends in online gig work and its occupational heterogeneity, the OLI does not provide answers to the scale of platform work. 

Therefore, the use of secondary data generated by platforms’ operations seems a good way to sketch the contours of the platform economy, although it is not best suited for mapping the prevalence of platform work at an individual (worker) level. To investigate how widespread are experiences with platforms, how often and to what extent individuals engage in platform work and the role of this type of work in supporting their livelihoods, a collection of primary data is necessary. ....

Big Data Ontologies

'Big Data, urban governance, and the ontological politics of hyperindividualism' by Robert W Lake in (2017) Big Data and Society comments 

Big Data’s calculative ontology relies on and reproduces a form of hyperindividualism in which the ontological unit of analysis is the discrete data point, the meaning and identity of which inheres in itself, preceding, separate, and independent from its context or relation to any other data point. The practice of Big Data governed by an ontology of hyperindividualism is also constitutive of that ontology, naturalizing and diffusing it through practices of governance and, from there, throughout myriad dimensions of everyday life. In this paper, I explicate Big Data’s ontology of hyperindividualism by contrasting it to a coconstitutive ontology that prioritizes relationality, context, and interdependence. I then situate the ontology of hyperindividualism in its genealogical context, drawing from Patrick Joyce’s history of liberalism and John Dewey’s pragmatist account of individualism, liberalism, and social action. True to its genealogical provenance, Big Data’s ontological politics of hyperindividualism reduces governance to the management of atomistic behavior, undermines the contribution of urban complexity as a resource for governance, erodes the potential for urban democracy, and eviscerates the possibility of collective resistance. 

 

Lake argues 

Data politics dominated newspaper headlines in New York City at the end of 2015. Controversy erupted when a former Police Commissioner charged that the city’s method of collecting crime data underreported actual events. He cited as an example the NYPD’s practice of recording a “shooting” only if a bullet wounds a victim. According to the New York Times account:

 

a shooting … is recorded only if someone is hit …. If a bullet tears a person’s clothing but does not wound the victim, the episode is not included in the Police Department’s official tally of shootings … Gunfire at a car in which the occupants are wounded by shattered glass but not by a bullet is not recorded as a shooting. (Goodman, 2015)

 

As the official in charge of the police department’s CompStat (Computer Statistics) program explained: “‘We need the bullet to cause the injury … and we need blood’” (Goodman, 2015). A follow-up article a few weeks later reported that “the number of murders recorded by the (police) department is almost always lower than those counted as homicides by the city’s medical examiner” (Goodman, 2016). The Police Commissioner defended such practices, saying that “I stand by my crime statistics because they are factual, they are the truth,” while a civil liberties advocate countered that “the controversy highlights just how soft and subjective police statistics can be” (Goodman, 2015).

 

Meanwhile, some 100 miles to the south, in the economically devastated city of Camden, New Jersey, police officials reported a large-scale expansion of that city’s “ShotSpotter” automated gunfire detection system (Adomaitis, 2015). ShotSpotter is described by its corporate provider as “an acoustic surveillance technology that incorporates audio sensors to detect, locate and alert police agencies of gunfire incidents in real time …. The alerts include … the precise time and location (latitude and longitude) represented on a map and other situational intelligence” (ShotSpotter Fact Sheet, 2016). The expanded ShotSpotter system in Camden was part of a larger strategy of augmented video surveillance and data collection designed to reassert the appearance of police control in a city that routinely tops national rankings in the incidence of violent crimes (NeighborhoodScout, 2016).

 

What counts as a “gunshot” in Camden, in many cases, would not register as a “shooting” in New York City. Whereas New York construes a “shooting” in the narrowest possible terms requiring the presence of a shooter, a bullet, and a victim’s blood, Camden’s citywide acoustic surveillance system automatically records every “digital alert” of an “actual gun discharge” as a “gunshot crime in progress” pinpointed in time and space (ShotSpotter Fact Sheet, 2016). These differences between New York City and Camden cannot be separated from their political context. The outcome of mayoral elections in New York City, as well as the city’s attractiveness for residents, tourists, and investors, depends on the public perception of safety and security, exerting downward pressure, in turn, on the practice of collecting and documenting crime statistics. The NYPD’s CompStat program tracks weekly crime data by precinct as a tool for managing organizational personnel and resources but it is equally a tool for managing public opinion (Eterno and Silverman, 2010). In a similar manner but conveying a different message, Camden’s expanded ShotSpotter detection system deploying sensors and monitors in every neighborhood also influences political opinion by establishing a visible police presence throughout the city.

 

A related controversy over categories, exclusions, and measurement erupted over data on New York City’s homeless population at a time when visible homelessness, like crime, had become a political liability for the city’s mayor. The annual homelessness count reported by the U.S. Department of Housing and Urban Development (HUD) in late 2015 found 75,323 homeless individuals in New York City but that number was quickly challenged by advocates for the homeless and HUD acknowledged uncertainty in the “reliability and consistency” of the data (Stewart, 2015a; U.S. Department of Housing and Urban Development, 2015). The ambiguities in the data were manifold. Individuals and families who became homeless through eviction, fire, landlord harassment or other reasons, and were living doubled-up with friends or relatives were not considered homeless by HUD’s definition and were excluded from the count and HUD’s report listed as zero the number of chronically homeless families in New York City not in homeless shelters. Although the city’s Human Resources Administration (HRA) funds 45 emergency and transitional shelters for women and their children forced to flee their homes due to domestic violence, HUD also reported as zero the number of homeless domestic violence (DV) victims in shelters because the DV shelters operated by HRA were considered separate from the homeless shelters operated by the Department of Homeless Services (New York City Department of Homeless Services, 2016). Simultaneously, the Mayor’s Office announced an “unprecedented expansion” in the number of shelter beds for homeless victims of domestic violence to accommodate “a 50 percent increase over the current 8,800 individuals served yearly” (New York City Office of the Mayor, 2015; Stewart, 2015b). Further confounding HUD’s data, HUD’s count of 1706 homeless youth almost certainly underestimated a significant subgroup of the homeless who, advocates said, might exceed 10,000 (Gibson, 2011) but “avoid public places where they could be counted for fear of referral to Child Protective Services and … avoid shelters out of safety concerns” (Navarro, 2015; Stewart, 2015a, 2016).

