Measuring Crime: Lynnfield’s Local Police Force Stop & Search Data

Introduction

Background to the Study

Over the last decades, following the footsteps of developed nations such as the United States and the United Kingdom, police officers in many other countries across the world are increasingly adopting the ‘stop and search’ policing strategy with the view to keep crime levels down, especially in areas referred to as crime hotspots (Reid 2009). The ‘stop and search’ concept, however, has been met with differing reactions, with critics arguing that it is to blame for the unequal treatment of racial minorities, young people, and persons of low economic status by police (Taylor 2003), while advocates argue that not only is it proper for police officers to use stereotypes to assist them in their decision-making processes, but it is unimaginable to expect law enforcement officers to ‘stop and search all sections of the society equally (Qureshi 2010). Owing to the differing states of thought, the powers exercised by law enforcement agencies to stop, question, and search people in public places is increasingly becoming a debatable aspect of police-society relations and a fundamentally important issue for criminological, law enforcement, as well as legal scholarship (Burrell & Bull 2011).

One key concern that has featured prominently in nearly all debates on the ‘stop and search policy is the possibility of racial profiling and the disparate treatment of racial minorities, young people, and economically disadvantaged groups (Farrell et al n.d; Reid 2009; Fabio et al, 2011). While pressure to monitor and control minority populations, adolescents, and economically disadvantaged groups in society has always been a function of police work (Castle 2008; Fabio et al 2011), some scholars, practitioners, and mainstream commentators are arguing that it may be improper or inadequate for police officers to rely on, to any degree, on race, ethnicity, age, religion, or national origin in selecting which persons to subject to regular or spontaneous checks, especially in the absence of trustworthy data or information (Farrell n.d.).

Purpose of the Study & Research Question

Using the data collected by the Lynnfield Local Police force, the present study aims to assess any obvious trends that may be associated with disproportionate and/or discriminatory exercise of the ‘stop and search policy by law enforcement agencies. In particular, the study explores whether police stop, search, and arrest practices for the past year differ according to the racial orientations, age, or socioeconomic status of the citizens within the Lynnfield area and its neighborhoods. Consequently, the study is guided by the following research question:

  1. Do the stop and search practices undertaken by law enforcement officers within Lynnfield’s neighborhoods influenced by racial stereotyping, age considerations, and socioeconomic status of residents?

Literature Review

A thread of existing literature (e.g., Petrocelli et al 2003; Taylor 2003; Qureshi 2010) demonstrates that profiling of persons by police based on several vectors, including race, wealth, and age, has become a matter of national importance, especially in the United States and the United Kingdom. Racial profiling, which is the most dominant practice according to extant literature (Ratcliffe & Breen 2011), is generally viewed “…as the practice of targeting or stopping a pedestrian or driver of a motor vehicle based primarily on the person’s race, rather than any individualized suspicion” (Farrell et al n.d., p. 2-3). It, therefore, follows that age concerns are central in the practice of age profiling (Burrell & Bull 2011), as is the case with socioeconomic status in the profiling of persons based on their social standing in the society (Fabio et al 2011).

Scholars have employed the conflict theory to explain the relationship between the police stop, search and arrest practices on the one hand, and the disparate treatment of racial minorities, young people, and the economically disadvantaged members of the society on the other. Conflict theory, according to Petrocelli et al (2003, p.1), “…holds that law and the mechanisms of its enforcement are used by dominant groups in society to minimize threats to their interests posed by those whom they label as dangerous, especially minorities and the poor.” The conflict theory, according to this particular author, is grounded on the fact conflict is a fundamental social process and, as such, the community is to a large extent molded and configured by the competing interests of social groupings who vie for dominance with the view of enacting or maintaining a social structure most beneficial to them. The conflict theory further affirms that the relative power of a given social grouping dictates the prevailing social order in that power not only control the lawmakers, but also the law enforcement machinery of the state (Petrocelli et al 2003), implying that laws are formulated to serve the interests of the privileged and law enforcement agencies are used to suppress and control any section of society that poses a threat to the status quo (Castle 2008).

