South LA, CA 2024 - Pedestrian Stops

South LA, CA 2025

PEDESTRIAN STOPS

This section examines pedestrian stops, which are stops for which the recorded reason was anything other than “traffic violation.”

Note: The racial categorization scheme mandated by California’s Racial and Identity Profiling Act (RIPA) requires law enforcement agencies to record stops of “Middle Eastern or South Asian” people separately from stops of “Asians” (that is, East Asians), and does not distinguish Middle Eastern from South Asian people. Because South Asians cannot be distinguished from non-Asian Middle Easterners in this dataset, stops of “Middle Eastern or South Asian” people are not counted as stops of “Asians” in the analyses on this page.

Under RIPA, all California law enforcement agencies are required to report data on all stops to the California Attorney General. In June 2022, the Los Angeles County Office of the Inspector General issued a report detailing a significant underreporting of stops by LASD in its RIPA reporting in 2018 and 2019. Though CPE has received no indication that the issues leading to this underreporting were resolved, South LA Station saw a marked increase in recorded stops in 2022 and 2023, which could indicate better adherence to RIPA protocol. CPE ran all the analyses presented here excluding pre-2022 data to see if underreporting impacted our findings, but found that the results were not significantly impacted.

PEDESTRIAN STOPS BY RACIAL GROUP

According to Los Angeles County Sheriff’s Department South LA Station data on pedestrian stops recorded between 2019 and 2023:

37% of all people officers stopped were Black, who made up 19% of the population of the South LA patrol area.
51% of all people officers stopped were Latinx, who made up 62% of the population of the South LA patrol area.
10% of all people officers stopped were White, who made up 9% of the population of the South LA patrol area.

Note: These analyses only include resident demographic data from areas of Los Angeles County that are patrolled by South LA Station deputies. For more information, see the Resident Demographics chart under the Context tab of this assessment.

More information

What does this show?

Each dark blue bar shows the percentage of the total stops recorded in the report period that were of people in one racial group. The orange bars show the percentage of the resident population that are people of the same racial group. Hovering over the blue bars shows the number of stops that makes up that percentage.

Comparisons between the number of Asian people stopped and the number of Asian residents are not exact. Because the Census categorizes Middle Eastern people as White and South Asians as Asian, and because California mandates a different racial categorization scheme (as noted above), the analysis presented here is limited to comparing this agency’s stops of “Asians” (that is, stops of East Asian people) to Census data about the percentage of the population that is Asian (including South Asian residents). This tends to understate the percentage of Asian residents who were stopped.

How was this calculated?

We first took the average total recorded stops per year and calculated the percentage that were recorded of people of each racial group. Then we compared those percentages to the percentages of the resident population that are of each racial group. See the Data Notes tab for information on how we define racial groups.

We measure a non-traffic stop as a single record of a person being stopped by police, regardless of the number of officers involved (if multiple people are stopped at the same time, each person is counted as a separate stop). We encourage departments to define a non-traffic stop as any such incident. Some departments limit their data to stops that result in a citation, in which case we would not be able to analyze their records. Our guidance on collecting data has more information on how to report non-traffic stops.

We generally use all pedestrian stop data provided by departments, including incomplete years of data. However, certain analyses require complete years on data, so time periods may vary across charts.

We use local demographic data (from the Census Bureau’s American Community Survey 5-year estimates) as the most straightforward and complete representation of the local population. The use of Census data also allows us to perform standardized analyses across law enforcement agencies. We recognize that this measure of demographics may not capture the entire population of individuals with whom police interact. However, the analyses on this page can shed light on the role that local demographics may play in any observed disparities.

Data required for this analysis:

PEDESTRIAN STOPS BY YEAR

The total number of pedestrian stops recorded each year with complete data ranged from a high of 3,463 in 2022 to a low of 554 in 2020.

More information

What does this show?

This chart shows the total number of pedestrian stops recorded during each year of the assessment period for all racial groups combined.