 

The selective practices of categorization and measurement illustrated in these examples might easily be dismissed as the intrusion of political agendas in the otherwise objective and politically neutral construction of data as, in the words of the NYPD Commissioner, “factual” and “the truth.” If this were the case, a solution might lie in the rationalization and depoliticization of methods of data collection, categorization, and analysis, bringing actual practices into closer alignment with normative claims. The ubiquity of Big Data as a technique of governance, biopolitics, and bureaucratic control, however, has expanded the scope of the problem and amplified the challenge of delineating solutions. My argument in this paper is that the challenge of (and to) Big Data is not confined only to the politicization of its practices but rather is situated in its foundational ontological premises, involving the evisceration of context through an ontology of hyperindividualism. An ontology of atomistic individualism underlies the construction of calculative data in general (Hacking, 1990, 1991, 2006) but the arrival of Big Data, involving the algorithmic production, manipulation, and application of very large datasets, has exacerbated and expanded the scope of the problem by obscuring from critical scrutiny its foundational hyperindividualist ontology.

 

This paper aims at a partial corrective by examining Big Data’s underlying calculative ontology. By ontology I mean “a set of contentions about the fundamental character of human being and the world” (Bennett, 2001: 160) or simply “a theory of objects and their ties” (Theory and History of Ontology, 2016). Specifying Big Data’s “ontological imaginary” (Bennett, 2001: 161) answers the question starkly posed by Wagner-Pacifici et al. (2015: 5) who ask, with respect to Big Data: “Just what is our basic ‘ontological unit?’” or, even more plainly, “What is a thing?” (see also Beauregard, 2015, 2016). Big Data’s “onto-story” (Bennett, 2001: 161) can be briefly summarized in the premise that the world is knowable via calculation and measurement and can be represented as the aggregation of discrete, independent, empirically observable units. These units are the “data points” representing, to list only a few examples, gunshots, homeless people, sociodemographic characteristics, credit card swipes, Internet searches, or geo-tagged locational coordinates captured from smartphones (Goldstein, 2016; Kitchin, 2013, 2014; Wagner-Pacifici et al., 2015; Weber, 1946). This calculative ontology both relies on and reproduces a form of atomistic individualism in which the ontological unit of analysis is the discrete data point, the meaning and identity of which inheres in itself, preceding, separate, and independent from its context or its relation to any other data point.

 

By the hyperindividualism of Big Data, I refer to the practice of disaggregation and reaggregation that proceeds through a multistep process of interconnected and interdependent constructions of the world. Big Data’s ontological imaginary involves (1) the division and disaggregation of data fields (“variables”) into ever-smaller units measured at ever finer-grained levels of resolution, (2) the practice of counting each individual observation as an autonomous unit—a thing-in-itself—extracted from and independent of its context, and (3) the reaggregation and recontextualization of the resultant data “bits” through the automated algorithmic search for statistical patterns and correlations hidden within the dataset. While an ontology of atomistic individualism underlies calculative practices in general, the diffusion of Big Data both relies on and produces a form of hyperindividualism of an unprecedented scope and scale. The hyperindividualization of Big Data results, first, from the hyperdisaggregation of data fields in what Kitchin (2014: 2) describes as the production of “massive, dynamic flows of diverse, fine-grained, relational data” recording and counting, for example, Internet transactions, selected words within social media posts, demographic “variables,” real-time spatiotemporal registers, and so on, where the identity or meaning of each data point is self-evidently and inherently given as a thing-in-itself divorced from its context. That hyperindividualization permits, second, the reaggregation and intercorrelation of data observations to construct new observations and “facts,” the meaning of which is based on, imposed by, and imputed from the discursive categorical labels in the data table rather than from the meaning residing in the lived experience of the original units of observation.

 

Consideration of Big Data’s ontology of hyperindividualism moves beyond epistemological debates over definitions, categorizations, data collection methods, and data accuracy. The interrogation of such matters derives from an internal critique of Big Data’s ontological framework while adopting and remaining within its ontological assumptions and focusing on problems of operationalization and implementation, that is, on problems of method (Lake, 2014). Motivating such internal critique is the belief that better (i.e. more accurate, consistent, objective, or comprehensive) methods of data collection, aggregation, and analysis will produce better knowledge. Beyond merely addressing internal operational mechanics, however, internecine conflicts over the “how” of Big Data have constitutive effects. By performing and naturalizing Big Data’s ontological assumptions, debates over what gets counted, through what methods, via what algorithms (Kwan, 2016), and despite what omissions and (mis)categorizations reproduce its foundational premises while deflecting attention away from a critical assessment of those underlying principles (Zaloom, 2003). The practice of Big Data governed by an ontology of hyperindividualism is also constitutive of that ontology, naturalizing and diffusing it through practices of governance and, from there, throughout myriad dimensions of everyday life. The challenge for governance is that problems inherent in the ontology underlying a practice cannot be resolved by altering the practice but must be addressed at the level of foundational ontological assumptions. Changing those ontological assumptions, however, destabilizes the entire edifice of practice built up on the prior underlying foundation that allowed the politicization of data construction to proceed in the first place. As Garfinkel observed, there are often “‘good’ organizational reasons for ‘bad’ clinical records” (Garfinkel, 1967: 186). Resistance to change on the part of interests invested in those current practices (e.g. the police or the mayor) all but guarantees the preservation of the status quo.

 

My purpose in this paper, accordingly, is to consider the implications for governance of Big Data’s ontology of hyperindividualism. Rather than taking Big Data’s ontological assumptions as the starting point of the analysis, however, my concern is to sketch a brief genealogical account of their emergence. A genealogical narrative understands practices (and their consequences) as situated in the confluence of the circumstances from which they emerged (Foucault, 1984; Hacking, 1991; Nietzsche, 1913). “History matters,” Trevor Barnes (2013: 298) reminds us, but, unlike history’s search for origins or causes, a genealogical approach problematizes the given-ness of Big Data’s ontological premises by unraveling and exposing their contingent emergence. Focusing on emergence rather than origins helps, as Jane Bennett (2001: 11) observes, to “counter the teleological tendency of one’s thoughts.” For Colin Koopman:

 

Genealogical problematization … provokes a question by rendering the inevitable contingent ….A genealogy also shows us how that which we took to be inevitable was contingently composed. A genealogy does not just show us that our practices in the present are contingent rather than necessary, for it also shows how our practices in the present contingently became what they are. The history of that which was once presumed inevitable not only makes us forget the inevitability, it also provides us with the materials we would need to transformatively work on that which we had taken to be a necessity. (Koopman, 2011: 545)

 

In the remainder of this paper, therefore, I explicate Big Data’s ontology of hyperindividualism as a radical extension of atomistic liberal individualism and I contrast it to a coconstitutive ontology that prioritizes relationality, context, and interdependence. I then situate the ontology of hyperindividualism in the longue durée of its genealogical emergence, drawing primarily from Patrick Joyce’s (2003) history of 19th-century liberalism and John Dewey’s (1929, 1935) pragmatist account of individualism, liberalism, and social action. In the concluding section of the paper, I consider the implications for governance of Big Data’s ontological politics of hyperindividualism. While Big Data’s hyperindividualist ontology extends throughout its applications in information technology, I focus here on the ways in which that foundational ontology affects the definition of urban problems, the dynamics of urban politics, and the practice of urban governance in the age of Big Data.