In their empirical analysis of police traffic stop data collected by the Richmond, Virginia Police Department, Petrocelli et al (2003) found that culturally dissimilar groupings were constantly viewed as threats to the existing social order and that many police officers still maintain criminal stereotypes about non-Whites to the extent of developing a predetermined orientation that the proportion of non-Whites living in the communities they police is an indicator of a crime problem. A study comparing the British Crime Survey and police stop and search statistics for a southern English county found that “…persons from a Black or Black British origin experienced a disproportionate number of searchers and arrests relative to White and other minority groups” (Qureshi 2010, p. 229). To reinforce these findings, a cross-sectional study conducted by Burrell & Bull (2011) found that members of racial minorities in the United Kingdom, especially Blacks, are far more likely to be stopped and searched by law enforcement officers, but it is yet unclear whether the discrepancy in stops and searches could be rationalized by racial disparities in offending, or whether the discrepancy in stop and searches exceeds the disparity in offending.

When the suspect’s age was put into consideration, the study by Qureshi (2010, p. 227) found that “…only persons in the following age groups were searched: 16 to 19 years; 25 to 29 years; and 40 to 49 years, with arrestees in the two older groups.” These findings reinforce the outcomes of another study done by Qureshi and Farrell (2006), which found that individuals between 25 and 29 years of age were more likely to be stopped, searched, and arrested by law enforcement officers than persons from other age categories. The overall perception presented by these findings is that the police stop and search practices fall unevenly upon individuals from their late teens onwards (Qureshi 2010). In their assessment of the age-crime curve, Fabio et al (2011, p S325) concluded that “…residing in a disadvantaged neighborhood during early adolescence may have an enduring effect of the age-crime curve throughout an individual’s life.” These findings demonstrate that individuals in certain age categories may indeed be easy targets for frequent police stop and search practices.

In socioeconomic status, a study conducted by Chambliss (1994) cited in Petrocelli et al (2003) found that an elite police force operating in Washington, D.C., focused all their attention on the “urban ghetto”, a section of Washington where an estimated 40 percent of the Black population resides below poverty level, with the resulting selective targeting focusing precisely on young, unemployed Black males. In yet another study investigating factors affecting the probability of traffic stops and searches for African Americans, Taylor (2003, p. 60) found that blacks from poor neighborhoods low socioeconomic standing “…were more likely to report that their traffic stops were unwarranted and were more likely to be searched for contraband.” The differential treatment of minorities and persons with low economic standing, according to Petrocelli et al (2003, p. 4), have “…negatively affected families and education, created moral panic and swelled prison populations that [are] comprised predominantly of minorities – especially young Black males.”

There exists a positive side to the police stop and search practices, at least according to extant literature. Reid (2009) argues that the practices are often used by police officers in the United Kingdom not only to reassure the public due to their visibility but also to deter or disrupt crimes that are therefore not committed. Indeed, according to this particular author, “…concerns about knife crime [in Britain] in the first half of 2008 have led, understandably, to calls from a variety of backgrounds for greater use of stop and search” (p. 178). Fabio et al (2011) are of the opinion that police stop and search practices have proved effective in crime-prone neighborhoods and it is only by coincidence that many crime hotspots are located in areas inhabited by minorities, and that research has shown crime to be intrinsically related to age. These authors argue that one of the most consistent outcomes in criminological studies has been the variation in offending over age, referred to as the age-crime curve.

On his side, Qureshi (2010) provides two justifications for police using the stop and search practices targeted at minorities, the young, or the economically disadvantaged. The first justification is that law enforcement officers are at liberty to use stereotypes to assist them in their decision-making processes, implying that the police are free to draw upon their experiences and cultural perceptions to summarize information about potential courses of action before selecting one and acting on it. The second justification is premised on the fact that it is virtually inconceivable for law enforcement officers to stop and search all sections of society equally, in large part because they operate within a set of working tenets to structure their decision-making process (Qureshi 2010).

