I will support targeted investments in small and midsize police departments for recruitment, retention, training, and officer support.

Adam Gray · California · Democratic

spending impact 0.70 specificity 0.86 extraction confidence 85%

Contest this claim

Occurrences

Invest to Protect Act of 2025 – This bipartisan legislation makes targeted investments in small and midsize police departments by providing funding for recruitment, retention, training, and officer support.

Gray endorsed the Invest to Protect Act of 2025, which would fund recruitment, retention, training, and officer support for small and midsize police departments.

GRAY BACKS EFFORTS TO SUPPORT CENTRAL VALLEY LAW ENFORCEMENT DURING NATIONAL POLICE WEEK
primary · press_release · model gpt-5.5

Evidence

The January 2026 appropriations package included Commerce, Justice, and Science appropriations; the House passed H.R. 6938 on January 8, 2026 by 397-28, and the Senate passed it before enactment on January 23, 2026.

This indicates enactment of the FY2026 CJS appropriations vehicle that normally funds DOJ law-enforcement grant accounts. It is a partial delivery signal if Gray voted with the large House majority, but the source does not itself prove a Gray-specific vote or a small/midsize-police targeting provision.

partial same_term A for effort

2026 United States federal budget
secondary · model gpt-5.5 · confidence 55%

Contest this evidence item

Public Law 119-74 is the enacted FY2026 Commerce, Justice, Science appropriations law, the appropriations title that funds Justice Department law-enforcement grant programs including COPS-related accounts.

The law is the strongest delivery-adjacent vehicle found before the lookback window. It supports federal investment in law-enforcement grant programs, but available evidence in this refresh does not prove a dedicated Adam Gray action targeted specifically to small and midsize departments for recruitment, retention, training, and officer support.

partial same_term A for effort

Commerce, Justice, Science, and Related Agencies Appropriations Act, 2026
secondary · model gpt-5.5 · confidence 62%

Contest this evidence item

The Clerk records H.R. 1, the One Big Beautiful Bill Act, passing 218-214. Adam Gray, Democrat of California, is listed as voting No.

This is a concrete official vote on a major law-enforcement-related spending law, but its law-enforcement investments were primarily immigration and border enforcement rather than the promised targeted investments for small and midsize police departments. Gray’s No vote does not deliver the promise and does not count as supportive action for this claim.

unresolved same_term

Roll Call 190 | Bill Number: H. R. 1
secondary · model gpt-5.5 · confidence 82%

Contest this evidence item

The enacted H.R. 1 law included large federal law-enforcement spending through immigration and border-enforcement accounts, not a targeted small/midsize local police recruitment, retention, training, and officer-support program.

Because Gray voted against H.R. 1 and the law did not match the small/midsize-police targeting in the commitment, this source does not support delivery. It helps avoid misclassifying broad law-enforcement spending as fulfillment of the specific campaign promise.

unresolved same_term

Public Law 119-21
secondary · model gpt-5.5 · confidence 70%

Contest this evidence item

Assessments

partial same_term A for effort

Same-term federal appropriations enacted through Public Law 119-74 funded Justice Department law-enforcement grant accounts, which is directionally consistent with supporting investments in police departments. However, the evidence does not establish that Adam Gray wrote, sponsored, or materially advanced a provision specifically targeted to small and midsize police departments for recruitment, retention, training, and officer support. The separate H.R. 1 evidence does not support fulfillment because Gray voted no and the law-enforcement spending was mainly immigration and border enforcement. This warrants partial credit rather than full delivery.

provider codex_cli · model gpt-5.5 · confidence 60%