Legal Aid Data Crunching

Apples, oranges and lemons: The use and utility of administrative data in the Victorian legal assistance sector by Hugh M. McDonald, Cosima McRae, Nigel J. Balmer, Tenielle Hagland and Clare Kennedy for the Victoria Law Foundation (2020) comments

‘Evidence based decision making,’ the idea that policy should be informed by rigorously established objective evidence, has become a mantra around the world for both policy makers and service delivery agencies, and no less in Victoria. In the interviews for this project, we encountered an enormous appetite for data and evidence – both from funders and frontline services. Everyone recognises the value it can deliver in efforts to improve access to justice for Victorians.  

In this regard, administrative data is low hanging fruit. Agencies collect it already so it is inexpensive; it is as close to a universal impression of service use as we’re likely to get; and there is often years of data which can be mined for trends and change. Used effectively, service providers get a reliable picture of where the dollars go: who they helped, in what ways, and their responsiveness to change over time. It can be forged into a valuable tool for government and other funders to develop a more sophisticated understanding of legal need and effective responses. So maximising the utility of administrative data makes patent sense.

 This is not what we found. Despite willingness, there were significant issues with accuracy and consistency of data, and barriers in collection and use – inadequate and/or numerous data systems; diverse data requirements for different stakeholders; inconsistent recognition of the value of data collection; mixed staff capability; and for many, a wicked tension between spending tight resources on frontline services and investing in data systems and practice. 

One size never fits all, and different organisations have different data needs, but higher levels of accuracy and consistency would benefit everyone, most particularly Victorians in need of legal assistance.

The report states

What is administrative data? 

Administrative data is information collected and stored as part of the everyday functions of organisations, commonly providing a record of activities, such as the number and types of services. However, it can provide far more than a simple record of transactions, making an important contribution to research and policy. In the legal assistance sector, it has the potential to answer critical access to justice questions. Governments use administrative data to monitor performance against policy objectives, to understand what works in service delivery, and to capture client and service outcomes. Policy makers and researchers globally increasingly appreciate how administrative data can be used as a tool to understand complex social policy settings. Service providers also demand more from their administrative data, as they seek information to help design more effective and efficient services. 

Using administrative data comes with challenges, but also distinct advantages. Administrative data can reveal valuable real time insights into clients or service users and the outcomes services achieve. It can monitor change over time, gather insights on sensitive issues, and capture diverse, often hard to reach subgroups of the population. Since it already exists in organisational and institutional records, using administrative data reduces the burden and cost of additional data collection complements other research methods. 

This report 

To date, the data collected by the Victorian civil justice sector has not been systematically explored. To unlock the potential of administrative data, we must first understand what data exists, in what form and quality, and how it is currently used. The Victoria Law Foundation Data Mapping Project looks at three branches of the Victorian civil justice system: the legal assistance sector; courts and tribunals; and alternate dispute resolution and complaint mechanisms. The aim is to explore civil justice system data and its context. This is a foundational step in understanding its availability, suitability and utility in answering access to justice questions. 

This report details findings from Stage 1, examining the administrative data collected by Victoria’s public legal assistance sector. Specifically:

• what administrative service data is collected 

• the quality of that data – its accuracy and consistency 

• how the legal assistance sector uses administrative service data, and what they want to be able to use it for. 

This was done by interviewing representatives from 29 legal assistance organisations across Victoria, including community legal centres, Victoria Legal Aid and Aboriginal legal services. Other materials, such as client intake forms, were also collected and analysed; and interview responses and collected materials were analysed using qualitative techniques. 

Data inconsistency and inaccuracy 

Data collection and practices across Victoria’s public legal assistance sector varied considerably. Variable data practice was not always a bad thing. There were several examples of strategic, innovative and agile data practices within participating organisations. However, between organisations, what and how data was collected and what systems and practices were used was inconsistent. There was also evidence of broad quality issues, with a minority of participant organisations confident that their data was highly accurate. This inconsistency and inaccuracy preclude credible sector-wide use of administrative data. 

Basic data elements were treated inconsistently. For example, data collection differed on how key demographic and service features were measured and recorded. Inconsistent data practices extended to who entered data and when; how comprehensive entry was; whether and how data entry was checked; as well as the interpretation and application of data standards. Variations meant core components of the legal assistance sector’s administrative data, such as client demographics and services delivered were not consistently recorded. 

Data utility is undermined by poor quality data. Sector-wide legal assistance data will include inaccurate, inconsistent and missing data, which is masked in large aggregated datasets. Inconsistent data and data practice means comparing apples to oranges, with confidence in sector-wide administrative data analysis and comparison misplaced. Inaccurate data introduces lemons, further undermining data utility. Inconsistent and inaccurate data is like trying to compare apples, oranges and lemons. 

Despite efforts to improve legal assistance sector data accuracy and consistency in response to successive reviews and inquiries, the findings show that data quality deficiencies remain. Moreover, investment in improved data and data capability in one part of the sector may be undermined by poor data and practices in another. 

Data use and database limitations 

Individual organisations were using administrative data for a range of functions: to report to funders; make submissions to government and inquiries; plan services; conduct research; and to evaluate services. Many participant organisations had a sound understanding of data strengths and weaknesses, and knowledge of how practices varied amongst organisations. 

There was widespread evidence of administrative data being used in pragmatic and useful ways, including to learn more about clients, services and communities, and to better respond to legal and other need. 

This included collecting data that went beyond reporting requirements, often to monitor and evaluate specific projects or programs, or more fully capture clients’ legal and related needs. However, this data was often collected in discrete spreadsheets rather than using the organisation’s main data system. This was a rational response to database limitations, but typically meant such data was not readily available for broader analysis, resulting in missed opportunities for shared learning from such efforts. 

Some data systems were difficult to modify and interrogate, and legal assistance organisations expressed frustration with their rigidity. Several Victorian legal service providers had recently invested in new data systems and human resources to provide more functionality and meet organisational need. 