Study Hypotheses

The present study aims to prove or reject the following three hypotheses:

  • H1: Racial and socioeconomic variables are more likely to influence the percentage of police stop and search practices prevalent in the neighborhoods.
    It has been described in the literature review that minorities and poor neighborhoods often experience a higher percentage of police stop and search practices than primarily White and wealthy neighborhoods, though this assertion is open to debate. Using the data from Lynnfield’s local police force, the researcher intends to prove or disapprove this assertion, which is critical in reinforcing the popularly held view that police stop and search practices are disparately oriented toward race and socioeconomic variables. Consequently, the ‘suspect work’ and/or ‘self-defined ethnicity’ become the independent variables, while ‘reason for stop/search’ becomes the dependent variable.
  • H2: There exists a significant relationship between the age variable and the probability of being stopped, searched, and arrested by law enforcement officers.
    It has been demonstrated in the literature that adolescents and young adults between the ages of 16 and 20 years are more prone to police stops and searches, while adults between the ages of 40 and 49 years are more prone to arrests. Proving this hypothesis will reinforce the widely held perception that the age variable is employed to make discriminatory and/or disproportionate police stop and search practices. Here, ‘suspect’s age’ becomes the independent variable, while ‘reason for search’, ‘stop location’, and/or ‘weapon status’ becomes the dependent variables.
  • H3: The ethnicity of the stop and search policy officer influences the nature of people who are stopped, searched, and/or arrested.
    A popular stream of literature demonstrates that White police officers are more likely to stop and search Blacks and other people from minority races, not to mention that the police officers are often accused by people of overstepping their mandate by harassing the search victims. In anticipation of either proving or rejecting this hypothesis, the ‘officer-defined ethnicity’ will be used as the independent variable, while suspect-defined ethnicity will be used as the dependent variable.

Findings & Analyses

Univariate Data Analysis

Table 1: Descriptive Statistics for the Selected Variables

Variable Measurement Frequency Mean Mode median
Suspects employment (N=10609)
Professional
Skilled
Semi-skilled
Manual non skilled
Unemployed
Nominal 707(6.7%)
2121(20%)
2972(28%)
2827(26.6%)
1982(18.7%
3.31
Self-defined ethnicity (N=10609)
Minorities (All other apart from Other White; White-British; White Irish)
Whites
Not Stated
Nominal 3158(29.7%)

6257 (59.0%)
1194 (11.3%)

Reason for Stop/Search (N=10609)
Officer intuition
Suspicious acting
Called to scene
Prior information
Public complain
Nominal 3325(31.3%)
3005(28.3%)
1374 (13.8%)
1464(13.8%)
1441(13.6%)
2.5
Suspect Age (N=10414)
0-10 years
11-20 years
21-30 years
31-40 years
41-50 years
51-60 years
61-70 years
71-80 years
Ordinal 5 (0.1%)
874 (8.4%)
3509 (33.7%)
3236(31.1%)
1782 (17.1%)
769(7.4%)
210 (2.0%)
29 (0.3%)
34.38
Officer-defined ethnicity (N=10609)
White
Black
Asian
Other
Not selected
Nominal 7103(67.0%)
1990(18.8%)
1253(11.8%)
141(1.3%)
122(1.1%)
1.51

Descriptive statistics are good at describing data, but not at establishing relationships between and among variables. From the above descriptive analysis, therefore, it is obvious that racial and socioeconomic variables influences the police stop and search practices (proves hypothesis 1), but it cannot be known for sure the strength of this relationship using mere descriptive statistics. From the descriptive statistics, however, it can be argued that around 18.7% of those who are stopped and searched by police are unemployed, while almost three in every ten (29.7%) come from minority backgrounds.

The descriptive statistics are able to prove hypothesis 2 because it can deduced that there exist a significant relationship between the age variable (mean score of 34.38 years) and the probability of being stopped, searched and arrested by police. Indeed, it can be noted from the analysis that almost a third (33.7%) of those stopped and searched are between 21 and 30 years old. This finding confirms what has been reported in many studies.

Lastly, the descriptive statistics around 67.0% of the law enforcement officers are white, but they are unable to establish a relationship of whether the ethnicity of the police officer actually influences the nature of people who are stopped, searched and/or arrested, as well as the treatment accorded to victims during the searchers.

