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Indicator Gauge Icon Legend

Legend Colors

Red is bad, green is good, blue is not statistically different/neutral.

Compared to Distribution

an indicator guage with the arrow in the green the value is in the best half of communities.

an indicator guage with the arrow in the yellow the value is in the 2nd worst quarter of communities.

an indicator guage with the arrow in the red the value is in the worst quarter of communities.

Compared to Target

green circle with white tick inside it meets target; red circle with white cross inside it does not meet target.

Compared to a Single Value

green diamond with downward arrow inside it lower than the comparison value; red diamond with downward arrow inside it higher than the comparison value; blue diamond with downward arrow inside it not statistically different from comparison value.

Trend

green square outline with upward trending arrow inside it green square outline with downward trending arrow inside it non-significant change over time; green square with upward trending arrow inside it green square with downward trending arrow inside it significant change over time; blue square with equals sign no change over time.

Compared to Prior Value

green triangle with upward trending arrow inside it higher than the previous measurement period; green triangle with downward trending arrow inside it lower than the previous measurement period; blue equals sign no statistically different change  from previous measurement period.

green chart bars Significantly better than the overall value

red chart bars Significantly worse than the overall value

light blue chart bars No significant difference with the overall value

gray chart bars No data on significance available

More information about the gauges and icons

Gender Pay Gap

County: Kings
Measurement Period: 2018-2022

This indicator shows the ratio between the median earnings of women in cents to every dollar of the median earnings of men, or cents on the dollar.

Why is this important?

The Equal Pay Act of 1963 requires that men and women in the same workplace be given equal pay for work. Yet, women, on average, have been paid less than men, making around 84 cents for every dollar paid to men. Differences in the industries and occupations where men and women work are the single largest measurable cause of women's lower wages. However, about 70% of the wage gap cannot be explained by differences in worker characteristics and may be due to discrimination (U.S. Department of Labor).

Considerations for Equitable Approaches: Pay differs substantially by gender, race, and ethnicity. For instance, women who identify as Black and Hispanic women (of any race) experience a larger pay gap compared to non-Hispanic White women. Efforts to close the gender and racial wage gap should address the leading contributors to differences in pay. Solutions must address occupational and industry segregation, while at the same time addressing discrimination and other factors not easily captured in statistical models (U.S. Department of Labor). 

More...
$0.70
cents on the dollar
Source: American Community Survey 5-Year
Measurement period: 2018-2022
Maintained by: Conduent Healthy Communities Institute
Last update: February 2024
Compared to See the Legend
Technical note: The U.S. Census Bureau calculates 90% confidence intervals for American Community Survey estimates. Use caution when interpreting values with wide confidence intervals. Confidence intervals that are farther away from estimates in either direction indicate uncertainty due to small survey sample sizes. The U.S. Census Bureau does not recommend comparing overlapping 5-year periods since much of the data in each estimate are the same. Use caution when comparing estimates for census tracts over time as these geographies are redefined with each decennial census according to population changes.
More details:
Data for this indicator can be found in tables B20017 (overall values) and B20017B-I (race/ethnicity breakout values) on data.census.gov.
 
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Data Source

Filed under: Economy / Income, Economy / Employment, Social Determinants of Health, Women