Data demands and capability 

Reporting to funders and governments placed a substantial burden on organisations. On average, participating organisations had nine funding streams with separate reporting requirements. Reporting requirements also changed frequently, creating further challenges. The data capability of legal assistance organisations varied significantly, often as a function of size of organisation, with evidence of polarisation in capability. There were several participating organisations which had embarked on innovative service provision and associated data work, including improved monitoring, evaluation and data-led service planning and design. Others had limited time for data beyond compulsory reporting. 

More generally, organisations reported demands for data without commensurate resourcing. Organisations explained that funding for frontline services was more readily available than funding for back-end operations, such as data practices. For some, allocating resources to back-end data and other operations came at the expense of frontline service delivery. For many of these services, this made such allocation impossible. The single biggest barrier to responding to data demands and improving data capability was a lack of dedicated funding and infrastructure to support data practices. 

Capturing complexity and the value of legal assistance 

Participating organisations reported that the administrative data currently collected did not fully gauge the value of work, failing to adequately capture the complexity of clients and matters. Simple service counts did not capture the relative effort required to meet some clients’ legal needs. There was a broad consensus that measuring the impact of legal assistance services was complex and difficult to achieve with available administrative data. 

There was widespread interest in measuring outcomes, broadly defined as a means to demonstrate individual and collective impact. Participants could point to outcome measurement frameworks, which examine the range of contributions legal assistance services might make, but also to the challenges associated with measuring these contributions. Not all outcomes are equally easy to capture, and several barriers were cited, including difficulty defining outcomes, data quality, implementing measures in diverse settings, limitations of data management systems, and the resources required for data collection and analysis. 

There were also broader questions regarding the methodological limits administrative data in measuring outcomes, and the need for complementary research methods to successfully quantify impact. 

A way forward 

A worldwide shift in access to justice policy, from ‘top-down’ institutional perspectives focused on legal problems involving formal processes, to ‘bottom-up,’ focused on the ability of individuals to resolve problems, requires review of the utility of different models of legal assistance services. Where policy shifts, reshaping service priorities and models, data systems and practices must keep pace and shift accordingly. This means that the data foundations need to be sound. At present administrative data fails to meet its potential, though findings indicate a number of ways forward: • Quality data requires standards, protocols and infrastructure in order to get the basics right. Data quality frameworks can assist in this. The movement to measure outcomes places a further premium on data consistency and accuracy. This includes the need for modern, fit for purpose data management systems that reflect the work of services, and meet data collection, reporting, outcome measurement and policy needs. • Quality data requires leadership, collaboration and coordination to marshal and foster cross-sector development. Building a quality evidence base needs strategic thinking and commitment to drive improved data culture and practice. Governments, funders and service providers need an agreed direction of travel and the realistic means to get there. • Quality data requires investment in people and time, in resources and capability. Without funding, building data capability and practices comes at the cost of frontline legal assistance service capacity, presenting an unacceptable dilemma. There is work to be done, but unlocking the potential of administrative data can have wide ranging benefits for governments, funders, policy makers, legal assistance service providers, and ultimately Victorians with civil justice needs.

The Federal Tax Court and an Automation Tax

'The Gatekeeper Court: For the Revenue or for the Taxpayer?' (University of Melbourne Legal Studies Research Paper No. 828, 2019) By Rachel Davies and Miranda Stewart comments

Since its establishment, the Federal Court of Australia (“the Court”) has become the leading tax court in the nation. The Federal Court is the final port of call for most taxpayers and for the Federal Commissioner of Taxation. In the spirit of inquiry into the nature of “income” for tax purposes, this paper does both a “wide survey and an exact scrutiny” of aspects of the Court’s record in taxation matters over the last 40 years. The paper presents statistics about tax cases in the Court since its establishment in 1977 and discusses trends. We then turn to discuss important themes in tax cases before the Court, including the boundaries of ordinary income and allowable deductions; the complexity of the tax statute and of the task of statutory interpretation; and the approach of the Court to tax avoidance. Finally, the paper considers some features of tax litigation in the Court and challenges for the future.

'Taxation of Automation and Artificial Intelligence as a Tool of Labour Policy' (SMU Centre for AI and Data Governance Research Paper No. 2019/01) by Vincent Ooi and Glendon Goh argue

Rapid developments in automation technology pose a risk of mass displacement of human labour, resulting in the need to support and retrain displaced workers (a negative externality). We propose an “automation tax” that would slow the adoption of automation technology in appropriate circumstances, giving workers and social support systems time to adapt. This could be easily implemented through changes to the existing schedular system of depreciation/ capital allowances, reducing the uncertainty of its application and implementation costs. Such a system would be flexible enough to keep up with rapid technological developments. Two main dimensions may be adjusted to produce intended distortionary effects: 1) accelerated depreciation, and 2) bonus depreciation. While the benefits of efficiency gains mean that the automation tax is unlikely to have widespread application, it does provide a useful tool for specific situations where the rate of automation needs to be slowed due to its resultant social costs.

'Navigating the 4th Industrial Revolution: Taxing automation for fiscal sustainability' by Bronwyn McCredie, Kerrie Sadiq and Ellie Chapple comments 

The 4th industrial revolution has arrived. But this industrial revolution is unlike those witnessed in the past that saw advancements through manufacturing and trade accompanied by higher standards of living for many. Equal opportunity and growth have been replaced by the 21st century trend of rising inequality, in which advancement through digitisation and automation brings fortune to the few and threatens to leave the rest behind (Weyer, 2016). As a result, current tax systems are under pressure with displaced workers requiring support, and the fiscal purse, which has historically been funded by income taxes, being eroded due to a decreasing number of workers to tax. Conceivably, it is up to Governments to address this ‘double negative effect’, but how and from what theoretical basis does it do so? 

This paper presents a theoretical basis and three alternate models for taxing automation: a pigouvian tax; a tax on economic rents and an appreciation tax. Each of these models is evaluated alongside a discussion on the shift in global tax policy from taxing income to taxing capital. This paper argues that this shift is necessary to reduce inequality and to ensure even the lowest common denominator is provided for, for we are the 99%.