Bi-variate Data Analysis: Cross-tabulations

Table 2: Racial & Socioeconomic Status versus Reason for Stop and Search

Reason for stop/search Total
N=10609
Officer intuition Suspicious acting Called to scene Prior information Public complain
Suspects employment
Professional
Skilled
Semi skilled
Manual/non-skilled
unemployed
225
699
912
879
610
190
571
852
822
570
82
292
391
358
251
120
296
404
371
273
90
263
413
397
278
707
2121
2972
2827
1982
Self defined ethnicity
White
Minorities
Not Stated
1945
1003
377
1746
948
311
850
367
157
869
415
180
857
415
169
6267
3148
1194

The table above acts to prove the hypothesis that minorities and socioeconomic variables are more likely to influence the percentage of police stop and search practices in Lynnfield neighbourhoods. Indeed while there are only 707(6.7%) who have been subjected to the stop and search practices for different reasons, ranging from officer intuition to public complaints, a total of 1982(18.7%) unemployed persons have been subjected to the same practices for the past one year. Employment status here is taken as an indicator to a person’s socioeconomic standing in society. Equally, it can be demonstrated that significant proportions of minorities (29.7%) have been subjected to the police stop and search practices for the past one year. Although the proportion of Whites who have been subjected to the practices is bigger than that of minorities, standing at 6267 (59.1%), it can be argued that Lynnfield is predominantly inhabited by Whites, making a figure of 29.7% minorities quite significant.

Table 3: Relationship between Age Variable & Reason for being Stopped & Searched

Reason for stop/search Total
N=10414
Officer intuition Suspicious acting Called to scene Prior information Public complain
Suspect Age (yrs)
0-10
11-20
21-30
31-40
41-50
51-60
61-70
71-80
2
267
1100
1016
543
234
72
13
0
229
986
967
502
212
42
3
1
107
399
426
265
121
31
5
2
138
516
416
242
109
28
4
0
133
508
411
231
94
38
4
5
874
3509
3236
1783
770
211
26

The table above demonstrates that over 3509 (33.7%) persons are exposed to police stop and search practices between the ages 21 and 30, while 3236 (31.1%) are exposed between the ages 31 and 40. Although the reasons for stop and searches varies across the distribution, with majority statistics revealing that many persons are stopped and searched as a result of either officer intuition or suspicious-looking character, the findings prove the hypothesis that there exists a substantial relationship between the age variable and the probability of being stopped and searched by law enforcement officers

Table 3 Ethnicity of Police Officer & Nature of People Stopped & Searched

Self-Defined Ethnicity Total
N=10609
Whites* Minorities* Not stated
Officer-Defined Ethnicity
White
Black
Asian
Other
Not recorded
6219
12
11
4
6
233
1695
1083
119
36
651
283
159
18
80
7103
1990
1253
141
122
Whites* = White British; White Irish and Other White
Minorities* = All ethnic groupings other that White British; White Irish and Other White

The analysis proves the third hypothesis by demonstrating that the ethnicity of the stop and search police officer to a large extent influences the nature of the people who are stopped and searched within the neighbourhoods. Indeed, it can be demonstrated that white police officers stopped and searched 6219 (87.6%) of Whites, Black police officers stopped and searched 16995 (85.2%) persons of minority ethnic backgrounds (mostly of African origin), while Asian police officers stopped and searched 1083 (86.4%) persons of minority backgrounds (mostly of Asian origin). This finding demonstrates that the ethnic background of a police officer is of critical importance in making the decision on the person to stop and search.

Elaboration & Significance Tests

Table 4: Suspects Employment Status versus Reason for Stop/Search versus Weapon Found

Was suspect carrying weapon Reason for Stop & Search
Officer Intuition Suspect behaviour Called to scene Prior information Public complaint TOTAL
No weapon Suspects Employment
Professional

Unemployed

217
598
187
563
82
250
118
270
90
276
694

1957

Knife Suspects Employment
Professional

Unemployed

4

5

0

1

0

1

0

1

0

1

4

9

Gun Suspects Employment
Skilled

Semi-skilled

1

1

0

0

0

0

0

0

0

0

1

1

The table above can elaborate the first hypothesis as it demonstrates that persons from poor neighbourhoods (unemployed) are more likely to carry knives than their well-off counterparts. This finding provides police with enough justification to conduct impromptu searches on persons from poor socioeconomic backgrounds.

