Introduction

The association between ethnicity and crime is a contentious issue. While public discussions commonly revolve around possible bias in policing and sentencing, the unresolved question concerns possible disparate rates of drug-related crime. A large body of research has examined disparities in U.S. prison populations and found that it was mostly a result of the war on drugs and that race has very little influence on sentencing (Beck and Blumstein 2018; Klein et al. 1990). It is well known that ethnic minorities are overrepresented in low-level drug offences (Golub et al. 2007), but this could be from higher drug use prevalence rates among minority populations, less discrete public use (Harcourt and Ludwig 2007; Nguyen and Reuter 2012), and not necessarily policing bias (Sampson and Lauritsen 1997).

Given the major importance of drug offences in explaining racial disparities in U.S. prisons (Tonry 1994), it is notable that no European research has examined ethnic disparities in serious drug offences (but see Paoli and Reuter 2008). Ethnic disparity in the Nordic criminal justice systems is a comparably new topic for research and most studies examine offending rates – that is, the number of charges for the most common categories, property offences and violence, relative to the size of the subpopulation. Only very few studies include data on drug offences. These studies, inadvertently or by design, focus on low-level offending because they use crime counts. There are many more drug possession and retail sales offences than there are wholesale and trafficking (Bäckman et al. 2021; Moeller 2021).

The use of crime rates in studies of ethnic disparities misses important aspects of the issue. Not all crimes are equal. Some crimes cause more harm to society than others (Sherman et al. 2016). For example, violence has more “symbolic significance” compared to property offences (Brodeur 2007), and this will influence public (mis)perceptions of crime trends (Esberg and Mummolo 2018). Crime in the Nordics broadly show decreasing rates of offending, but with increases in selected serious crime types (Andersen and Mueller-Johnson 2018; Kärrholm et al. 2020). Drug offences cover the entire scale of crime harm. Low-level drug offences (possession and retail sale) are perceived as the least harmful offence types, while high-level drug offences (wholesale and trafficking) are among the most harmful because they connect to other serious offending including violence (Gómez-Quintero et al. 2023; Ratcliffe 2015).

In their review of the research on race and crime, Sampson and Lauritsen (1997) called for more studies from (1) cultural contexts outside of the U.S., which (2) include drug offending, and (3) examine more than one decision point in criminal justice system. This study answers that call and provides a description of disparity ratios between two country of origin groups, for all cases that had as their primary charge violence, property, or drugs (n = 718,775). Drug offences are categorized as possession, retail sale, wholesale, or trafficking. Data are for the total Danish population over the period 2013–2019, and measure criminal charges, sentencing decisions on prison or probation, and the length of term.

Review

There is substantial variation in the scope of the ethnic disparity in registered offending depending on data sources, offence types, and countries of origin. Disparities are larger in register studies of charges and convictions, and smaller in research based on self-reported offending. Self-report studies will tend to miss serious offending, because they are rare occurrences, while register studies can be influenced by self-perpetuating bias in the criminal justice system (Klement 2020; Ousey and Kubrin 2018). The number of registered offences is not only a function of crime, but also of the societal reactions to crime, and the public’s inclination to report crime. Most research on ethnic disparities examines the index offences, crimes against persons and property (Hindelang 1974), and finds higher ethnic disparities for violence, and lower for property offences, but still markedly above rates for the majority population (Ousey and Kubrin 2018; Skardhamar et al. 2014). In Denmark, non-Western immigrant men are about twice as likely to be convicted for violence and about 29 per cent more likely to be convicted for property crimes after controlling for socio-economic status, age, and gender composition (Andersen and Tranæs 2011).