Discrimination

'Does the Crown Court Discriminate Against Muslim-Named Offenders? A Novel Investigation Based on Text Mining Techniques' by Jose Pina-Sánchez Julian V Roberts and Dimitrios Sferopoulos in (2018) The British Journal of Criminology comments

Most research in sentencing discrimination in the United Kingdom has relied on aggregate analyses comparing disparities by ethnic group. These studies fail to consider differences in the individual characteristics of the cases processed. To circumvent the lack of official data, we scraped sentence records stored in a commercial website, from which a sample of 8,437 offenders sentenced to custody in the Crown Court from 2007 to 2017 was generated. Using the names of the offenders, we have been able to classify 8.6 per cent of our sample as having a traditional Muslim name. We find that Muslim-named offenders received sentences 9.8 per cent longer than the rest of the sample. However, this difference disappeared once we accounted for the type of offence and other key case characteristics. 

 The authors argue

Is there evidence of discrimination at sentencing in England and Wales? The 2017 Lammy Review has provided a timely reminder of the need for more—and better—research into the criminal justice treatment of racial, ethnic and immigrant minorities in England and Wales. A significant body of research addresses the differential impact on these groups at all stages of the criminal process (e.g. Chigwada-Bailey 2003; Hood et al. 2003; Cole and Wardak 2006; Earle 2011; Phillips 2012; Phillips and Bowling 2017; Irwin-Rogers 2018). Sentencing—the most visible and symbolic stage of that process (Ashworth 2010)—has been subject to far less academic scrutiny. The most significant study of race and sentencing is now over a generation old (Hood 1992). Since then, empirical research has been intermittent,1 with the Ministry of Justice undertaking much of the work on this topic. As part of its section 95 duties, the Ministry of Justice publishes annual statistics relating to race and criminal justice, including sentencing (e.g. Ministry of Justice 2017). These reports provide bivariate statistics, highlighting relationships between race and sentencing outcomes, but are unable to control for relevant case characteristics that might explain those relationships. 

The Lammy Review demonstrated racial disparities in sentencing outcomes for certain offence categories. More specifically, the review reported that within drug offences the odds of a prison sentence were 240 per cent higher for defendants who self-identify as Black, Asian or Minority Ethnic (BAME) compared with White defendants. The review’s analysis took some relevant case characteristics into account. For example, previous convictions and plea were considered, but not other mitigating or aggravating circumstances or indeed the possibility that BAME drug offenders had been convicted of more serious drug crimes (see Hopkins et al. 2016; Lammy 2017: 33). Regrettably, the Lammy Review failed to conduct or commission original empirical research, which might have accounted for other relevant case characteristics. Nor did the review draw upon existing databases that could have helped answering the key question of whether and to what extent racial minorities are treated differently. 

The Ministry of Justice biennial report ‘Statistics on Race and the Criminal Justice System’ has consistently documented sentencing differentials between BAME defendants and White defendants accused of the same offence. The most recent Ministry report (2017) found that BAME defendants had a higher custody rate than White defendants. In addition, since 2012, the average sentence length has been consistently longer for all non-White ethnic groups. In 2016, of all offenders sentenced to immediate custody, Black and Asian offenders received an average sentence length of 24 and 25 months, respectively, compared with 18 months for White offenders (Ministry of Justice 2017: 53). These disparities are cause for concern (see The Secret Barrister 2018: 285). However, they do not constitute incontrovertible evidence of discrimination at the sentencing stage since we do not know whether the differential outcomes can be explained by legally relevant factors2 (Green 1961; Hall and Simkus 1975; Raynor and Lewis 2011; Pina-Sánchez and Linacre 2016) such as those determining the harm of the offence or the culpability of the offender. If for example, BAME defendants were less likely to plead guilty—as suggested by Thomas (2010) and Hood (1992)—we would expect to see differences in sentencing outcomes, all other characteristics being equal. 

This methodological challenge is not new. In 1987, Zatz described the comparison of group means as an obsolete approach to investigate sentence disparities. Multivariate approaches are superior when it comes to detecting the presence of discrimination in sentencing. These methods can be used to control simultaneously for the relevant aggravating and mitigating factors present in different cases, which is key to be able to distinguish legitimate disparities in sentencing from truly discriminatory practices. Hundreds of such studies have been conducted in the United States, with regression modelling being the predominant method of choice (Baumer 2013). In the United Kingdom, however, official sentencing data have traditionally been presented in an aggregated format, precluding the use of regression modelling techniques. In response to critics,3 the Ministry of Justice released a large data set of 1.2 million cases sentenced from 2007 to 2011 at the magistrates and Crown Courts.4 These individual cases included some important demographic characteristics of the defendant, such as age, gender and ethnic group; however, they did not contain any relevant case characteristics other than the broad offence type, thus preventing researchers from differentiating between warranted and unwarranted disparities.

Art Economics

The detailed Making Art Work: An economic study of professional artists in Australia by David Throsby and Katya Petetskaya for the Australia Council for the Arts comments

This survey is the sixth in a series carried out over more than 30 years at Macquarie University, with funding from the Australia Council. The surveys have thrown light on the ways in which professional arts practice has been changing over time. The development of the internet and digital technologies have transformed not only the ways in which artists can participate in the international art world and the global economy, but also the very processes of artistic creation. At the same time, employment conditions for artists have been changing radically, with increasing insecurity in contractual arrangements, and the replacement of steady employment with the emerging concept of the portfolio career, characterised by a variety of work arrangements. Nevertheless, there is also a sense in which nothing changes. The fundamental processes of creativity, the pursuit of an artistic vision and the passionate commitment to art that characterises art professionals—these things remain at the heart of what it is to be a practising artist. For many artists the real challenge is to keep hold of these core values in such a rapidly changing environment.

The survey is concerned with serious, practising professional artists. The seriousness is judged in terms of a self-assessed commitment to artistic work as a major aspect of the artist’s working life, even if creative work is not the main source of income. The practising aspect means that we confine our attention to artists currently working or seeking to work in their chosen occupation. The term professional is intended to indicate a degree of training, experience or talent and a manner of working that qualify artists to have their work judged against the professional standards of the relevant occupation. 

The survey covers both full-time and part-time artists; employed and self-employed artists; and artists regardless of whether all, some or none of their income comes from art practice. It identifies artists according to their principal artistic occupation (PAO), grouped into eight occupational classifications: writers; visual artists; craft practitioners; actors and directors; dancers and choreographers; musicians and singers; composers, songwriters and arrangers; community cultural development artists (formerly known as community artists or community cultural development workers). The survey does not cover film-makers or interior, fashion, industrial or architectural designers. In previous surveys, as in the present one, a number of Indigenous artists working in urban and regional locations are picked up in the sampling procedures. But it has always been a matter of concern that the surveys have not been able to include Indigenous artists working in remote and very remote areas of Australia. Fortunately this longstanding shortcoming in coverage of Australian artists is now being overcome; a national survey of Aboriginal and Torres Strait Islander artists in remote communities is underway at present on a region-by-region basis, undertaken by the Macquarie University research team.

