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Measuring Harm with Crime Harm Indices

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The Crime Analyst's Companion

Abstract

Analysing crime problems commonly involves counting crimes using records from police databases. But these crime counts weight all crimes equally, not capturing the different levels of harm associated with different crimes. In recent years, Crime Harm Indices (CHIs) have emerged as a tool to help analysts, researchers and decision-makers understand and focus on the harm associated with crime problems. CHIs are lists of values that are estimates of the relative harm from each crime type. These values are applied to each crime record, or count per crime type, as a weight. Summing the weights yields an estimate of the total harm from all offences. CHI-based analysis is complementary to—but not a replacement of—traditional crime counts and can yield insights into crime problems that would otherwise be hidden. This chapter introduces CHIs and provides examples of and guidance for their use by crime analysts. It also points readers in the direction of methods for developing their own CHI if there is not one available in their jurisdiction.

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Notes

  1. 1.

    Broad groupings of crime into high, medium and low harm categories are thus excluded (e.g. Crime Statistics Agency, 2020).

  2. 2.

    Some authors refer to these resulting harm estimates as the ‘index’ (e.g. Babyak et al., 2009). I use the term CHI to denote the list of weights, the tool in the analyst’s toolbox that enables crime harm to be calculated. These weights can be applied to crime counts in various ways, depending on the needs of the analyst, their research questions and the same analytical considerations that would be applied to unweighted counts (e.g. which crimes to include and which, if any, denominator to use to create a standardised rate, such as population). The development of consistent CHI-weighted performance measures and official statistics (Bangs, 2016; Sherman & Cambridge University associates, 2020) is one of many potential CHI applications.

  3. 3.

    Starting point means a sentence that can be moved up or down based on aggravating or mitigating factors; minimum means the shortest possible sentence; maximum means the longest possible sentence.

  4. 4.

    An additional UK-based CHI used a public survey where crime seriousness was rated on a scale from 1 to 20 (Ignatans & Pease, 2016), but this method has been criticised for lacking granularity and range of weights, and being costly to implement (Bland & Ariel, 2020; Curtis-Ham & Walton, 2018). See also Fenimore (2019) and Kwan et al. (2000) for US and Hong Kong versions of the public survey approach, respectively.

  5. 5.

    Tanner (2018) argues that if harm and volume are highly correlated (as they were in his study comparing harm and volume in neighbourhoods), using a CHI provides little added value for police resource deployment. However, I’ve found its value lies in the outliers of this correlation: the places (or people) that score highly on harm but not on volume, and vice versa. So I recommend using CHIs regardless of the correlation between harm and volume in a given dataset (unless the correlation is so high that there are no outliers, as I discuss in the section on CHI traps, tips and tricks).

  6. 6.

    Tracking is comparable to the Scanning stage of the SARA (Scan Analyse Respond Assess) model for problem-solving crime analysis, but it can also include ongoing monitoring of performance from an Assessment perspective. Targeting and Testing map to the Analyse and Assess stages.

  7. 7.

    Although the importance of using appropriate denominators to enable comparison between places (or times) with different numbers of potential crime targets cannot be overstated, further discussion is beyond the scope of this chapter other than to refer readers to these informative sources: Boivin (2018) and Johnson et al. (2020).

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Correspondence to Sophie Curtis-Ham .

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Curtis-Ham, S. (2022). Measuring Harm with Crime Harm Indices. In: Bland, M., Ariel, B., Ridgeon, N. (eds) The Crime Analyst's Companion. Springer, Cham. https://doi.org/10.1007/978-3-030-94364-6_13

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  • DOI: https://doi.org/10.1007/978-3-030-94364-6_13

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