Thefts and violence come to the attention of the justice system by the public reporting to police. For property offences, insurance companies require that there is a police report, so reporting propensity is high. For violence, there is more variation across incidents, individuals, countries, over time, and between neighbourhoods (Goudriaan et al. 2004). Illustratively, Baumer (2002) found that lower household income and being black implies a lower average likelihood of reporting assault or robbery to police. In turn, this focus on index offences in research on ethnic disparities risks “overemphasizing the importance of race or ethnicity in offending and victimization and underemphasizing its influence on criminal justice decision-making” (Sampson and Lauritsen 1997, p.317).

The public only rarely reports drug offences. Ethnic disparities in counts of drug offences therefore potentially reflect discretionary decision-making and bias more than underlying offending. Only scarce Nordic research has specifically examined ethnic disparities in drug offending, but Bäckman and colleagues’ (2021) study of Swedish conviction trends found increased ethnic disparity in drug convictions. However, they counted drug offences as one category, which indirectly leads to a focus on less serious offending. Internationally, research confirms that ethnic minorities are overrepresented in low-level drug offending (e.g. Bielen et al. 2021; Golub et al. 2007). In Denmark, Moeller (2010; 2021) found a pattern where an increase in the number of drug offences correlated with an increase in ethnic disparity. Alternatively, the conventional explanation holds that police focus resources on specific neighbourhoods due to overall elevated crime levels and this presence in turn provides opportunities for control (Beck and Blumstein 2018; Golub et al. 2007).

For serious drug offences, the opposite holds. Drug traffickers and distributors do their utmost to hide their dealing (Decker and Chapman 2008), and it requires sustained police effort and substantial prosecutorial resources to arrest high-level drug offenders (Bushway and Forst 2013; Sevigny and Caulkins 2004). Discretionary decision-making does not influence these case counts. Not just anyone can become a high-level drug dealer, or more low-level dealers would do so (Hochstetler 2001). Distributing or trafficking large amounts of expensive drugs requires connections and trusting relations that benefit from shared ethnicities, and language barriers that complicate law enforcement infiltration (Caulkins and Reuter 1998; Decker and Chapman 2008; Moeller and Sandberg 2019).

Paoli and Reuter (2008) noted a “striking overrepresentation” of specific ethnic minority groups in European drug trafficking that correlated with known trafficking routes. While ethnicity is clearly not a determinant (Eski and Sergi 2024), connections to source and trans-shipment countries imply better opportunities. This “pipeline” hypothesis posits that expatriate communities from drug-producing countries provide a background movement of people that drug smugglers can hide in. The broader the pipelines, the easier it is for drug couriers to hide because surveillance decreases in intensity when the general traffic increases. It is also easier to find a willing courier when the pipeline is broader (Reuter and Kleiman 1986). Illustratively, an interviewee in Moeller’s (2017) study, when asked about competition between native Danish outlaw motorcycle gangs and “immigrant gangs”, commented “who do you think has the best contacts in Morocco?”

Country of origin

The Nordic countries share convergent trends in immigration (Skardhamar et al. 2014). In the 1970s, guest workers from Yugoslavia, Pakistan, and Turkey decided to stay and opted for family reunification and the tied movers from family reunifications became a source of immigration over the following quarter of a century (Mogensen 2010). In the late 1980s and into the 1990s, immigrants were mostly refugees from Poland, Iran, Iraq, Lebanon, and Sri Lanka, ex-Yugoslavia, and Somalia (Dinesen 2010). For the past ten years, most immigrants are refugees seeking protection from wars in Syria and other Middle Eastern conflict zones (Andersen et al. 2022).

There are substantial variations in offending rates among immigrants and their descendants in the Nordic countries. These variations correlate with region of origin and the motivations for immigration. In brief, immigrants from Asian countries have lower rates of registered offending compared to the native Danish population. Immigrants from Eastern European countries, other Western countries, on average have offending rates like the majority population, but immigrants and descendants from Middle Eastern and North African countries are heavily overrepresented (Statistics Denmark 2021), particularly in violence and to a lesser extent property offences (Andersen and Tranæs 2011; Skardhamar et al. 2014; Vasiljevic et al. 2020). When holding socio-economic factors constant, persons of foreign background had a twice as high risk of a criminal conviction compared to individuals born in Sweden to two Swedish-born parents, from 1973 to 2017 (Bäckman et al. 2021; see also Lappi-Seppälä and Tonry 2011).