The artist population 

Estimates of the population of artists in Australia depend on the definitions adopted. If attention is focused on practising professional artists according to our own definition, the size of the population is estimated at just under 50 thousand.

Looking at trends in numbers over recent years, we note that during the 1990s the artist population grew substantially but thereafter remained reasonably steady. In the most recent period, total numbers have increased, rising by about 10 percent in total over the past seven years. Over this time we estimate that the numbers of actors, writers, dancers and musicians have continued to grow, while the numbers of craft practitioners and community cultural development artists appear to have declined.

Demographics

On average, artists are older than the labour force as a whole; among artistic occupations, writers are the oldest and dancers are the youngest. The population of artists is divided approximately equally between men and women, unlike the labour force, which has a higher proportion of males. Most artists (75 percent) were born in Australia, and there is a lower proportion of persons from a non- English speaking background among artists (10 percent) than among the wider workforce (18 percent).

In broad terms the family circumstances of artists parallel those of the labour force as a whole, although the largest group—artists living with a partner and with no dependent children—is proportionately greater in size than for the labour force (42 percent compared to 34 percent). Almost three-quarters of Australian artists reside in a capital city, reflecting the fact that major metropolitan centres are where arts infrastructure tends to be concentrated.

Education and training

Overall, artists are more highly educated than the workforce at large; just over three- quarters of them hold a university degree, compared to only 22 percent in the wider labour force. Beyond their general education, many artists have undergone specific training in their artform or in a related artform—about three-quarters have had formal training and 56 percent have had private training of some sort. Almost two-thirds identify self-teaching and/or learning on the job as avenues for their arts training. Among the various training experiences that artists have undergone, just under 40 percent see formal training as the most important type, and 23 percent refer to learning on the job as their most important pathway.

Obtaining a basic qualification to become an artist takes six years on average, and is often not the end of training; many artists continue to engage in advancing their education and training throughout their career. Most artists acknowledge that they improve their skills through self-education and learning on the job. Some seek new skills in another artform to extend their creative range. Others may enrol in refresher courses or workshops to maintain or enhance their skills. Overall, lifelong learning may perhaps be a stronger reality in the arts than in many other professions.

Career progression

In the overall population of practising professional artists in Australia, around 60 percent can be identified as “established”, with the remaining either “starting out” or “becoming established”. Almost all established artists can identify a single moment at which they felt they had gained established status; the moment most often nominated was “my first big professional engagement; my poem/ novel/play/script/composition published/ performed/ produced; my first solo show/ exhibition”, identified by one-third of artists.

Factors that might work to advance an artist’s career, can be classified as intrinsic—those factors that are personal to the artist, or extrinsic—factors that arise from external circumstances. For example, intrinsic factors include an artist’s talent, motivation or self- belief, whereas extrinsic factors include support from family and friends, recognition by others, financial assistance or a lucky break that just happens at the right time. Respondents to the survey identified the personal qualities of persistence and passion in approximately equal measure as the most important intrinsic factors advancing their careers, whilst support and encouragement from others was the most important extrinsic factor.

In regard to negative influences, the great majority of artists point to economic factors such as lack of financial return from creative practice, lack of work opportunities, and lack of time to do creative work due to other responsibilities, as the most important factors holding back their professional development. It is notable that, in contrast to the factors advancing an artist’s career, all of these inhibiting factors are extrinsic.

The multi-talented artist

Artists show considerable versatility in the range of work they have been engaged in within their own artform during their careers. Moreover many artists do not confine their creative work to a single artform, but cross over into other areas of artistic practice. For example, our data show that many actors have had experience in writing or singing, and many community artists have been involved in acting, directing or writing. There is some evidence, in comparison with previous survey data, that the extent of cross-artform engagement has been increasing over time, especially among performing artists.

Although the contribution of Australian artists to our cultural life is widely recognised, the enormous breadth and depth of output of Australia’s professional artists is not always fully appreciated. Our data demonstrate the range of achievements of artists—much of this work meets the highest professional standards appropriate to their respective artforms. About 60 percent of artists have had a professional engagement interstate. In addition, just over 40 percent have had their work seen overseas, helping to advance international recognition of the Australian arts.

Patterns of working time

In analysing artists’ allocation of their working time, we make the now standard distinction between three types of work: creative work, arts-related work (primarily teaching), and non-arts work. From our data it appears that artists consistently spend about 55–60 percent of their working time on creative work, about a quarter of their working time on arts-related activities, and the remaining 20 percent on non-arts work.

On average we find that artists are currently working a 45-hour week, about half of which is devoted to creative work in their PAO. Overall, artists spend on average 28 hours on creative work of various sorts, nine hours on paid arts-related work and eight hours on paid non-arts work.

About one-quarter of a professional artist’s time on average is spent on arts-related work, which uses the artist’s creative skills and artistic knowledge either directly or indirectly. The overwhelmingly most common form of arts-related work is teaching, mostly in the artist’s own artform but occasionally crossing into another artform; on average 70 percent of artists across all artforms who are engaged in arts-related work do so through teaching.

Not all artists are able to work in the arts full-time. In fact our data show that only 56 percent of artists spend all their working time at arts work (creative plus arts-related), and many fewer (23 percent) spend 100 percent of their time solely at creative work. The data show that two-thirds of artists would like to spend more time at their creative practice, and one-third is happy with the way things are.

Among those who would like to spend more time at their creative practice, the problems preventing them from doing so are overwhelmingly related to their economic circumstances. These include the lack of available work (which is especially true for performing artists), inadequate financial return for work sold (affects visual artists, craft practitioners, and community artists), and insufficient markets (as may be a problem for writers, visual artists, craftspeople, and composers).

Income and expenditure

In the financial year 2014–15, Australian practising professional artists earned average gross incomes of $48,400, comprising $18,800 in creative income, $13, 900 in arts-related income, and $15,700 in non-arts income. The distribution of incomes is heavily skewed towards the lower end; our data indicate that about 60 percent of artists make less than $10 thousand per year on average from creative work, and even when all earned income sources are accounted for, there are still around 20 percent of artists who make less than $10 thousand in total. At the other end of the income scale, only 13 percent of all artists made more than $50 thousand from their creative work in 2014–15. From our data it is clear that artists’ income from creative work in their chosen profession is far below that earned by similarly qualified practitioners in other professions. Even when other arts-related earnings and non-arts income are added in, the gross incomes of artists are substantially less than managerial and professional earnings. Indeed their total incomes on average are lower than those of all occupational groups, including non- professional and blue-collar occupations.