Disruptions related to the COVID 19 pandemic may have affected the volume of police-community interactions recorded in 2020 and 2021, although the extent of this impact likely varies by jurisdiction according to the local policies and restrictions implemented in response to the outbreak. It is worth noting whether or the extent to which racial disparities persisted over this time period, despite the reduction in overall police activity.

How was this calculated?

Data required for this analysis:

PEDESTRIAN STOP RATES BY RACIAL GROUP

After using a statistical technique called regression analysis to account for the influence of different crime rates, poverty levels, and percent of Black residents in neighborhoods:

We take into account the share of Black residents, crime rates, and poverty levels in a neighborhood because these factors affect the likelihood that a person of any racial group in a neighborhood will have police contact. For details on CPE’s regression analysis, see “More Information” below.

More information

What does this show?

This infographic displays findings from CPE’s regression analysis, a statistical technique that allows CPE to investigate differences in pedestrian stop rates by race, taking into account other socioeconomic factors that may affect policing strategies and deployment. Specifically, this regression tests how much more or less likely each racial group is than White pedestrians to be stopped in a neighborhood with an average poverty rate, crime rate, and percentage of Black residents – three factors commonly associated with increased rates of police contact. The results of this analysis show the size of racial disparities in pedestrian stops that remain even when the influence of poverty levels, crime rates, and the percentage of Black residents across neighborhoods are removed from the equation.

We take into account the share of Black residents in a neighborhood because this factor affects the likelihood that a person of any racial group in a neighborhood will have police contact. This relationship between police presence and the percent of Black residents in a neighborhood is, in part, a result of systemic racism and structural disadvantage (for example, a lack of community services can lead to more calls for police service). But police-driven factors, such as departmental policy or officer behavior, also contribute to increased police activity in neighborhoods with more Black residents. Our model cannot precisely distinguish the extent to which this increased police activity is due to reasons within a department’s control, or reasons outside a department’s control. By accounting for the neighborhood share of Black residents, the results of this analysis therefore may under-estimate the extent to which departmental factors contribute to observed disparities between Black and White people.

How was this calculated?

To represent neighborhoods, we use Census tracts — small geographic areas of approximately 4,000 residents — as defined by the Census Bureau. We use publicly available Census data to measure the percentage of Black residents in each neighborhood.

To measure serious crime rates, we count crimes in each neighborhood that are recorded by the department. Specifically, we count reports of Part 1 offenses. The FBI’s Uniform Crime Reporting Statistics defines Part 1 offenses as: murder and non-negligent homicide, rape (legacy and revised), robbery, aggravated assault, burglary, motor vehicle theft, larceny theft, and arson. Racial groups which made up less than 2% of all incidents, or which had fewer than 40 total incidents, were excluded from this analysis (see the Data Notes tab for information on how we define racial groups).

We measure a pedestrian stop as a single record of a person being stopped by police, regardless of the number of officers involved (if multiple people are stopped at the same time, each person is counted as a separate stop). We encourage departments to define a pedestrian stop as any such incident. Some departments limit their data to stops that result in a citation, in which case we would not be able to analyze their records. Our guidance on collecting data has more information on how to report pedestrian stops.

South LA Station deputies patrol an area that includes multiple towns and unincorporated areas, and the boundaries of this patrol area do not perfectly align with the boundaries of Census tracts. Resident demographic data for the Station’s patrol area were therefore not readily available from the Census Bureau, so this assessment uses resident demographic data provided by Los Angeles County’s Internal Services Department.

Data required for this analysis:

Incident unique identifier
Date of incident
Pedestrian's racial group
Location of incident (i.e. street address, including zipcode or latitude/longitude)
Crime unique identifier
Crime date of incident
Crime offense (NIBRS/UCR) classification or description
Crime location (i.e. street address, including zipcode or latitude/longitude)

PERCENTAGE OF PEDESTRIAN STOP FREQUENCY EXPLAINED BY NEIGHBORHOOD FACTORS

This chart displays findings from CPE’s regression analysis, a statistical technique that tests how much neighborhood poverty levels, crime rates, and share of Black residents—three common explanations for increased police contact—contribute to how often all recorded stops occur.