Cultural differences may help explain these differences. Skardhamar and colleagues (2014) compared the rank order of countries with the highest disparities in property offences and violence in Norway and Finland. For persons from North African and Middle Eastern countries, in Norway, convictions for violence were 1.8–4.3 higher, and 1.5–3.2 when controlling for age and gender. In Finland, the corresponding figures were 3.2–7.5 and 2.1–5.6. Andersen and colleagues (2022) applied empirical measures of cultural background and reasons for migrating to Norwegian register data to examine this heterogeneity further. They found that rates of criminal charges were lowest for work- and education-based migrants and highest for refugees from “environments that differ culturally the most from Norway in terms of Survival versus Self-Expression values” (Andersen et al. 2022)., i.e. Middle Eastern and North African countries.

In the U.S., cultural differences between immigrant groups and the destination country implies a decrease in overall crime rates. The Latina/o immigrant populations – including those who maintain an undocumented status – tend to offend less than other groups, net of community context (Ousey and Kubrin 2018). Rojas-Gaona and colleagues (2016) explained this “paradox” of immigrants from poorer backgrounds offending less with reference to the high violence culture of American society. Conversely, the Nordics are high-trust, low-crime countries. Immigrants and their descendants from non-Western countries have lower levels of generalized trust in societal institutions, including law enforcement (Jensen and Pedersen 2007; see also Krieg et al. 2023; for similar findings from Germany). Parents from low-trust countries tend to transmit this low trust from one generation to the next, through restrictive upbringing practices, which reduces integration into Danish society (Dinesen 2010).

Sentencing severity

Serious drug offences are rare at the population level, but they are among the most severely sanctioned offences. In Ratcliffe’s (2015) offence gravity score, cannabis possession is among the least serious offences scoring 1 out of 14 points, and distribution of more than 1 kilo of cocaine scoring 13, with only murder and rape of minors scoring 14. The final severity of drug sentences reflects many factors, including prior sentences, recidivism, willful misconduct, culpability of the offender (Sevigny and Caulkins 2004), complexity, and sophistication (Gómez-Quintero et al. 2023). Prison populations largely reflect involvement in violent and drug offending (Beck and Blumstein 2018; see also Ousey and Kubrin 2018; Tonry 1994). Only around half of prison inmates in Denmark have at least one parent that is both a citizen and was born in the country (Kriminalforsorgen 2021). This ethnic disparity in the prison population is much higher than we would expect from disparities in crime rates and is closer to the current U.S. black–white prison disparity of 5:1 (Klein et al. 2023) and the “war on drugs” arrest disparity (Blumstein 1993; Tonry 1994).

A large international literature examines potential ethnic discrimination in sentencing as an explanation for this disparity in the prison population. In their summary, Sampson and Lauritsen (1997) observed that it results from the types of crime, prior felony convictions, aggregation effects, and not discrimination based on race. Blumstein (1993) also noted that differences in offending explained 80 per cent of the racial disproportionality in prison populations. S. Klein and colleagues (1990) concurred and found that adding race to their analyses did not improve the accuracy by even one per cent. In the U.S., sentencing guidelines delineate sanctions for various drug types and amounts. These guidelines were introduced with the explicit purpose of reducing the potential for ethnic bias (Beck and Blumstein 2018; Brownsberger 2000). Mitchell (2005) concluded that the evidence of a racial sentencing gap in a meta-analysis was statistically significant, but substantively small and highly variable. A later study by Light (2021) found that there was no longer a racial sentencing gap in federal courts. In the European context, Bielen and colleagues (2021) found that defendants with Islamic names received 3–5 per cent more severe sentences in Belgian drug offences. However, when they controlled for prior convictions, they coded it as a dichotomous variable that did not take account of the severity of criminal history, leaving the option open that the sentence disparity is due to prior offending (see also Bushway and Forst 2013; Klein et al. 1990).

