Arrest quality, conviction rates, community trust, use of force patterns, and accountability for misconduct.
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We cannot answer a single question about arrest quality, community trust, or use of force patterns.
NYPD tracks arrests but not convictions. They record use of force incidents but do not share the data. They receive thousands of complaints but substantiate almost none.
What This Means: We are spending $6 billion annually on policing without any ability to assess:
By crime type and precinct
We have conviction volume data but NOT arrest-to-conviction rates (since we lack arrest data). Here's what we know:
NYC Conviction Trends (2014-2024):
Conviction Class Distribution (2024):
Geographic Patterns (2024):
COVID-19 Impact:
All boroughs experienced 60-73% conviction drops in 2020. By 2024:
What's Missing:
To calculate true arrest-to-conviction rates, we need NYPD arrest data matched to these conviction outcomes. Without it, we cannot determine if 50% or 90% of arrests lead to convictions, or identify arrest quality problems.
We have conviction volume but not arrest-to-conviction rates. This partial data shows conviction trends and borough patterns, but cannot measure arrest quality without matching arrest data.
NYPD arrest data matched to conviction outcomes to calculate true conviction rates
FOIL requests to all 5 NYC District Attorney offices: "Arrest-to-conviction rates by crime type and originating precinct, with case disposition stages (2020-2025)" + NYPD arrest data by crime type and precinct
Early dismissal rates by crime type
If 30% of arrests are dismissed at arraignment, NYPD is making bad arrests that waste court resources and harm innocent people. Early dismissal rates reveal arrest quality problems.
Court disposition data showing dismissals at various stages
FOIL requests to NYC District Attorneys + Office of Court Administration: "Case dispositions by stage (arraignment, pre-trial, trial) with originating precinct and crime type (2020-2025)"
Wrongful arrest and exoneration rates
Wrongful arrests destroy lives and cost the city millions in settlements. Tracking exonerations and wrongful arrest lawsuits reveals if NYPD has systemic quality problems in investigations.
Exoneration data + wrongful arrest settlement data
FOIL requests: "NYPD settlements and judgments for wrongful arrest, false imprisonment, and malicious prosecution (2015-2025)" + Innocence Project data on NYPD-related exonerations
Evidence suppression rates
If courts frequently suppress evidence due to illegal searches or questionable probable cause, NYPD is violating constitutional rights and wasting resources on cases that cannot be prosecuted.
Court data on evidence suppression motions and outcomes
FOIL request to Office of Court Administration: "Evidence suppression motion outcomes by originating precinct and violation type (illegal search, lack of probable cause, etc.) for 2020-2025"
Conviction rates by precinct
If wealthy neighborhoods have 80% conviction rates but poor neighborhoods have 40%, that suggests discriminatory policing or lower-quality investigations in certain areas. Neighborhood patterns reveal equity issues.
Conviction rate data by precinct
Same as Q65 but analyzed by precinct to identify geographic disparities
CCRB complaints by type and precinct
Complaint rates reveal officer misconduct patterns and community friction. High complaint precincts indicate problematic policing practices that damage community trust.
Civilian Complaint Review Board (CCRB) complaint data
CCRB publishes complaint data. Requires analysis: "Total complaints by type (force, abuse of authority, discourtesy, offensive language), precinct, and outcome (2015-2025)"
Accountability for misconduct
If only 5% of complaints are substantiated, either most complaints are frivolous OR the system protects bad officers. Substantiation rates reveal whether accountability mechanisms work.
CCRB complaint outcome data
CCRB data: "Complaint outcomes (substantiated, unsubstantiated, exonerated, unfounded, officer unidentified) by complaint type and year (2015-2025)"
Public confidence surveys by neighborhood
Effective policing requires community cooperation. If communities do not trust police, they will not report crimes or cooperate with investigations. Trust levels predict clearance rates.
Community survey data on police trust and satisfaction
FOIL request + academic sources: "Community satisfaction surveys, trust metrics, and cooperation rates by precinct or neighborhood (2015-2025)"
Witness cooperation rates
Low witness cooperation explains low clearance rates. If communities will not talk to police, crimes cannot be solved. Cooperation rates are a leading indicator of community-police relations.
Detective investigation data on witness cooperation
FOIL request: "Investigation metrics including witness cooperation rates, community assistance, and information quality by precinct and crime type"
Impact on crime reporting and clearances
If broken trust causes 20% fewer crime reports and 10% lower clearance rates, that is a massive hidden cost of aggressive policing. Quantifying this cost informs policing strategy.
Econometric analysis correlating trust metrics with reporting and clearance rates
Requires academic research combining CCRB data, clearance data, and community survey data to model relationship between trust and outcomes
Use of force incidents by type and precinct
Use of force frequency reveals officer training quality, supervision effectiveness, and potential abuse patterns. High force rates may indicate poor de-escalation training or aggressive policing culture.
NYPD use of force incident reports
FOIL request: "Use of force incidents by type (firearm discharge, physical force, restraint, conducted electrical weapon), precinct, and outcome (2015-2025)"
Repeat offender analysis
If 10% of officers account for 50% of force incidents, those officers need retraining or removal. Concentration patterns identify problem officers before they cause serious harm.
Officer-level use of force data (anonymized for analysis)
FOIL request: "Distribution of use of force incidents per officer (anonymized), including repeat incident rates and disciplinary outcomes"
Investigation and discipline rates
If use of force incidents are rarely investigated or disciplined, that signals lack of accountability. Discipline rates reveal whether the system holds officers accountable for excessive force.
Use of force investigation outcomes and disciplinary actions
FOIL request: "Use of force incident investigations, outcomes (justified/unjustified), and resulting disciplinary actions (2015-2025)"
Benchmarking force patterns
If NYC officers use force 3x more frequently than peer cities, that indicates training or culture problems. Comparative data reveals if our force patterns are normal or excessive.
Use of force data from comparable police departments
Public records requests to LA, Chicago, Philadelphia, Houston police departments: "Use of force incident rates per 1,000 arrests or per 100,000 population (2015-2025)"
Zero Data on Arrest Quality: NYPD makes hundreds of thousands of arrests annually but does not track conviction rates, dismissal rates, or wrongful arrest settlements by precinct or officer. We have no way to assess whether arrests are justified or effective.
Zero Data on Community Trust: Effective policing requires community cooperation. If people will not report crimes or serve as witnesses because they distrust police, clearance rates suffer. Yet NYPD does not systematically measure or report community trust levels.
Zero Public Data on Use of Force: NYPD records use of force incidents but does not publicly share patterns, officer-level data, or disciplinary outcomes. Without this transparency, we cannot assess if force is used appropriately or hold problem officers accountable.
Minimal Accountability for Misconduct: CCRB receives thousands of complaints but substantiates a tiny percentage. Without transparency on complaint patterns and outcomes, the system protects bad officers rather than removing them.
The Pattern: Every question about quality and accountability is unanswerable because NYPD refuses to share data that every professional organization tracks. This is not incompetence - it is a strategy to avoid accountability for poor performance and misconduct.