Statistical analysis showed that neighborhood crime rates, poverty, and share of Black residents explained 33% of the frequency of pedestrian stops, while 67% was not explained by these factors.

For details on CPE’s regression analysis, see “More Information” below.

More information

What does this show?

This chart shows the total number of pedestrian stops recorded during each year of the assessment period for all racial groups combined.

How was this calculated?

Data required for this analysis:

COMPARING SEARCH RATES AT PEDESTRIAN STOPS

According to Los Angeles County Sheriff’s Department South LA Station data, once pedestrians were stopped:

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What does this show?

This visualization shows, out of the same number of stopped pedestrians, how many pedestrians in each racial group were then searched.

How was this calculated?

We first divided the number of stops that involved a search for each racial group by the number of stops of that racial group. We then multiplied that number by 1,000 to get the per 1,000 stops rate.

Police are typically required to search people they arrest. When the search reason is provided in the law enforcement agency’s data, these mandatory searches are excluded from this analysis because they are not necessarily based on an officer’s discretionary evaluation of whether they expect to find contraband. Otherwise, this analysis includes any search that was not recorded as mandatory, including both discretionary searches and those with no search reason provided.

See the Data Notes tab for information on how we define racial groups.

Data required for this analysis:

SEARCH REASON AT PEDESTRIAN STOPS

According to Los Angeles County Sheriff’s Department (LASD) South LA Station data, once pedestrians were stopped:

Consent and Officer Safety searches generally require the lowest threshold of evidence of actual wrongdoing. Ineffective, lacking evidence, and increasing the risk of use of force, LASD should consider the necessity of and requirements behind conducting these kinds of searches. Some agencies—like the California State Highway Patrol—and states like Oregon and New Jersey have banned consent searches without reasonable, articulable suspicion of criminal wrongdoing.

Search reasons with low yield rates may suggest that deputies’ suspected reasons for the search may not have been justified. These types of discretionary searches are also associated with higher rates of use of force. These data may present an opportunity for the agency to intervene or implement changes in their search policies.

More information

What does this show?

This analysis shows whether police search people of different racial groups for the same search reasons, or whether particular search types disproportionately target people of particular racial groups. When certain types of searches that are known to escalate to use of force disproportionately target members of certain racial groups, law enforcement leadership should investigate the policies and behaviors that may be contributing to those disparities.

How was this calculated?

For the first chart, we grouped stops by the reason for the search and the racial group of the person searched. We determined what proportion of stops involved each type of search for each racial group by dividing the number of searches for each search reason for a particular racial group by the total number of stops of people of that racial group. For the second chart, we divided all contraband found searches into groups based on the kind of contraband found and then by the search reason that precipitated the discovery. From there, we divided those searches by the total number of searches for each kind of contraband found.

See the Data Notes tab for information on how we define racial groups.

Data required for this analysis:

COMPARING SEARCH OUTCOMES AT PEDESTRIAN STOPS

One common explanation for racial disparities in stops and searches is that members of some racial groups may be more likely to have contraband. To assess this, this analysis examines how often deputies recorded discovering contraband such as alcohol or stolen goods in discretionary searches—searches that are not mandatory but instead based on deputies’ discretion—of people in each racial group.

Across all searches:

When discovery rates are lower for people deputies search at disproportionately high rates, this may indicate that deputies more frequently decide to search members of this group at a lower level of suspicion. When discovery rates are relatively similar across racial groups, it suggests that significant racial disparities in stop and search rates cannot be justified by differences in the outcomes of those searches. It’s also important to note that the discovery of contraband at pedestrian stops is generally rare and not indicative of a serious crime. For details on the types of contraband most often discovered, please see “More Information” below.

More information

What does this show?