No Nordic research on immigration and crime has included measures of sanction severity. These discussions commonly use simplistic measures of crime, counts, and rates. In an early study, Blumstein (1974, p. 854) argued for adding seriousness weights as reporting only crime rates fails to account for the seriousness of the offence, “a one per cent decrease in burglaries could mask even a doubling of the homicide rate”. Sherman and colleagues (2016) similarly argued that a “holistic” view of crime should include measures of severity, harms to society. Within types of offences, there is also variation in severity. Days in prison is the most accurate, but costly, measure (Ashby 2018; Kärrholm et al. 2020). Comparing mean days in prison for various offence types, affixes “a coefficient of social resonance” to each event (Brodeur 2007).

Objectives

This study aims to contribute to the research on ethnic disparities in the criminal justice systems by describing the following: rates of charges for drug possession; sale; wholesale; and trafficking; in-out decisions for drug charges; sanction severity across offences. It is not the aim of this article to assess bias in the criminal justice process. Several large international studies have grappled with the question of bias. In this study, only raw numbers are presented. Several Nordic register-based studies have controlled for age, gender, and socio-demographic differences and found that these factors attenuate disparities only moderately (Skardhamar et al. 2014). None of those studies included serious drug offences.

Materials and methods

The analytical focus is on four categories of drug offences, but data include violence and property offences for context. Violence comprises 14 types of offences, from threats, disturbance of public order, through to simple violence and manslaughter, but not sexual violence.Footnote 1 Property offences comprise 26 types including thefts of varying severity, robberies, burglaries, and serious tax evasion.Footnote 2

The Danish legal framework on drug offences is based on the Law on Euphoria-Inducing Substances, introduced in 1969. Less serious drug offences, i.e. possession and sale, are subsumed under this law. The maximum sentence is two years. More serious offences, i.e. wholesale (manufacturing or possessing drugs with the intent of selling) and trafficking (import, export, giving and receiving) fall under the Penal code Sect. 191, which has a maximum sentence of 16 years. The primary sentencing criterion for both is the amount and type of drug. The State Attorney (2006) delineated Sect. 191 and the Law on Euphoria-Inducing Substances to the following amounts: hash 10 kilos; heroin 25 g; cocaine 25 g; amphetamine 50 g. Other legally relevant factors are the criminal history of the defendant and offence seriousness in terms of professionalism, dangerousness, culpability, and harm (Sevigny and Caulkins 2004). For possession and sale, aggravating circumstances pertain to repeated instances of selling, and selling particularly harmful substances. Wholesale and trafficking aggravating circumstances consist of selling to a larger number of people or for large sums of money.

I follow Statistics Denmark’s categorization of immigrants, descendants, and ethnic Danes. An immigrant is defined as a person born outside of Denmark to two parents who were both foreign citizens born outside of Denmark, while a descendant is defined as a person born in Denmark to two parents who were both born outside of the country and who are not Danish citizens. A person who has at least one parent born in Denmark or is the child of a Danish citizen is part of the majority of ethnic Danes (Statistics Denmark 2020). MENAP is a regional grouping of countries that is used internationally and consists of Middle Eastern, North African countries, and Pakistan. Denmark adds Turkey to this grouping, due to the geographic proximity to the other countries and the historically significant role of Turkish immigrant workers in the 1970s (Ministry of the Interior 2022). The category MENAP + T consist of 24 countries: Afghanistan, Algeria, Bahrain, Djibouti, Egypt, Iran, Iraq, Jordan, Kuwait, Lebanon, Libya, Mauritania, Morocco, Oman, Pakistan, Qatar, Saudi Arabia, Somalia, Sudan, Syria, Tunisia, United Arab Emirates and Yemen, and Turkey. In 2013, around 161,000 persons were immigrants or descendants from these countries, and in 2019 around 218,000 persons.

