Bill Overview
Title: DHS Basic Training Accreditation Improvement Act of 2021
Description: This bill addresses issues involving accreditation and law enforcement training, research, and development at the Department of Homeland Security (DHS). Specifically, the bill requires DHS to report to the congressional homeland security committees on the accreditation status for each basic training program within DHS. If a basic training program loses accreditation, the relevant DHS component shall notify the department within 30 days after such loss. The Under Secretary for Science and Technology must carry out research and development of systems and technologies to enhance access to training offered by the Federal Law Enforcement Training Centers to state, local, tribal, and territorial law enforcement, with particular attention to rural or remote communities, to enhance domestic preparedness for and collective response to terrorism and other homeland security threats.
Sponsors: Rep. Demings, Val Butler [D-FL-10]
Target Audience
Population: Law enforcement personnel involved with DHS training programs
Estimated Size: 180000
- The bill focuses on improving accreditation and training for law enforcement personnel who are trained by the DHS.
- The target population includes law enforcement officers who are a part of DHS training programs, specifically those who might be affected by changes in accreditation.
- This indirectly affects state, local, tribal, and territorial law enforcement agencies that rely on DHS training, particularly in rural or remote locations.
- If some programs lose accreditation, it could require changes to training protocols, impacting the law enforcement officers undergoing such training.
Reasoning
- The policy focuses on enhancing law enforcement training, especially for those in rural and remote areas. This could improve skills and preparedness for terrorism and other threats.
- Budget limitations imply that not all training programs might immediately benefit or achieve accreditation improvements. Some areas might see more benefits based on prioritization.
- Costs of new technologies and systems may limit the extent of implementation, affecting how widespread the impact is.
- There is likely to be no direct impact on civilians or law enforcement officers not involved in DHS training, but indirect effects could enhance public safety through better-trained officers.
Simulated Interviews
Police Officer (Texas)
Age: 36 | Gender: male
Wellbeing Before Policy: 7
Duration of Impact: 10.0 years
Commonness: 8/20
Statement of Opinion:
- I hope this policy will allow us in rural areas to receive better training without having to travel far.
- Loss of accreditation in any programs could delay our training and affect our readiness.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 7 |
| Year 2 | 8 | 7 |
| Year 3 | 9 | 6 |
| Year 5 | 9 | 6 |
| Year 10 | 9 | 6 |
| Year 20 | 8 | 5 |
DHS Training Coordinator (New York)
Age: 45 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 5.0 years
Commonness: 6/20
Statement of Opinion:
- This policy will ensure we maintain high standards and can improve our training delivery.
- I worry about the budget constraints and potential pressure it could put on our resources.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 7 | 6 |
| Year 3 | 7 | 6 |
| Year 5 | 8 | 6 |
| Year 10 | 7 | 6 |
| Year 20 | 7 | 6 |
State Trooper (California)
Age: 29 | Gender: female
Wellbeing Before Policy: 5
Duration of Impact: 10.0 years
Commonness: 7/20
Statement of Opinion:
- As a new trooper, I hope this policy makes advanced training more accessible.
- Not directly impacted yet, but it's great training programs might improve in the future.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 5 | 5 |
| Year 2 | 6 | 5 |
| Year 3 | 7 | 6 |
| Year 5 | 7 | 6 |
| Year 10 | 7 | 6 |
| Year 20 | 7 | 6 |
Sheriff in a rural area (Montana)
Age: 50 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 10.0 years
Commonness: 4/20
Statement of Opinion:
- This policy is crucial for us in rural areas to get better access to necessary training.
- Budget constraints at state level mean we often rely on DHS training.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 5 |
| Year 2 | 7 | 5 |
| Year 3 | 8 | 5 |
| Year 5 | 9 | 5 |
| Year 10 | 9 | 5 |
| Year 20 | 8 | 5 |
DHS Technology Developer (Florida)
Age: 34 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 15.0 years
Commonness: 5/20
Statement of Opinion:
- This policy gives me a chance to develop cutting-edge training solutions heightening security.
- Limited funding could restrict technological advancements.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 7 |
| Year 2 | 8 | 7 |
| Year 3 | 8 | 7 |
| Year 5 | 9 | 7 |
| Year 10 | 9 | 7 |
| Year 20 | 8 | 7 |
Local Police Chief (Nevada)
Age: 41 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 10.0 years
Commonness: 6/20
Statement of Opinion:
- This policy could mean better preparedness for my officers if handled well.
- Wary of how logistics will affect roll-out in remote areas.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 6 |
| Year 2 | 8 | 6 |
| Year 3 | 8 | 6 |
| Year 5 | 9 | 6 |
| Year 10 | 8 | 6 |
| Year 20 | 7 | 5 |
Federal Security Analyst (Michigan)
Age: 38 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 5.0 years
Commonness: 7/20
Statement of Opinion:
- The policy is an important step towards maintaining DHS's reputation and efficacy.
- However, managing accreditation and ensuring technology reach could be challenging.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 7 | 6 |
| Year 3 | 7 | 6 |
| Year 5 | 7 | 6 |
| Year 10 | 7 | 6 |
| Year 20 | 6 | 5 |
Tribal Law Enforcement Officer (Oregon)
Age: 52 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 15.0 years
Commonness: 3/20
Statement of Opinion:
- Hoping this policy caters specifically to underserved areas like ours.
- Additional funding and focus on tribal areas would significantly boost morale and preparedness.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 5 |
| Year 2 | 7 | 5 |
| Year 3 | 8 | 5 |
| Year 5 | 8 | 5 |
| Year 10 | 8 | 5 |
| Year 20 | 7 | 5 |
Border Patrol Agent (Arizona)
Age: 32 | Gender: male
Wellbeing Before Policy: 7
Duration of Impact: 20.0 years
Commonness: 8/20
Statement of Opinion:
- I am eager to see improved training systems come to fruition.
- Worried about possible delays or gaps if accreditation changes affect us.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 7 |
| Year 2 | 8 | 7 |
| Year 3 | 9 | 7 |
| Year 5 | 9 | 7 |
| Year 10 | 9 | 6 |
| Year 20 | 9 | 6 |
Policy Analyst for Department of Homeland Security (Washington D.C.)
Age: 47 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 5.0 years
Commonness: 6/20
Statement of Opinion:
- This policy will help refine and improve training standards, which is crucial.
- Contemplating the efficiency of fund usage and realization of desired outcomes.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 7 | 6 |
| Year 3 | 8 | 6 |
| Year 5 | 8 | 6 |
| Year 10 | 8 | 6 |
| Year 20 | 7 | 6 |
Cost Estimates
Year 1: $150000000 (Low: $100000000, High: $200000000)
Year 2: $160000000 (Low: $110000000, High: $210000000)
Year 3: $170000000 (Low: $120000000, High: $220000000)
Year 5: $190000000 (Low: $140000000, High: $240000000)
Year 10: $0 (Low: $0, High: $0)
Year 100: $0 (Low: $0, High: $0)
Key Considerations
- Ensuring ongoing accreditation compliance will require consistent oversight and potential dedicated staffing.
- The technological enhancements must be interoperable with existing state and local systems.
- Long-term cost savings depend on effective integration and utilization of new training technologies.