We also find that although artists on average in 2014–15 spent almost 60 percent of their working time at their creative activities, they earned only 39 percent of their total income from this source. By contrast the 19 percent of their time that they devoted to non-arts work earned them one-third of their total income.

About half of the artists who live with a spouse or partner regard that person’s income as “important” or “extremely important” in sustaining their creative work. We note that 59 percent of female artists who have a partner regard the partner’s income as important, extremely important, or essential in supporting their creative work, compared to 39 percent for male artists.

Estimating the costs attributable to artists’ creative work is difficult, particularly because of problems in allocating some cost items to specific activities. Bearing these difficulties in mind, we estimate that on average artists incurred just over $10 thousand in 2014–15 in expenses related to their artistic practice.

We can identify some trends in artists’ incomes over recent years by reference to the results of earlier surveys. We find that between 2000–01 and 2007–08, the incomes of artists remained relatively stable in real terms. However it appears that over the period 2007–08 to 2014–15, creative incomes have declined by almost 20 percent in real terms, despite the fact the proportion of time artists devote to creative work has remained roughly the same. Nevertheless other components of income have either increased or not declined as much, meaning that artists’ total earned incomes have declined by only about four percent, or less than one percent annually, over this period. Overall, however, we conclude that professional artists in Australia have not shared in the real earnings growth that most occupations have enjoyed in recent years.

Employment and financial security

About four in five artists (81 percent) work as freelance or self-employed workers in their principal artistic occupation; this represents an increase of more than 12 percent since the survey, and is a continuation of a long-term trend. The majority work as unincorporated individuals, with an ABN, and receive their income as contracts for fixed amounts. In arts- related and non-arts work, the proportions working as freelancers are smaller (40 and 26 percent respectively).

Just under half of all artists are members of a superannuation scheme with an employer. Others have some other means of providing for their future financial security such as personal savings or investments, or support from a partner or family. The numbers without any arrangements have fallen dramatically since the previous survey, from 14 percent then to five percent now. Nevertheless it is worrying that four out of ten artists across the board do not consider their arrangements to be adequate.

In regard to unemployment, one-quarter of artists experienced some unemployment in the last five years, but this proportion has been declining—from 34 percent for the period between 1996 and 2001 and 28 percent for the period between 2004 and 2009. Fewer than half the artists who experienced unemployment between 2010 and 2015 applied for benefits Out of those who did, almost all were successful. But only about one-third of these artists were able to continue their arts practice as an approved activity. At least a quarter of all artists who applied for unemployment benefits encountered problems in accessing these benefits specifically because of their occupation.

Professional practice issues

Overall, 30 percent of all artists use an agent, gallery or dealer to promote their work, with the highest proportion among actors. Regardless of whether artists are using an agent, manager or gallery dealer, almost three- quarters of them state that they are themselves the most active promoter of their work.

About half of artists believe their business management skills to be good or excellent, but more than one-third of artists describe their skills only as adequate, and a further 11 percent regard their business skills as inadequate. About one-quarter of all freelance artists indicated that they were very likely to seek to improve their skills in the year ahead, and a further 38 percent said this was likely. More than four out of five artists (82 percent) believe that they hold copyright over their creative work, a proportion that has increased since 2009 (when it was 76 percent). More than half (53 percent) of Australian artists are a member of one or more copyright collecting societies. This proportion is a significant increase over the last seven years. The proportion of all artists receiving a payment from a collecting society in 2016 (33 percent) was more than double the proportion in 2009. About one-quarter of Australian artists believe that their copyright has been infringed in some way. Almost two in five artists whose copyright has been infringed have taken action, and about 60 percent of these actions have been successful. Around one-fifth of Australian artists believe that their moral rights have been infringed at one time or another, (approximately the same percentages as in 2009 and 2001). Visual artists, actors and community artists appear to be the groups most affected by moral rights infringements. 

There are a number of sources of financial assistance to artists including Commonwealth, State/Territory and local government programs, private foundations, arts organisations and so on. Such financial assistance frequently buys artists freedom from financial concerns in order to spend more time on their art; indeed this is the most common impact of financial assistance as recognised by artists themselves. 

The changing context of artistic practice 

Around half of all artists have utilised their artistic skills in some other industry outside the arts, and more than 80 percent of these artists have generated some income from such activities. In most cases this sort of outside work involves applying artistic skills in education and research outside the arts, including teaching. But otherwise, the industries in which artists undertake these activities follow closely the opportunities that are appropriate to the skills involved. Technology plays a particular role in supporting and extending professional art practice. The most often used technologies are word processing software, and image and sound recording and playing devices. In addition, the great majority of artists use the internet in administering and supporting their creative practice, particularly via the use of email, blogs, and social media. Almost all artists also access the world-wide web for research related to their creative work and at least nine in ten use it to learn and train themselves in their creative practice. Sales and promotion also figure prominently in internet use; between 70 and 80 percent of artists promote their work through the internet.

Eight out of ten artists think it likely or very likely that future technological changes will open up new creative and income-earning opportunities for artists, but only just over 40 percent believe there will be more opportunities for them personally. 

Gender issues 

There are few significant differences between the genders in terms of average age, family circumstances, NESB status, educational levels, and factors seen as advancing or inhibiting their careers. However, although the proportions of female and male artists who have had children under their care at some point in their career are more or less the same, substantially more women than men feel that this restricted their work as an artist “significantly” (38 percent versus 18 percent).

The main area where differences between male and female artists exist is in regard to income. On all measures except one women fare worse than men—the exception is earnings from arts-related work where women spend a greater proportion of their time than men. Of particular concern is the substantially lower incomes earned by women for their creative work in their PAO, given that female artists on average spend about the same amount of hours working in their creative work as male artists. There seems no plausible reason to suppose that women are less productive in their creative work than men. It is clear that, however interpreted, the earnings gap for women artists is particularly acute.

Despite this, there is at least some positive news for female artists—the gender pay gap appears to be narrowing. In 2001 the average total income of male artists was 57 percent higher than that of women; the corresponding percentage difference had come down to 38 percent in 2008, and had reached 32 percent in 2015. The difference in creative incomes has also narrowed from 88 percent in 2008 to 44 percent in 2015.