In the second category, “all other countries”, 90–92 per cent have Denmark as their country of origin. I group individuals with all other countries of origin in one category partly for analytical reasons and partly because the rates of criminal charges are relatively similar within this group. For individuals with their country of origin in Denmark, Western countries, and non-Western countries other than MENAP + T, the number of charges per 1,000 inhabitants was around 16, 16, and 34, respectively. Without considering any explanatory factors, the number of charges per 1,000 inhabitants with country of origin in MENAP + T was, on average, 92 in the studied period. The category “All other countries”, consisted of around 4,464,000 persons in 2013 and 4,631,000 in 2019.

The crime data were obtained from three registries maintained by Statistics Denmark: one contains charges; one contains convictions for primary offences; and the last contains convictions on secondary offences (Danish registry abbreviations: KRAF, KRKO, and KRSI). I include inhabitants of 15 years of age and above as this is the age of criminal responsibility in the studied period. Offenders ages 15–17 are presented in adult courts but can be sentenced to prison only for exceptional reasons (Lappi-Seppälä and Tonry 2011).

Data on country of origin were obtained from registries on demographic characteristics and immigrants and their descendants (Danish registry abbreviations: BEF, and IEPE). The data are stored on a secure server hosted by Statistics Denmark, the national statistical agency. A case identification number makes linking information on a court case across registries possible. The national personal identification number makes linking information on individuals in each case possible.Footnote 3 In all five registries, Statistics Denmark replaces each case and personal identification number with a unique, anonymized number (for more on Nordic register data, see Lyngstad and Skardhamar 2011).Footnote 4

For each court case, which might include multiple offences, only the verdict on the primary offence and the sanction if it is a conviction, is recorded. Even though a secondary offence might result in an acquittal, a conviction and the related sanction is recorded for the entire court case if the primary offence results in a conviction. Instead of only studying either verdicts on primary offences and ignoring the secondary offences or studying all individual offences and ignoring sanctions, I examined both, depending on the focus of the specific analysis.

I include convictions that result in acquittals, unconditional prison sentences, and conditional prison sentences. I exclude withdrawals of charges and other types of infrequent verdicts (in Danish: tiltalefrafald, påtale opgivet, and anden afgørelse). Occasionally, sanctions consist of a combination of, for example, an unconditional prison sentence and a fine. In these instances, I rely on Statistics Denmark’s categorization of the primary sanction. Convictions without a court meeting but with a fine are coded as the fines, and this includes around 11,000 convictions for violations of the Law on Euphoria-Inducing Substances in the studied period. Unconditional prison sentences to “life” were coded as 5,760 days.

I created two samples, A and B. Sample A consists of all offences in each court case including secondary offences. Sample B only has the primary offences in each court case, and is a subset of sample A. When examining the number of offences and country of origin category, I use sample A, and when examining sanction severity for the primary offence, I use sample B. Days in prison is the most accurate measure of severity (Ashby 2018; Kärrholm et al. 2020). The unit of analysis in both samples is offences. Sample A has 718,775 observations for the seven years (Mean per year = 102.682; SD = 5.116; Min. = 93.875; Max. = 111.188). Sample B has 286,832 observations (Mean per year = 40.976; SD = 3562; Min. = 34.812; Max. = 45.740). I present descriptive results as disparity ratios and do not attempt to explain characteristics of communities or individuals that could lead to higher rates of registered offending.

Results

First, I describe the number and rates of charges for violence, property crimes, and the four types of drug offences. Next, I disaggregate these by country of origin category. After this, I present the share of charges for the different offence types that lead to unconditional or conditional prison sentences, by country of origin category. Lastly, I calculate the mean sanction severity, measured as prison days, for unconditional and conditional sentences, by offence type and the country of origin category.