Table 5: Chi Square Test on Suspect Employment Status & Reason for Stop/Search

Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 17.527(a) 16 .352
Likelihood Ratio 17.271 16 .368
Linear-by-Linear Association .492 1 .483
N of Valid Cases 10609

N.B: 0 cells (.0%) have expected count less than 5. The minimum expected count is 91.57.

The above results demonstrated that the results can be generalized to other study settings.

Summary & Discussion

The findings demonstrate that the stop and search practices undertaken by law enforcement officers are indeed influenced by racial stereotyping, age considerations, and socioeconomic status. All the three hypotheses have been proved following the above analysis. Not only has the researcher been able to prove that racial and economic variables are more likely to influence the percentage of police stop and search practices prevalent in neighbourhoods, but it has also been proved beyond reasonable doubt that there exists a significant relationship between the age variable and the probability of being stopped and searched by police. Additionally, it has also been proved that the ethnicity of the stop and search police officer influences the nature of people, who are stopped, searched and/or arrested.

A thread of existing literature (e.g., Petrocelli et al 2003; Taylor 2003; Qureshi 2010) demonstrates that profiling of persons by police based on several vectors, including race, wealth and age, has become a matter of national importance, and that the basis of profiling can be found in the conflict theory, which suggests that laws are formulated to serve the interests of the privileged and law enforcement agencies are used to suppress and control any section of society that poses a threat to the status quo (Castle 2008). As has been found in the present study regarding the relationship between age and stop/search practices, Fabio et al (2011, p S325) had found that “…residing in a disadvantaged neighbourhood during early adolescence may have an enduring effect of the age-crime curve throughout an individual’s life.” These findings demonstrate that individuals in certain age-categories may indeed be easy targets for frequent police stop and search practices.

To conclude, it’s clear that the findings provide useful insights into the concept of stop and search as it is applied today. The main urgent task for the law enforcement officers is to develop stop and search approaches that would not be seen to impede on the civil and human rights of the populace. As noted in the literature, law enforcement agencies should strive to ensure that stop and search practices are employed in the public domain to reassure the citizens due to their visibility (Reid 2009), but not to cause unwarranted fear and moral panic

Reference List

Burrell, A & Bull, R 2011, ‘A preliminary examination of crime analyst views and experiences of comparative case analysis’, International Journal of Police Science & Management, vol. 12 no. 1, pp. 2-15.

Castle, A 2008, ‘Measuring the impact of law enforcement on organized crime’, Trends in Organized Crime, vol. 11 no. 2, pp. 135-156.

Fabio, A, Tu, LC, Loeber, R & Cohen, J 2011, ‘Neighbourhood socioeconomic disadvantage and the shape of the age-crime curve’, American Journal of Public Health, vol. 101 no S1, pp. S325-332.

Farrell, A., Rumminger, J & McDevih, J n.d., New challenges in confronting racial profiling in the 21st century: Learning from research and practice. Web.

Petrocelli, M, Piquero, AR & Smith, MR 2003, ‘Conflict theory and racial profiling: An empirical analysis of police traffic stop data’, Journal of Criminal Justice, vol. 31 no. 1, pp. 1-11.

Qureshi, F & Farrell, G 2006, ‘Stop and search in 2004: A survey of police officer views and experiences’, International journal of Police Science & Management, vol. 8 no. 3, pp. 83-103.

Qureshi, F 2010, ‘A comparison of the British crime survey and police statistics for a southern English county’, International Journal of Police Science & Management, vol. 12 no. 2, pp. 220-237.

Ratcliffe, JH & Breen, C 2011, ‘Crime diffusion and displacement: Measuring the side effects of police operations’, The Professional Geographer, vol. 63 no. 2, pp. 230-243.

Reid, K 2009, ‘Race issues and stop and search: Looking behind the statistics’, The Journal of Criminal Law, vol. 73 no. 2, pp. 165-183.

Taylor, PN 2003, A national analysis of racial profiling and factors affecting the likelihood of traffic stops for African Americans. Web.

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