Regional artists

Only a minority of artists across all artforms (21 percent) indicated that living and working outside a capital city had no effect on their work. Of those who did see some impact of location on their work, a larger proportion judged this impact to be negative rather than positive; this is a different result from that found in previous Artists Surveys, where the numbers seeing a positive effect have mostly been greater than those judging the effect to be negative.

On most measures there are few differences between artists according to their location. However, we can observe that on the whole artists living outside capital cities appear to earn significantly less than their urban counterparts.

Artists from non-English speaking backgrounds

About 10 percent of artists in Australia are from a non-English speaking background (NESB). The majority of artists (54 percent) who learned a language other than English as their first language see a more positive than negative effect on their art practice stemming from their NESB status, with about one- quarter (27 percent) indicating no effect, and the remainder (19 percent) saying they felt it has had a negative effect.

In common with artists as a whole, NESB artists see economic and work-related factors (lack of financial return, lack of time) as the most important factors inhibiting their professional development. However, it is significant that 18 percent (or twice as many NESB artists compared to artists from an English-speaking background) see the lack of access to funding or other financial support as the most important inhibiting factor at the present moment.

In regard to applying for financial assistance, the same proportion (more than half) of artists from English and non-English speaking backgrounds applied for a grant, fellowship, residence, prize or funding between 2010 and 2015. However, the success rate for NESB artists was lower than for artists from an English-speaking background (60 percent versus 68 percent).

Artists with disabilities

Overall about nine percent of all artists have some form of physical or mental disability that may affect their artistic practice. Around one in five artists with a disability say that it affects their artistic practice all the time, and a further 15 percent say it affects them most of the time. Most commonly, artists with a disability say that it affects them only sometimes (55 percent). About one in ten indicate that their disability does not affect their creative work. Artists with a disability earn significantly less than their colleagues with no disability. The negative differential in mean incomes is greatest for creative incomes—artists with disability earn an income from their creative work that is less than half that for other artists. The disparity is lessened to some extent with the addition of non-arts incomes but even so, artists with disability still fare considerably worse, with gross incomes that are not much more than half (58 percent) of the incomes of artists who do not have a disability to deal with.

About one-third of artists with a disability had some experience of unemployment between 2010 and 2015 compared to just under one- quarter of artists without a disability. Likewise the periods of time spent unemployed, and the longest consecutive periods of unemployment, were considerably longer. Almost one in five artists with a disability indicate that having a disability has been the most important factor inhibiting their professional development, both throughout their career and at the present time.

Wellbeing

The concept of subjective wellbeing has come into prominence in recent years in social and economic policy-making. This phenomenon can be measured in terms of individuals’ assessment of how satisfied they are with their lives. Artists in the survey indicated that on average they are generally satisfied with their lives, at a level similar to that of most Australians. It should be noted that some part—perhaps a major part—of our assessment of artists’ life satisfaction can be explained by the generally high quality of life in this country as experienced by all Australians. Also, the question in our survey refers to the artist’s life in general, not specifically to their life as an artist. There appears to be little variation across artforms in levels of life satisfaction. Although there may be some grounds for concluding that dancers are the most satisfied and community artists the least, the extent of variation around the mean is relatively minor. It appears that older artists are more satisfied than younger ones with their lives, a tendency especially noticeable among musicians, dancers and writers. 

Age rates are not greatly influenced by age for applicants for grants from the Australia Council or from State/Territory or local government funding sources. 

Mobility 

Some artistic occupations may require practitioners to move their place of residence from time to time. Across all artists we find that 55 percent have not changed their place of residence in the last five years, a similar proportion to the Australian population as a whole. However, there are significant differences between the artforms. Looking at the most mobile groupings—those who have re- located four or more times—we can see that it is performing artists who are the most strongly represented in this group.

In regard to incomes, the data show that artists relocating two or more times in the last five years are earning creative incomes that are around 25 percent less than those who have stayed put, and outcome no doubt due to the disruptions to the artist’s creative practice caused by the frequent need to move. Similarly total incomes of the most frequent movers are more than $10 thousand or about 20 percent less than the aggregate incomes of those who haven’t changed their place of residence.

Some longer-term trends

As noted earlier, the artistic workforce is growing older. The ageing of the population is particularly noticeable amongst visual artists, dancers, musicians and community artists. These trends are suggestive of the changing demographics in the artistic workforce—in particular its maturation, with increasing numbers of artists entering artistic professions later in their lives and of established artists continuing to practice for longer periods in their later years. These trends have been generating a larger body of senior practitioners in the artistic community over time. 

Assembling data from previous Artists 

Surveys going back to 1980, enables us to conclude that there does appear to be a gradual ageing of the population of artists in Australia over time. Over the approximately 30-year period covered by the data, it appears that the proportion of younger artists in the population has fallen, whilst the proportion over 55 has grown significantly—more than doubling over this period. The latter effect is particularly noticeable amongst visual artists, craft practitioners, musicians, composers and community artists. Trends in the proportions of the younger cohort of artists are less easy to discern, although there appears to have been a steady decline in the proportion of young people practising in community cultural development and the visual arts.

In the present survey, the most important factors identified by artists in the different age groups as inhibiting their professional development at the present time were economic factors. In particular younger artists are held back by lack of work opportunities, reflecting the perennial difficulties faced by new entrants in breaking into the arts profession. Mid-career artists suffer particularly from a lack of return to creative practice and a lack of time for creative work due to other pressures, including the need to sustain their incomes by taking on other employment, making it difficult for them to maintain their presence in the field.

There are clear patterns in the financial circumstances of artists according to their age. It is the mid-career period that is the most productive—creative incomes in this period are highest, and higher than for older artists, notwithstanding the fact that older artists spend a slightly larger proportion of their time at their creative work. As artists grow older, their inclination to apply for financial assistance declines, and their likelihood of success also appears to decline. On the whole success rates are not greatly influenced by age for applicants for grants from the Australia Council or from State/Territory or local government funding sources

Patterns of artists’ time allocation have remained remarkably stable. Since the early 1990s the average proportion of total working time spent on creative work hovered at just over 50 percent but has now increased to just under 60 percent. Whilst the average proportion of time spent working outside the arts altogether has remained around 20 percent. Likewise the weekly hours worked has seen only small fluctuations around a mean of about 43 hours.

In the case of incomes, little has changed

in real terms; artists’ creative incomes have increased sufficiently in nominal terms to keep pace more or less with inflation, but no more. Meanwhile, artists’ relative position in comparison with other professionals has deteriorated, since those other groups have enjoyed a rising trend in their real incomes for most of the period covered.