Gera US Opportunity Profile — Methodology

What is the GUSOP?

The Gera US Opportunity Profile (GUSOP) is a county-level composite score (0–150) that combines four structural ACS variables into a single comparable index. A score of 100 represents the US national average exactly. Scores above 100 indicate above-average education and economic opportunity; scores below 100 indicate below-average.

The index is education-framed (the education component carries the highest weight) because GeraLearn's mission is skill-building — the index is intended to help learners understand their local education and labour market context, not as a general quality-of-life ranking.

Data sources

All tables from the ACS 5-Year Summary File flat-file downloads (2019–2023 (ACS 5-Year Estimates)), available without any API key at: https://www2.census.gov/programs-surveys/acs/summary_file/2023/table-based-SF/data/5YRData/. Published: October 2024. US Public Domain — no licence restrictions.

Formula (step by step)

All four components are relative to the US national benchmark, so the score automatically normalises as national averages change when new ACS data is released.

1. Step 1 — Education component (weight 40)

   Compute the county BA+ rate: (B15003_E022 + B15003_E023 + B15003_E024 + B15003_E025) / B15003_E001 × 100. Divide by the US national BA+ rate (35%) and multiply by 40. Cap at 60 (1.5× the full weight) to prevent extreme-outlier distortion.

   ed_score = min(60, county_baPct / 35 × 40)
2. Step 2 — Income component (weight 25)

   Divide the county median household income (B19013_E001) by the US national median ($78,538) and multiply by 25. Cap at 37.5 (1.5× the full weight).

   inc_score = min(37.5, county_income / 78538 × 25)
3. Step 3 — Employment component (weight 25)

   Employment rate = 1 − (B23025_E005 / B23025_E002). National employment rate = 1 − 5.2% = 0.948. Divide county employment rate by national and multiply by 25. Cap at 37.5.

   emp_score = min(37.5, (1 − county_unempRate/100) / 0.948 × 25)
4. Step 4 — Mobility component (weight 10)

   Compute county mobility rate = (B08301_E010 + B08301_E019) / B08301_E001 × 100 (public transit + WFH combined). Divide by the national mobility rate (5.9%) and multiply by 10. Cap at 15. This component rewards commute flexibility — both WFH and transit-served counties score higher.

   mob_score = min(15, county_mobilityPct / 5.9 × 10)
5. Step 5 — Composite GUSOP

   Sum the four components and round to nearest integer. A county matching the national average on all four metrics scores exactly 100.

   GUSOP = round(ed_score + inc_score + emp_score + mob_score)

Honesty gates

• No fabrication: Every county metric comes directly from the Census flat-file column listed above. No interpolation, no estimation, no modelling.
• Missing data: Counties missing any of the four ACS table values are excluded from the dataset (not scored). The current dataset contains {ACS1_COUNTIES.length} complete-data counties.
• Score cap: Each component is capped at 1.5× its weight to prevent extreme outliers (e.g. San Francisco's very high transit share) from pushing the composite above 150.
• Currency: ACS 5-Year Estimates average five years of survey responses (2019–2023). Individual-year figures may differ. Income values are in nominal USD, not inflation-adjusted across years.

Licence

US Census Bureau data is US Public Domain — no copyright restriction on reproduction or reuse. The Gera US Opportunity Profile (GUSOP) formula and the GeraLearn presentation layer are original GeraLearn work. Citation should read: “Gera US Opportunity Profile, computed by GeraLearn from US Census Bureau ACS 2019–2023 data.”

Update cadence

The GUSOP is updated annually when the Census Bureau releases new ACS 5-Year Estimates (typically September–November each year). Current data: 2019–2023 (ACS 5-Year Estimates), released October 2024. GeraLearn last recomputed: 2026-06-20.