Number and Rates of Charges.

Property offences are by far the most commonly registered, with four times as many as drug possession offences in a year. There are about one and half times as many drug possession offences as there are violent offences. The rates of the four drug offence types reflect their seriousness. It takes around six possession offences for each sale offence, and two sale offences for each wholesale offence. For the Danish population as a whole there are around six trafficking offences per 100,000 population, as seen in Table 1 below.

Table 1 Charges and rate per 100.000 population (n = 718,775; sample A)
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These levels are quite stable over the period under examination, with four exceptions. The number of charges for violent crimes was higher from 2017 to 2019 compared to preceding years. Charges for drug selling were the highest for the period in the two last years under examination, 2018–2019. Drug trafficking charges increased markedly in 2019, and 2017 had an exceptional number of wholesale charges.Footnote 5

Rates of charges by country of origin category

Disaggregating the rates of charges for the two country of origin categories reveals large disparities. Table 2 below shows the mean rates and variation, and the disparity ratio.

Table 2 Charges per 10,000 inhabitants and disparity ratios (n = 656,106; sample A)
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Note the large standard deviation on rates of wholesale offences for the MENAP + T group. The outlier year 2017 contributes to this elevated mean. When excluding 2017, the disparity ratio for wholesale offences was 4.8. The disparity ratio for the drug offences are in a similar range as the index offences, except for sale which is higher. For both country of origin categories, the distribution between offence types are similar. For the category All other countries, 11 per cent of charges are for violent crimes and 66 per cent are for property offences. For MENAP + T, 14 per cent are violence and 61 per cent property. For both country categories, 18 per cent of charges are for drug possession.

In-Out Decision.

Moving to sentencing decisions, Figs. 1 and 2, along with Tables 3 and 4, show the rates of unconditional and conditional prison sentences, for offence types, for each country of origin category. The figures illustrate the flow of cases through the Danish criminal justice system, with a focus on the charges that end in an unconditional or conditional sentence. The proportion of cases that end in acquittal is low, between zero per cent for possession, to around five per cent in trafficking cases. Around 95 per cent of possession cases are resolved with a fine, as are 69 per cent of property offences. As noted in the review, it is violence and the serious drug offences, and drug sales that most commonly result in a prison sentence.

Fig. 1
figure 1

Sankey diagram – Share of charges that lead to unconditional and conditional sentences, and offense type as share of prison days. All other countries

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Fig. 2
figure 2

Sankey diagram – Share of charges that lead to unconditional and conditional sentences, and offense type as share of prison days. MENAP + T countries

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Table 3 Share of charges that lead to unconditional and conditional sentences, and offense type as share of prison days. All other countries
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Table 4 Share of charges that lead to unconditional and conditional sentences, and offense type as share of prison days. MENAP + T
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Table 3 details the contents of Fig. 1. For persons from all other countries, the proportion of charges for violence that end in a conviction to unconditional prison was 41.2 per cent, and 38.4 per cent for property offences. However, when looking at prison days, sentences for violence constitute less than their share of convictions, at 32.6 per cent, and similarly property offences account for less at around 33 per cent. The largest increases across the criminal justice system are for the serious drug offences, trafficking and wholesale. As seen in Table 3, trafficking and wholesale combined constitute around ten per cent of convictions to unconditional prison, but account for more than 30 per cent of all unconditional prison days for persons from all other countries.

Table 4 details the contents of Fig. 2. For the category of MENAP + T country of origin these shares are different, mostly because convictions for violence constitute a larger share, and they result in around 44 per cent of all prison days. The second most notable difference is in convictions for wholesale drug offences. For the MENAP + T category they constitute around 6 per cent of all convictions to unconditional prison and this increases at a similar rate as the all other countries category, when it comes to share of prison days. Wholesale offences end up being a smaller share of all prison days, at around 16 per cent.

