Labor Force Status by Nativity (ACS)

How Georgia's native-born, foreign-born, naturalized and noncitizen residents 16 and over participate in the labor force - participation, employment and unemployment rates from ACS 5-year estimates for the state and its larger immigrant-receiving counties.

Source: U.S. Census Bureau, American Community Survey 5-Year Estimates
Year coverage: 2020–2024
Updated: annual
Version: 1.0.0
Schema hash: 4c1d485587fc

Detail levels available

StateCounty · default

Overview

Labor-force status of the population 16 years and over by nativity and citizenship from the American Community Survey 5-year estimates (subject table S0501, Selected Characteristics of the Native and Foreign-Born Populations - the EMPLOYMENT STATUS rows), for Georgia and the 20 to 24 counties the Census publishes it for, vintages 2020-2024: the population 16+ (a count) and its labor-force participation (the headline metric), civilian labor force, employed, unemployed, Armed Forces and not-in-labor-force shares plus the unemployment rate (a share of the civilian labor force), for the total, native, foreign-born, naturalized-citizen and noncitizen populations, each with its 90 percent margin of error.

Row grain: One row per year, county_fips, district_code, tract_geoid, citizenship_status.

Key metric

labor_force_participation_rate — Labor Force Participation Rate (proportion)

The single headline value most answers want.

JSON schema →Data contract (YAML) →

Variables

Every column in the fact table. The code is the exact field name the API returns.

