Another reporter:
“Then why mention it?”
The chief looked irritated.
“Context.”
A reporter from a local Black newspaper asked:
“Does the department have a policy requiring pedestrians to produce identification absent reasonable suspicion of a specific offense?”
The chief answered:
“That depends on circumstances.”
“Which circumstances existed here?”
“I won’t litigate facts through media.”
“What crime did officers reasonably suspect?”
“The investigation is ongoing.”
“Did the caller report a crime?”
The chief’s jaw tightened.
“The caller reported suspicious activity.”
“What activity?”
“Again—”
The press conference went downhill.
The chief had spent years being good at press conferences.
That day, the questions had records behind them.
Three hours later, a leaked copy of the dispatch summary appeared online.
No race.
No observed crime.
No attempted entry.
No report of theft.
The union changed its statement.
Now the focus was “officer-safety concerns created by verbal resistance.”
My body-camera audio answered that.
Not publicly yet.
But investigators had it.
I was removed from direct handling of all evidence related to my own stop.
That frustrated me more than the shoulder.
Professionally, I hated sitting outside a room where people reviewed facts I knew by heart.
Ethically, it was necessary.
The broader case remained mine, but an independent federal team would decide whether my incident supported administrative, civil, or criminal action.
The first week after the stop, I worked from a separate conference room.
Every morning, I passed a glass wall behind which analysts reviewed stop data from the department.
Rows.
Dates.
Race.
Location.
Reason.
Search.
Contraband.
Arrest.
Force.
One analyst had been studying pedestrian encounters for three months.
She called me in.
“You can see aggregate case data, not yours.”
“Understood.”
She turned the screen.
Black residents made up eighteen percent of the department’s service population.
They accounted for forty-seven percent of pedestrian field interviews.
Fifty-four percent of discretionary searches.
Sixty-one percent of “failure to identify” warnings.
In the wealthiest three neighborhoods, the disparity was even larger.
The city attorney had previously argued socioeconomic patterns explained much of it.
Our statisticians controlled for location, time, call type, crime patterns, age, and other variables.
The gap narrowed.
It did not disappear.
The analyst clicked another tab.
Complaint outcomes.
Complaints from Black civilians alleging discourtesy or force were sustained at a markedly lower rate than comparable complaints supported by video.
“Why?”
I asked.
“We’re still modeling.”
“Supervisor assignment?”
“Strong factor.”
“Which supervisors?”
She hesitated.
Then highlighted names.
The sergeant who had shoved me appeared near the top.
My stomach tightened.
Not because I was surprised.
Because being physically touched by a data point changes something.
I had spent years training myself not to personalize cases.
Every complaint represented a person.
Every video represented a person.
Every row was somebody’s afternoon.
I knew that intellectually.
Now my shoulder hurt while I looked at the spreadsheet.
Rows felt less abstract.
One complaint stood out.
A seventeen-year-old Black boy had been stopped outside a grocery store six months earlier.
The sergeant said the boy resembled a burglary suspect.
He ordered him against a wall.
The teenager asked why.
The sergeant wrote that the boy became “verbally confrontational.”
The boy’s mother arrived.
She was arrested for obstruction after stepping between her son and the officer.
Body-camera video showed her saying:
“He’s seventeen. Tell me what happened.”