Bill Overview
Title: Community-Based Workforce Development Act
Description: This bill provides grants to expand workforce training programs for high-skill, high-wage, or in-demand industry sectors.
Sponsors: Sen. Casey, Robert P., Jr. [D-PA]
Target Audience
Population: Individuals seeking or undergoing training for high-skill, high-wage, or in-demand industry sectors
Estimated Size: 20000000
- The bill focuses on high-skill and high-wage industry sectors which are prevalent across many industries globally, including tech, healthcare, finance, etc.
- Workforce development impacts individuals seeking employment and those currently employed who need skill upgrades.
- The act provides grants which typically benefit educational institutions, training centers, and organizations involved in workforce development.
- Increased training opportunities can also impact organizations and companies that rely on skilled workers.
- Millions of people globally are in or transitioning to high-skill, high-wage industries.
Reasoning
- The policy targets individuals in high-skill, high-wage, or in-demand industry sectors, thus we should simulate people from relevant backgrounds such as tech, healthcare, and finance.
- The budget will not necessarily allow for immediate widespread impact on all individuals but can enhance existing programs or create new ones in areas with significant demand.
- Some individuals may not perceive immediate benefits (low to medium impact) even if they are in the target population due to program rollout dynamics and accessibility.
- Due to the high importance of the policy's target areas, ongoing professional development is crucial, necessitating consideration of potential long-term benefits in well-being.
- People in locations with higher industry growth might experience higher impacts due to more opportunity availability.
Simulated Interviews
Software Engineer (San Francisco, CA)
Age: 35 | Gender: male
Wellbeing Before Policy: 7
Duration of Impact: 5.0 years
Commonness: 5/20
Statement of Opinion:
- Excited about the opportunity to gain management skills.
- I believe the grants will help fund necessary transition programs that might allow me to step up in my career faster.
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 | 8 |
| Year 10 | 10 | 8 |
| Year 20 | 10 | 9 |
Nursing Professional (Boston, MA)
Age: 29 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 3.0 years
Commonness: 8/20
Statement of Opinion:
- I am keen to specialize in a field with a shortage of skilled workers like geriatrics.
- The added programs could finally make the training I need more accessible and affordable.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 6 |
| Year 2 | 7 | 6 |
| Year 3 | 8 | 6 |
| Year 5 | 8 | 7 |
| Year 10 | 8 | 8 |
| Year 20 | 9 | 9 |
Data Analyst (Austin, TX)
Age: 42 | Gender: female
Wellbeing Before Policy: 5
Duration of Impact: 4.0 years
Commonness: 7/20
Statement of Opinion:
- I've been wanting to get into machine learning, which is a tough field to enter without proper training.
- Hopefully, this policy will increase the availability of affordable courses in cutting-edge technologies.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 5 |
| Year 2 | 7 | 5 |
| Year 3 | 7 | 6 |
| Year 5 | 7 | 6 |
| Year 10 | 8 | 7 |
| Year 20 | 8 | 8 |
Manufacturing Worker (Detroit, MI)
Age: 50 | Gender: male
Wellbeing Before Policy: 4
Duration of Impact: 7.0 years
Commonness: 6/20
Statement of Opinion:
- I am skeptical but hopeful. Training opportunities in robotics could offer a new path in my career.
- The policy might bring those much-needed programs to my area.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 5 | 4 |
| Year 2 | 6 | 4 |
| Year 3 | 7 | 5 |
| Year 5 | 8 | 6 |
| Year 10 | 8 | 7 |
| Year 20 | 9 | 8 |
Freelance Graphic Designer (Portland, OR)
Age: 24 | Gender: other
Wellbeing Before Policy: 5
Duration of Impact: 2.0 years
Commonness: 9/20
Statement of Opinion:
- I'm independent, but pursuing new skills is tough financially.
- If training can supplement my income, it will be a real game-changer.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 5 |
| Year 2 | 6 | 5 |
| Year 3 | 7 | 6 |
| Year 5 | 8 | 7 |
| Year 10 | 8 | 8 |
| Year 20 | 9 | 8 |
Account Manager in Financial Services (Atlanta, GA)
Age: 60 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 3.0 years
Commonness: 4/20
Statement of Opinion:
- I'm near retirement, but upskilling could extend my career.
- I hope there will be space for older workers wanting to transition into new areas.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 6 | 6 |
| Year 3 | 7 | 6 |
| Year 5 | 7 | 6 |
| Year 10 | 7 | 6 |
| Year 20 | 8 | 7 |
Environmental Scientist (Seattle, WA)
Age: 27 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 5.0 years
Commonness: 5/20
Statement of Opinion:
- There are endless possibilities in renewables, but getting the right skills is critical.
- I hope the policy channels more grants into cutting-edge industry training related to sustainability.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 7 |
| Year 2 | 8 | 7 |
| Year 3 | 9 | 8 |
| Year 5 | 9 | 8 |
| Year 10 | 9 | 9 |
| Year 20 | 9 | 9 |
Financial Planner (Minneapolis, MN)
Age: 32 | Gender: female
Wellbeing Before Policy: 5
Duration of Impact: 1.0 years
Commonness: 3/20
Statement of Opinion:
- Certifications are costly, but essential for growth in my line of work.
- I hope more programs are subsidized, making them accessible for financial professionals like me.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 5 |
| Year 2 | 7 | 5 |
| Year 3 | 7 | 6 |
| Year 5 | 8 | 6 |
| Year 10 | 9 | 7 |
| Year 20 | 9 | 9 |
Cybersecurity Specialist (New York, NY)
Age: 45 | Gender: male
Wellbeing Before Policy: 8
Duration of Impact: 5.0 years
Commonness: 7/20
Statement of Opinion:
- I'm already in demand in my field, but further education could formalize my expertise.
- This policy could facilitate the acquisition of advanced credentials by providing necessary financial support.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 8 |
| Year 2 | 8 | 8 |
| Year 3 | 8 | 8 |
| Year 5 | 9 | 9 |
| Year 10 | 9 | 9 |
| Year 20 | 10 | 9 |
Project Manager (Chicago, IL)
Age: 39 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 4.0 years
Commonness: 5/20
Statement of Opinion:
- It's hard to keep up with the latest in project management standards and certifications.
- Maybe this policy can lead to more training programs addressing construction-specific project management.
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 | 8 | 8 |
| Year 10 | 9 | 8 |
| Year 20 | 9 | 9 |
Cost Estimates
Year 1: $500000000 (Low: $400000000, High: $600000000)
Year 2: $510000000 (Low: $410000000, High: $610000000)
Year 3: $520000000 (Low: $420000000, High: $620000000)
Year 5: $540000000 (Low: $440000000, High: $640000000)
Year 10: $600000000 (Low: $500000000, High: $700000000)
Year 100: $750000000 (Low: $650000000, High: $850000000)
Key Considerations
- The effectiveness of the training programs in equipping the workforce with the necessary skills to meet industry demands.
- The ability of partnerships with industries and educational institutions to align the curriculum with evolving high-skill job market needs.
- Potential regional disparities in the program’s rollout and impact, necessitating tailored approaches in different areas.