Column	Type	Unit	Range	Null?	Description
`year`Year	integer	—	—	no	ACS 5-year vintage END year: 2024 covers the pooled 2020-2024 survey period. Consecutive vintages overlap. Full description▾ ACS 5-year vintage END year: 2024 covers the pooled 2020-2024 survey period. Consecutive vintages overlap.
`county_fips`County FIPS	string	—	—	yes	5-digit county FIPS code (state 13 + county). Populated only on county-level rows; NULL on the state row. Only the 20 to 24 counties the Census publishes S0501 for appear (a foreign-born population threshold). Full description▾ 5-digit county FIPS code (state 13 + county). Populated only on county-level rows; NULL on the state row. Only the 20 to 24 counties the Census publishes S0501 for appear (a foreign-born population threshold). Joins counties; adds its label columns.
`district_code`District Code	string	—	—	yes	Always NULL: this topic collects state and county geography only. The Census publishes S0501 for just 27 of Georgia's 182 unified school districts (2024 vintage), so the district level was not collected and no district rows are served. Kept for the census domain's standard key shape. Full description▾ Always NULL: this topic collects state and county geography only. The Census publishes S0501 for just 27 of Georgia's 182 unified school districts (2024 vintage), so the district level was not collected and no district rows are served. Kept for the census domain's standard key shape. Joins districts; adds its label columns.
`tract_geoid`Tract GEOID	string	—	—	yes	Always NULL: S0501 is NULL at every census tract, so no tract rows are served. Kept for the census domain's standard key shape. Full description▾ Always NULL: S0501 is NULL at every census tract, so no tract rows are served. Kept for the census domain's standard key shape. Joins tracts; adds its label columns.
`citizenship_status`Citizenship Status	string	—	—	no	Native vs foreign born, and the foreign born by citizenship; a hierarchy, never summed. Full description▾ Nativity and citizenship status. Hierarchical, not a partition: all = native + foreign_born, and foreign_born = naturalized + noncitizen, so the five values must never be summed. 'all' is the total row. The ACS asks citizenship, not legal status: noncitizen covers lawful permanent residents, temporary visa holders, and unauthorized migrants alike. In this topic the universe is the population 16 years and over (S0501 columns C01-C05, EMPLOYMENT STATUS rows). 5 allowed values▾ `all — total / aggregate` `native` `foreign_born` `naturalized` `noncitizen`
`num_population_16_plus`Number Population 16 Plus	integer	count	—	yes	Estimated people 16 and over in the citizenship category - the base every share is a percent of. Full description▾ ACS 5-year estimate of the population 16 years and over in the citizenship_status category (S0501 row 'Population 16 years and over'), a count of persons. The denominator of labor_force_participation_rate and of every other share except unemployment_rate. The count the shares were computed from is unrounded; the published shares are rounded, so shares times this count are approximate.
`num_population_16_plus_moe`Number Population 16 Plus Moe	integer	count	—	yes	90 percent margin of error for num_population_16_plus, as published (integer persons). Never the headline metric. Full description▾ 90 percent margin of error for num_population_16_plus, as published (integer persons). Never the headline metric.
`labor_force_participation_rate`Labor Force Participation Rate	number	proportion	—	yes	Share of people 16+ who are working or looking for work (civilian labor force plus Armed Forces). Full description▾ Labor-force participation: the share of the population 16 and over that is in the labor force - employed, unemployed and looking, or in the Armed Forces (S0501 row 'In labor force'). Equals pct_civilian_labor_force + pct_armed_forces and 1 - pct_not_in_labor_force, within rounding. Published as a one-decimal percent of the population 16 and over and served as a proportion (divided by 100). Do not multiply by num_population_16_plus to rebuild a headcount - the rounding makes such counts false precision. The numerator count is not published, so only the denominator is served.
`labor_force_participation_rate_moe`Labor Force Participation Rate Moe	number	proportion	—	yes	90 percent margin of error for labor_force_participation_rate, in the same unit as the estimate (a proportion: published percentage points divided by 100). Never the headline metric. Full description▾ 90 percent margin of error for labor_force_participation_rate, in the same unit as the estimate (a proportion: published percentage points divided by 100). Never the headline metric.
`pct_civilian_labor_force`Percent Civilian Labor Force	number	proportion	—	yes	Share of people 16+ in the civilian labor force (employed plus unemployed, excluding Armed Forces). Full description▾ Share of the population 16 and over in the civilian labor force - employed or unemployed, excluding the Armed Forces (S0501 row 'Civilian labor force'). Equals pct_employed + pct_unemployed within rounding, and is the base of unemployment_rate. Published as a one-decimal percent of the population 16 and over and served as a proportion (divided by 100). Do not multiply by num_population_16_plus to rebuild a headcount - the rounding makes such counts false precision.
`pct_civilian_labor_force_moe`Percent Civilian Labor Force Moe	number	proportion	—	yes	90 percent margin of error for pct_civilian_labor_force, in the same unit as the estimate (a proportion: published percentage points divided by 100). Never the headline metric. Full description▾ 90 percent margin of error for pct_civilian_labor_force, in the same unit as the estimate (a proportion: published percentage points divided by 100). Never the headline metric.
`pct_employed`Percent Employed	number	proportion	—	yes	Share of people 16+ who are employed (the employment-to-population ratio). Full description▾ Share of the population 16 and over that is employed in the civilian labor force (S0501 row 'Employed') - the employment-to-population ratio, not the share of the labor force that has a job. Published as a one-decimal percent of the population 16 and over and served as a proportion (divided by 100). Do not multiply by num_population_16_plus to rebuild a headcount - the rounding makes such counts false precision.
`pct_employed_moe`Percent Employed Moe	number	proportion	—	yes	90 percent margin of error for pct_employed, in the same unit as the estimate (a proportion: published percentage points divided by 100). Never the headline metric. Full description▾ 90 percent margin of error for pct_employed, in the same unit as the estimate (a proportion: published percentage points divided by 100). Never the headline metric.
`pct_unemployed`Percent Unemployed	number	proportion	—	yes	Share of ALL people 16+ who are unemployed - smaller than the unemployment rate, which is a share of the labor force. Full description▾ Share of the population 16 and over that is unemployed - without a job, available, and actively looking (S0501 row 'Unemployed') - as a share of everyone 16+, NOT of the labor force. For the conventional unemployment rate use unemployment_rate, which divides by the civilian labor force instead. Published as a one-decimal percent of the population 16 and over and served as a proportion (divided by 100). Do not multiply by num_population_16_plus to rebuild a headcount - the rounding makes such counts false precision.
`pct_unemployed_moe`Percent Unemployed Moe	number	proportion	—	yes	90 percent margin of error for pct_unemployed, in the same unit as the estimate (a proportion: published percentage points divided by 100). Never the headline metric. Full description▾ 90 percent margin of error for pct_unemployed, in the same unit as the estimate (a proportion: published percentage points divided by 100). Never the headline metric.
`unemployment_rate`Unemployment Rate	number	proportion	—	yes	Unemployed as a share of the civilian labor force - the conventional unemployment rate. Full description▾ Unemployment rate: the unemployed as a proportion of the CIVILIAN LABOR FORCE, not of the population 16+ (S0501 row 'Unemployed - Percent of civilian labor force'). Served as published (one-decimal percent divided by 100), never recomputed from the rounded shares; it reproduces pct_unemployed / pct_civilian_labor_force within 0.002. Published zeros are real: a county subgroup with no unemployed respondents in the sample reports 0.0.
`unemployment_rate_moe`Unemployment Rate Moe	number	proportion	—	yes	90 percent margin of error for unemployment_rate, in the same unit as the estimate (a proportion: published percentage points divided by 100). Never the headline metric. Full description▾ 90 percent margin of error for unemployment_rate, in the same unit as the estimate (a proportion: published percentage points divided by 100). Never the headline metric.
`pct_armed_forces`Percent Armed Forces	number	proportion	—	yes	Share of people 16+ serving in the Armed Forces. Full description▾ Share of the population 16 and over in the Armed Forces (S0501 row 'Armed Forces'), the non-civilian part of the labor force. Published zeros are real (no Armed Forces respondents in the sample). Published as a one-decimal percent of the population 16 and over and served as a proportion (divided by 100). Do not multiply by num_population_16_plus to rebuild a headcount - the rounding makes such counts false precision.
`pct_armed_forces_moe`Percent Armed Forces Moe	number	proportion	—	yes	90 percent margin of error for pct_armed_forces, in the same unit as the estimate (a proportion: published percentage points divided by 100). Never the headline metric. Full description▾ 90 percent margin of error for pct_armed_forces, in the same unit as the estimate (a proportion: published percentage points divided by 100). Never the headline metric.
`pct_not_in_labor_force`Percent Not in Labor Force	number	proportion	—	yes	Share of people 16+ neither working nor looking for work (students, retirees, caregivers, others). Full description▾ Share of the population 16 and over not in the labor force - neither employed, unemployed and looking, nor in the Armed Forces: students, retirees, caregivers, the disabled, and discouraged workers (S0501 row 'Not in labor force'). Equals 1 - labor_force_participation_rate within rounding. Published as a one-decimal percent of the population 16 and over and served as a proportion (divided by 100). Do not multiply by num_population_16_plus to rebuild a headcount - the rounding makes such counts false precision.
`pct_not_in_labor_force_moe`Percent Not in Labor Force Moe	number	proportion	—	yes	90 percent margin of error for pct_not_in_labor_force, in the same unit as the estimate (a proportion: published percentage points divided by 100). Never the headline metric. Full description▾ 90 percent margin of error for pct_not_in_labor_force, in the same unit as the estimate (a proportion: published percentage points divided by 100). Never the headline metric.