Comparing the two country of origin groups on how charges flow through the criminal justice system, the most noticeable difference is registered violence. Because there are so many cases of violence, compared to the serious drug offences, this ends up creating a difference in the types of offences that the two respective country groups serve prison time for. For all other countries, unconditional prison days are evenly distributed between violence, property, and serious drug offences. For MENAP + T, violence dominates.

Sentence severity

Lastly, Table 5 below presents the mean severity of sentences, measured as days in prison. Across all the offence types, the mean unconditional sentence is around 11% longer for the MENAP + T category, while the mean conditional sentence is shorter.

Table 5 Summary table on mean length of unconditional prison sentence measured in days and distributed on country of origin for 2013 to 2019
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The biggest differences in the duration of unconditional sentences are for violence, where the MENAP + T category receive 35 per cent longer sentences. For the conditional sentences, the pattern is the opposite. Here, persons originating in the MENAP + T countries, on average receive shorter sentences. Most notably, the conditional sentences for trafficking in the MENAP + T category are only one-fifth as long as the all other countries group. It is not possible to discern from the available data what causes this difference. Prior U.S. research that examined these questions found that differences in mean sentences were attributable to offence severity, the criminal history of defendants, or other legally relevant reasons (Blumstein 1993; Klein et al. 1990; Sampson and Lauritsen 1997).

Discussion and conclusion

In this study, I described rates of criminal charges, and sentence severity for two categories of country of origin. The contributions to the existing Nordic drug research are threefold: firstly, the inclusion of three decision points in the criminal justice system enabled the comparison of differences across stages; secondly, the detailed exposition of differences across levels of drug offences introduced new context for known ethnic disparities in low-level drug offending; thirdly, the inclusion of a measure of sanction severity provided a new component that has been missing despite importance of such a measure in understanding U.S. disparities.

Regarding the rates of charges, I found disparities in the range of previous Nordic research (Andersen and Tranæs 2011; Andersen et al. 2022; Skardhamar et al. 2014) and related ratios in the U.S. (e.g. Klein et al. 2023; Ousey and Kubrin 2018; Rojas-Gaona et al. 2016; Tonry 1994). Unadjusted for population structure and socio-economic variables, the disparities were in a similar range across offence types (when excluding the unusually high disparity for wholesale drug offences), with higher disparity for violence, and lower for property offences. The biggest disparities were for drug wholesale and drug sale offences. Notably, the disparity in drug possession offences was not unusually high compared to the other offence types but it is not possible to discern from this study whether the 5.4 disparity for possession offences reflects underlying offending, elevated drug use, or maybe inconspicuous use in public, or biased policing (Nguyen and Reuter 2012). This finding contributes to the discussion about ethnicity in drug offending and bias in the criminal justice system. Typically, we would expect more potential bias in lower-level offending, and less discretion and bias for the higher-level offences. The level of discrimination required for explaining the observed disparities would have to be of “scandalous” proportions (Skardhamar et al. 2014). This descriptive study does not resolve this issue.

The difference between the two country categories in the rates of charges for wholesale drug offences was substantial. For the MENAP + T category, around 33 charges per 10,000 citizens per year, like the rate of possession charges brought against the all other countries group. Note the large variation around the mean. Some of the explanation for this elevated mean level can be found in the anomalous year 2017, which had an astounding 177 charges for wholesale drug offences in the MENAP + T category. This exceptional level of charges for serious drug offences was probably the outcome of a gang conflict in the capital Copenhagen, between the historically dominant outlaw motorcycle gangs and more recent street-oriented gangs consisting mostly of ethnic minorities (Klement 2020; Moeller 2017). The period from 2017 to 2019 was unusual in other regards as charges for violent crime was more prevalent, and charges for drug selling were almost twice as high in 2018–2019 compared to the mean for other years.

