FlockFacts

Methodology

This site is generated by an automated pipeline. There is no human reviewer. Articles are collected from public feeds, classified by a language model, clustered into incidents, and published on a nightly schedule; name redaction and evidence tiering are applied by fixed rules, not by editorial judgement on the day. Nothing here is an opinion piece; it is a sorted index of other people's records. What that costs you is set out under Known limitations, and every row links to the source so you can check it against the original.

Collection

News coverage mentioning Flock Safety, automated license plate readers, or ALPR is collected daily from public RSS feeds, time-boxed back to the company's founding year (2017). Each article's full text is extracted and classified into one of a small set of categories (crime solved, abuse or misconduct, false positive or misidentification, other). Duplicates are dropped by URL.

Audit

Every event is independently re-read by a language model that extracts the primary entity, the jurisdiction, the technical role the system played, and the best available outcome on record, then searches for corroborating sources. It assigns an evidence tier:

Incidents

Events describing the same matter are clustered into incidents by entity and jurisdiction token overlap, so one arrest covered by five outlets counts once.

Known limitations

Corrections

If a row is wrong, the fix is a better source. See About for how to send one.