Filters

Query parameters the fact endpoint accepts. Comma-separated values are OR within a parameter; multiple parameters AND together.

Parameter	Kind	Allowed values	Notes
`year`	year_exact	any value	—
`year_min`	year_range	any value	—
`year_max`	year_range	any value	—
`detail`	detail	`countiesstates`	enum-enforced, default: counties
`district_code`	foreign_key	any value	multi-value
`county_fips`	foreign_key	any value	multi-value
`tract_geoid`	foreign_key	any value	multi-value
`citizenship_status`	categorical	`allnativeforeign_bornnaturalizednoncitizen`	multi-value, enum-enforced
`district_type`	dimension_attribute	7 allowed values▾ `commission_charter` `resa` `standard` `state_agency` `state_charter` `state_school` `state_special`	multi-value, enum-enforced

Example requests

Run these against the base URL — they return live data.

All rows (first page), counties level

curl "https://georgiacivicdata.org/api/v1/census/labor_force_by_nativity"

counties data for 2024

curl "https://georgiacivicdata.org/api/v1/census/labor_force_by_nativity?year=2024"

Filtered to citizenship_status = native for 2024

curl "https://georgiacivicdata.org/api/v1/census/labor_force_by_nativity?year=2024&citizenship_status=native"

One county (FIPS 13135), 2024

curl "https://georgiacivicdata.org/api/v1/census/labor_force_by_nativity?county_fips=13135&year=2024&detail=counties"

Download 2024 as CSV

curl "https://georgiacivicdata.org/api/v1/census/labor_force_by_nativity?year=2024&format=csv"

Notes & limitations

NULL handling

Zero is a real, reported value.

Limitations

County coverage is PARTIAL: the Census publishes S0501 for only 20 to 24 of Georgia's 159 counties per vintage (22 in 2020, 20 in 2021, 23 in 2022, 24 in 2023, 24 in 2024) - the counties above a FOREIGN-BORN population threshold, not a total-population cut (2024 vintage: Bibb County, roughly 157,000 people, is unpublished; Barrow, roughly 90,000, is published) - and the published set shifts by vintage as counties cross it. Unpublished counties are absent from this table (not NULL, not zero, not imputed), so summing county rows never reproduces the state; the state row is always published; no school-district or tract geography is served at all. Statewide figures are complete; county figures cover metro Atlanta and the larger immigrant-receiving counties only. citizenship_status is a hierarchy, not a partition: all = native + foreign_born and foreign_born = naturalized + noncitizen, so never sum across it; the ACS asks citizenship, not legal status, so noncitizen covers lawful permanent residents, temporary visa holders, humanitarian migrants, and unauthorized migrants alike. num_population_16_plus is a count of persons; every other metric is a share published to one decimal percent and served as a proportion (three decimals). Do not multiply a share by the count to rebuild a headcount - the rounding makes such counts and their margins false precision - and note that unemployment_rate is a share of the CIVILIAN LABOR FORCE while pct_unemployed is a share of everyone 16 and over. ACS 5-year period estimates: the year column is the vintage END year and each estimate pools five years of survey responses (2024 = 2020-2024). Consecutive vintages share about 80% of their sample, so the series is heavily smoothed - never difference overlapping vintages as if they were annual change. Estimates are survey-based and carry 90% margins of error (the *_moe columns, in the same unit as their estimate); county margins on the citizenship subgroups reach 10 to 12 percentage points. State and county rows serve vintages 2020-2024 only: the state row has NULL county_fips, county rows carry county_fips, and district_code and tract_geoid are NULL on every row.