Moving to the in-out decision, the findings presented support the conventional wisdom that drugs and violence are the offence categories that most commonly result in imprisonment (Beck and Blumstein 2018; Tonry 1994). Tables 3 and 4, demonstrate that – broadly – similar shares of charges lead to unconditional and conditional sentences for the two country of origin categories. However, violence contributes more to total imprisonment for MENAP + T, due to the combination of higher rates of charges and longer average sentences. Since this study did not distinguish between types of violence, relatively few serious cases could have influenced the aggregate number of prison days. Similarly, the period with gang-related conflicts could have influenced that share of prison days that are the result of violence convictions, and may even have increased the mean severity.

As regards differences in sentencing severity, the disparities are less pronounced compared to those found in rates of charges. The international research that has examined this question (e.g. Beck and Blumstein 2018) suggests that these differences are typically due to the criminal history and contents of cases. While potential bias was not the focus of this study, it was examined indirectly by comparing rates of offending across crime types that differ in how they are reported to police, and how police investigate them. If there is bias at the first stage of the criminal justice system, the rates of charges for ethnic minorities should be higher for low-level drug offences compared to higher-level drug offences. At the following stages, in-out and days in prison, arguably the severity of the underlying offending is in focus.

The key limitation of this study is the lack of control for the influence of socio-economic and demographic factors on rates of offending or sentence severity. The decision not to control for these factors was practical. The register data must be purchased from Statistics Denmark. For this small study, data on sentence severity were prioritized. It is quite possible that controlling for these variables would reduce the disparities in rates of serious drug offending even more than for property and violent offences, due to the risky but potentially economically rewarding participation in the illicit drug economy. In general, socio-economic differences do not explain offending in the Nordic countries (e.g. Ring andShannon 2023), and arguably socio-economic strain should be less of a cause of involvement with drug trafficking in a Nordic welfare state, as compared to the U.S. Another limitation was the lack of data on the number and severity of prior convictions, or details on the contents of individual cases. This precludes drawing strong conclusions. Research from the U.S. suggests that sentencing severity reflects legally relevant factors: criminal history and case severity. Based on the data in this study, it is not possible to ascertain whether these differences are attributable to the content of the criminal charges or the criminal history of defendants, or both, or something else altogether, e.g. bias (Bielen et al. 2021). The Nordic research that controls for age and gender compositions, and socio-economic background all find that it reduces the overrepresentation (Andersen et al. 2022; Bäckman et al. 2021; Skardhamar et al. 2014) and findings from the international research suggest this is similar for serious drug offences (Beck and Blumstein 2018; Klein et al. 1990). Future research should examine this association in the Nordic countries.

The findings in this study suggest that ethnic disparities in Nordic prisons will increase in the future. Historically, the Nordic countries constitute a penal policy cluster with a low share of the population in prison at a given time (Lappi-Seppälä and Tonry 2011). However, several punitive criminal justice measures have been implemented in response to recent gang conflicts. Homicide characteristics are changing as a growing share of homicides arise from conflicts between gangs (Liem et al. 2019). These homicides have a low clearance rate and are highly symbolically significant events (Brodeur 2007). A public execution of a rival gang member is the tip of the iceberg of a deviant subculture, regulated by violence and subterranean norms (Sampson and Lauritsen 1997).

Lastly, in the review, it was noted that ethnic disparities are larger in register studies and smaller in research based on self-reported offending. A Swedish study, based on self-reported offending among 15–16-year-olds, found that ethnic disparity appears to be diminishing in low-level offending (Vasiljevic et al. 2020). Conversely, the present study provided evidence at the opposite end of the crime-type continuum. When focusing on the most serious drug offences and sanction severity, ethnic disparity is even higher than register-based studies that examine index offences. Summing up, this study contributes to the research on ethnic minorities and drug offending in the Nordic countries by examining three decision points in the criminal justice system and by including four categories of drug offences. Including the in-out decision and sentence severity adds an important component to the research on immigration and crime. Using measures of offence severity to weigh offence counts provides a better measure of temporal crime trends.