Textile machine setters, operators, and tenders

Detailed Occupation

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2020 Workforce
23.7k
Average Age
44.4
Average Salary
$30,211
Average Male Salary
$33,451
Average Female Salary
$27,150

About

Textile machine setters, operators, and tenders are most often employed by the Fabric mills, except knitting mills industry. The average yearly wage for Textile machine setters, operators, and tenders was $30,211 in 2020.

The locations that employ the most Textile machine setters, operators, and tenders are Whitfield County PUMA, GA, Northwest Georgia Regional Commission (Northeast) PUMA, GA, and Burke & McDowell Counties PUMA, NC. The locations with a relatively high concentration of Textile machine setters, operators, and tenders are Whitfield County PUMA, GA, Northwest Georgia Regional Commission (Northeast) PUMA, GA, and Burke & McDowell Counties PUMA, NC.

briefcaseEmployment

Employment and salary information for the Textile machine setters, operators, and tenders workforce. Textile machine setters, operators, and tenders workforce in 2020 was 23,668 people, of which 51.4% were women and 48.6% were men. Textile machine setters, operators, and tenders are paid most in Coffee, Covington, Butler & Crenshaw Counties PUMA, AL but are relatively concentrated in Whitfield County PUMA, GA.

Employment Over Time

Metric
Grouping
11,498
Male Workforce
± 2.63k
12,170
Female Workforce
± 2.71k

The Textile machine setters, operators, and tenders workforce in 2020 was 23,668 people (51.4% women and 48.6% men). This implies an average annual growth of −13.8% between 2018 (27,461) and 2020 (23,668).

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Employment by Location

Level
Metric

This map shows the states in the United States shaded by average wage for Textile machine setters, operators, and tenders.

During 2020, the states that concentrated the best average annual wage were Maine ($47,419), South Carolina ($43,464), and Kentucky ($40,971).

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Yearly Wage Ranking

$30,211
AVERAGE WAGE
#448 in the ranking (2020)
$55,954
NATIONAL AVERAGE WAGE
For all occupations across the US

In 2020, Textile machine setters, operators, and tenders earned an average of $30,211, $25,743 less than the average national salary of $55,954

The graph shows the ranking of Textile machine setters, operators, and tenders in relation to all Detailed Occupation in 2020.

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Wage Distribution

Gender
0.288
WAGE GINI

In 2020, Textile machine setters, operators, and tenders had a wage GINI coefficient of 0.288, which is lower than the national average of 0.478. In other words, wages are distributed more evenly for Textile machine setters, operators, and tenders (shown in red) than for the overall labor force (shown in gray).

The graphic shows the distribution of average salaries by buckets for Textile machine setters, operators, and tenders compared to the entire workforce in the country.

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rigIndustry

Information on the industries that employ Textile machine setters, operators, and tenders and on wages for those in the field. Fabric mills, except knitting mills is the industry that employs the most Textile machine setters, operators, and tenders, both by share and by number, though the highest paid industry for Textile machine setters, operators, and tenders, by average wage, is Furniture & home furnishings stores ($335,746).

Occupations by Industries

Metric
Value
23.7k
2020 Workforce
± 3,777
−10.3%
1 YEAR GROWTH
± 24.5%

This graphic shows the share of Textile machine setters, operators, and tenders employed by various industries. Fabric mills, except knitting mills employs the largest share of Textile machine setters, operators, and tenders at 46.4%, followed by Carpet & rug mills with 39.5% and Fiber, yarn, & thread mills with 14.1%.

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geosearchDiversity

Demographic information on Textile machine setters, operators, and tenders in the US. The workforce of Textile machine setters, operators, and tenders in 2020 was 23,668 people, with 51.4% woman, and 48.6% men. The average age of male Textile machine setters, operators, and tenders in the workforce is 43.4 and of female Textile machine setters, operators, and tenders is 45.3, and the most common race/ethnicity for Textile machine setters, operators, and tenders is White.

Gender and Age

Metric

The workforce of Textile machine setters, operators, and tenders in 2020 was 23,668 people, with 51.4% woman, and 48.6% men.

The age ranges that concentrated the largest workforce were 55 to 59 years (2,968 people), 50 to 54 years (2,964  people), and 35 to 39 years (2,681 people). Among them they concentrated 36.9% of the total workforce.

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Ethnicity

Gender

In 2020, 32% of Textile machine setters, operators, and tenders workers were Hispanic and 68% non-Hispanic.

The treemap shows the distribution of Hispanic workers according to their origin, highlighting Mexican (81.2%), Guatemalan (11.2)%, and Salvadoran (7.61)%

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Races

In 2020, 63.7% of the Textile machine setters, operators, and tenders workforce were White, of which 53.5% were women and 46.5% men. Other races that concentrated a significant number of workers were Black (18.7%) and Other (10.2%).

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learningEducation & Skills

Data on higher education choices for Textile machine setters, operators, and tenders from The Department of Education and Census Bureau. The most common major for Textile machine setters, operators, and tenders is Business but the most specialized major according to RCA in 2020 were Natural Resources & Conservation.

Majors

ACS PUMS data only shows the major for bachelor's degrees. However, we can filter the data based on highest degree obtained.
Type of Majors
Degree

The most common majors achieved by Textile machine setters, operators, and tenders in 2020 (counting all academic degrees) were Business (250 people), Education (153 people), and Visual & Performing Arts (142 people).

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Education Levels

Metric

The main educational levels achieved by the Textile machine setters, operators, and tenders workers were High School or Equivalent (10,735 people), Secondary Education (4,310 people), and Some college (3,671 people).

The graphic shows the Textile machine setters, operators, and tenders workforce by gender and educational level.

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