One common explanation for why members of some racial groups are stopped or searched at different rates is that they may be more likely to have contraband. To assess this, we looked at whether searches of pedestrians in different racial groups resulted in contraband being found at different rates. For each racial group, we separated all searches into the percentage that resulted in contraband found and the percentage that resulted in no contraband found. In the second chart, we separated all searches that yielded contraband into the percentage of specific types of contraband found.

In the first chart, the darker portion of each bar (on the bottom) shows the percentage of all searches of pedestrians of that racial group that ended with contraband found, while the lighter portion of the bar (at the top) shows the percentage where no contraband was found. Hovering over a bar shows the number of searches that makes up that percentage.

It is important to compare this chart to the stop rates for people, above, to identify which groups may be experiencing a stop rate that may be driving high totals of contraband found.

How was this calculated?

We took the total recorded searches of pedestrians of each racial group and calculated the percentage that did and did not reveal contraband.

See the Data Notes tab for information on how we define racial groups.

Data required for this analysis:

PEDESTRIAN STOP REASONS BY RACIAL GROUP

This analysis investigates which stop reasons are most often recorded for people of each racial group and overall.

Departments should investigate which stop reasons are more often recorded in stops of groups experiencing racial disparities, as well as what stop reasons are more often recorded overall. Stops that are not based on direct risks to public safety or evidence of criminal activity are less likely to be efficient or productive uses of investigative resources.

More information

What does this show?

Each colored bar shows the percentage of the total pedestrian stops of that racial group for which a stop reason was recorded. Hovering over a colored bar shows the number of stops that makes up that percentage. Any stop reason that was recorded in a high number of incidents will influence the racial makeup of pedestrian stops overall.

How was this calculated?

We took the total recorded stops of pedestrians of each racial group and calculated the percentage for which each reason was recorded. We then grouped these percentages according to stop reason.

We combine categories of reasons for easier interpretation. See the Data Notes for details on how these categories are created and how racial groups are defined.

Data required for this analysis:

PEDESTRIAN STOP OUTCOMES BY RACIAL GROUP

This analysis investigates which stop outcomes are most often recorded for pedestrians of each racial group and overall. According to Los Angeles County Sheriff’s Department South LA Station data:

39% of all pedestrian stops resulted in a warning or no action taken, which suggests they were unlikely to be based on any risks to public safety or evidence of criminal activity.
Black pedestrians were arrested 1.3 times as often as White pedestrian. They were also released with a warning or no action taken at similar rates to White pedestrians who were stopped.
Latinx pedestrians were arrested 1.3 times as often as White pedestrian. They were also released with a warning or no action taken at similar rates to White pedestrians who were stopped.

Pedestrians who are more likely to be stopped despite not committing any crime or infraction are unnecessarily exposed to a greater risk of experiencing harmful stop outcomes including searches, arrests, and use of force. Reducing these kinds of low-level stops can help reduce racial disparities in policing and free up departmental resources for higher priority public safety needs.

More information

What does this show?

Each colored bar shows the percentage of all stops of pedestrians of that racial group for which that stop outcome was recorded. Hovering over a bar shows the number of stops that make up that percentage.

Findings on recorded pedestrian stop outcomes should be interpreted in context with findings on racial disparities in recorded stop reasons and searches at pedestrian stops. Pedestrians of racial groups who are stopped more frequently are often also more likely to be stopped for reasons that tend to be less related to public safety, which may increase their likelihood of being released with a warning or no action taken. Pedestrians who are more likely to be stopped despite not committing any crime or infraction are subject to a greater burden of police contact, which increases the likelihood of a cascade of interrelated harms including arrest, criminalization, and even injury or death.

How was this calculated?

We took the total recorded stops of pedestrians in each racial group and calculated the percentages for which each enforcement outcome was recorded. We then grouped these percentages according to enforcement outcome.

We only count the most serious outcome for a given stop (e.g. if a person receives a citation and is also arrested, we only count the arrest). The order from most serious to least serious outcome is:

We combine categories of outcomes for easier interpretation. See the Data Notes tab for details on how these categories are created and how racial groups are defined.