Abstract
Understanding offender motivation is key to developing effective crime reduction policies. Criminological theories seeking to explain offender motivations are plentiful—some argue for a pure utilitarian agenda driven by opportunity (rational choice), others for the influence of socially constructed standards of behavior (strain, learning), and still others argue for accounting for multiple layers of influence (crime pattern theory). Though these theories have been used to explain the presence of antiquities looting, few have sought to examine offender motivations specifically due to a lack of data. But what kind of data should those interested in offender motivations be looking for? How does this align with possible underlying theoretical motivations? This study speaks to these questions by first considering how criminological theoretical paradigms account for antiquities looter motivations. Then, it traces how to approach examining looting motivation by identifying the types of evidence and data needed to test theoretical predictions and which methodologies would be appropriate for such an analysis. Finally, this study demonstrates this approach using case study featuring a newly collected spatiotemporal dataset on antiquities looting in Egypt. Looking from 2015 to 2017, this study will determine what can be learned about possible offender motivations in Egypt at this time.
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Notes
- 1.
Accessing international crime statistics that are consistently available for multiple time periods (e.g., for longitudinal analysis) is a well-established issue. The United Nations has dedicated projects around the world to establish reliable methodologies and standards for international crime statistics (UN, 2017). Though availability of statistics has improved overall, there remains inconsistent availability longitudinally and the types of statistics available are country dependent. Countries with a history of or actively involved in conflict tend to have the least availability for crime statistics. This is mirrored in data available from other sources like the World Bank.
- 2.
Criminological theories are more commonly applied to explain behavior within the art market, including techniques of neutralisation (Conklin, 1994; Mackenzie & Yates, 2016) and routine activity theory (Mackenzie & Green, 2009). These studies are able to access more varied data sources with a focus on how assumptions of offender motivations across theories can serve to improve preventative measures (e.g., through deterrence). This study focuses on how criminological theory can assist in understanding offender motivation specifically in the area of antiquities looting.
- 3.
Other conceptualisations have also been offered in the literature. Fabiani (2018) offers ‘opportunistic’ and ‘strategic’ looters as a means of bypassing the implied mutual exclusivity between victim, criminal, and professional. Mac Ginty (2004) offered a typology of looting from a political science perspective, rejecting the premise that looting can be considered from a criminological lens since the crime of theft ignores important socio-political contexts.
- 4.
This heuristic is based on my analysis of offender motivation in criminological theory. The presentation is informed Coyne and Eck’s (2014) representation of the differing levels of influence of situational choice in offender decision-making.
- 5.
Lower Egypt refers to Egypt’s northern Delta region.
- 6.
One approach would be to seek approval and funding for a community- or individual-level study in the area. Yet there may be any number of reasons such studies have not been undertaken in Egypt–inability to travel to the region of interest (e.g., due to conflict, global pandemics, etc.) or the inability to secure funding and appropriate permissions.
- 7.
Tourist arrivals measure the portion of Egypt’s economy related to cultural heritage.
- 8.
It is important to note that none of these theoretical relationships can be examined from a causal perspective in this case study.
- 9.
Lower Egypt contains 13 governorates (geopolitical border akin to states in the United States) in the Nile Delta: Alexandria, Beheira, Cairo, Damietta, Daqahliyah, Al Gharbiyah, Ismailia, Kafr es Sheikh, Al Minufiyah, Port Said, Qalyubiyah, Al Sharqiyah, and Suez. Suez is excluded from this database due to an inability to identify any geo-coded archaeological site locations.
- 10.
Coding for evidence of archaeological looting involved a set procedure to ensure consistency of coding: (1) creating a boundary around each site, (2) coding each source of imagery separately according to which has the earliest image per site and comparing sequences of imagery to detect change, (3) reviewing, validating, and aggregating the data. See Fabiani (2019) for a full description of the data collection. Detailed coding procedures are available at www.michellefabiani.com.
- 11.
Data for socio-political stress were compiled from the Global Terrorism Database (GTD), Armed Conflict Location and Event Database (ACLED), and the Uppsala Conflict Data Program (UCDP).
- 12.
Overlaying a spatial grid on an area creates uniform more granular spatial units of analysis. See Fabiani (2019) for more information.
- 13.
Operationalisations for all the variables are discussed in depth in Fabiani (2019).
- 14.
Even with 10-km grid cells, neither environmental nor economic indicators proved granular enough to examine purely from a purely spatial perspective. Economic indicators also could not be examined spatiotemporally.
- 15.
Total crop production and unemployment were dropped from the final model due to high collinearity with other environmental and economic measures, respectively.
- 16.
This analysis is exploratory and is unable to speak to causality. It is possible that there is no spatial relationship in evidence.
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Fabiani, M.D. (2021). Offender Motivations and Expectations of Data in Antiquities Looting. In: Oosterman, N., Yates, D. (eds) Crime and Art. Studies in Art, Heritage, Law and the Market, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-030-84856-9_15
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