text:
Franklin County, Iowa

Franklin County is a county located in the U.S. state of Iowa. As of the 2020 census, the population was 10,019. The county seat is Hampton. The county was formed on January 15, 1851 and named after Benjamin Franklin.

Geography
According to the U.S. Census Bureau, the county has a total area of 583 sqmi, of which 582 sqmi is land and 0.6 sqmi (0.09%) is water.

Major highways

 * I-35.svg Interstate 35
 * US 65.svg U.S. Highway 65
 * Circle sign 3.svg Iowa Highway 3
 * Elongated circle 57.svg Iowa Highway 57

Transit

 * List of intercity bus stops in Iowa

Adjacent counties

 * Cerro Gordo County (north)
 * Butler County (east)
 * Hardin County (south)
 * Wright County (west)
 * Grundy County (southeast)

2020 census
The 2020 census recorded a population of 10,019 in the county, with a population density of. 92.62% of the population reported being of one race. There were 4,656 housing units of which 4,141 were occupied.

2010 census
The 2010 census recorded a population of 10,680 in the county, with a population density of. There were 4,894 housing units, of which 4,332 were occupied.

2000 census
As of the census of 2000, there were 10,704 people, 4,356 households, and 2,983 families residing in the county. The population density was 18 /mi2. There were 4,763 housing units at an average density of 8 /mi2. The racial makeup of the county was 94.92% White, 0.08% Black or African American, 0.23% Native American, 0.16% Asian, 0.02% Pacific Islander, 4.05% from other races, and 0.53% from two or more races. 6.00% of the population were Hispanic or Latino of any race.

There were 4,356 households, out of which 29.30% had children under the age of 18 living with them, 58.90% were married couples living together, 6.40% had a female householder with no husband present, and 31.50% were non-families. 27.60% of all households were made up of individuals, and 15.40% had someone living alone who was 65 years of age or older. The average household size was 2.41 and the average family size was 2.93.

In the county, the population was spread out, with 24.20% under the age of 18, 7.30% from 18 to 24, 24.00% from 25 to 44, 23.90% from 45 to 64, and 20.50% who were 65 years of age or older. The median age was 41 years. For every 100 females there were 96.40 males. For every 100 females age 18 and over, there were 93.90 males.

The median income for a household in the county was $36,042, and the median income for a family was $45,184. Males had a median income of $29,694 versus $21,115 for females. The per capita income for the county was $18,767. About 5.70% of families and 8.00% of the population were below the poverty line, including 9.70% of those under age 18 and 7.10% of those age 65 or over.

Franklin County Fair
Franklin County is home to the Franklin County Fair. Held annually for five days in mid-July, the Franklin County Fair is held on the fairgrounds located on the west side of Hampton. Traditionally, grandstand entertainment begins on Wednesday with the Barnes PRCA Rodeo. Thursday, Friday, and Saturday are usually concerts featuring nationally known entertainment. In 2007 such names as Terri Clark, Marshall Tucker Band, and Trent Tomlinson & Danielle Peck brought fans to the grandstand. On Sunday the Figure 8 Races generally fill the grandstand. The fair also includes free entertainment and a carnival midway. The fairgrounds features the Franklin County Historical Museum, Pleasant Hill (turn of the century village with stores, crafters, old west shows, music and entertainment), and Grandpa's Farm (all phases of farming demonstrated with vintage implements powered by draft horses, steam engines and antique tractors).

Education
There are four high schools in Franklin County. The Hampton-Dumont Community School District is a P/K-12 school system located in Hampton and serving the communities of Hampton, Dumont, Aredale, and Hansell. Hampton-Dumont has a K-12 enrollment of 1,194. The West Fork Community Schools are made up of a whole grade sharing agreement between SCMT and Rockwell-Swaledale. West Fork serves the communities of Sheffield, Chapin, Meservey, Thornton, Rockwell, and Swaledale and has a combined enrollment of 764 between the two districts. The AGWSR Community School District serves the communities of Ackley, Geneva, Wellsburg, and Steamboat Rock and has a K-12 enrollment of 654 students. The CAL Community School District, located just south of Latimer, serves the communities of Coulter, Alexander, and Latimer and has a K-12 enrollment of 274 students.

Cities

 * Ackley
 * Alexander
 * Coulter
 * Dows
 * Geneva
 * Hampton
 * Hansell
 * Latimer
 * Popejoy
 * Sheffield

Census-designated places

 * Bradford
 * Chapin

Townships
Franklin County is divided into sixteen townships:

 * Geneva
 * Grant
 * Hamilton
 * Ingham
 * Lee
 * Marion
 * Morgan
 * Mott
 * Oakland
 * Osceola
 * Reeve
 * Richland
 * Ross
 * Scott
 * West Fork
 * Wisner

Population ranking
The population ranking of the following table is based on the 2020 census of Franklin County.

† county seat

title: Franklin County, Iowa


text:
Floyd County, Iowa

Floyd County is a county located in the U.S. state of Iowa. As of the 2020 census, the population was 15,627. The county seat is Charles City.

History
Floyd County was established in 1854 and was named for Sergeant Charles Floyd of the Lewis and Clark Expedition, who died in 1804 near what is now Sioux City, Iowa, and who was the only member to die on the Expedition.

The first school in the county was taught at Nora Springs in 1854. The second was opened at Charles City, the third at Floyd. Twelve years later there were 54 schools in the county, in September 1875, there were 100 school-houses in Floyd County.

Geography
According to the U.S. Census Bureau, the county has a total area of 501 sqmi, of which 501 sqmi is land and 0.8 sqmi (0.1%) is water.

Major highways

 * US 18.svg U.S. Highway 18
 * US 218.svg U.S. Highway 218
 * Elongated circle 14.svg Iowa Highway 14
 * Elongated circle 27.svg Iowa Highway 27

Adjacent counties

 * Mitchell County (north)
 * Chickasaw County (east)
 * Butler County (south)
 * Cerro Gordo County (west)
 * Howard County (northeast)
 * Bremer County (southeast)
 * Franklin County (southwest)

2020 census
The 2020 census recorded a population of 15,627 in the county, with a population density of. 96.21% of the population reported being of one race. There were 7,314 housing units of which 6,674 were occupied.

2010 census
The 2010 census recorded a population of 16,303 in the county, with a population density of. There were 7,526 housing units, of which 6,886 were occupied.

2000 census
As of the census of 2000, there were 16,900 people, 6,828 households, and 4,711 families residing in the county. The population density was 34 /mi2. There were 7,317 housing units at an average density of 15 /mi2. The racial makeup of the county was 98.11% White, 0.23% Black or African American, 0.09% Native American, 0.43% Asian, 0.09% Pacific Islander, 0.44% from other races, and 0.60% from two or more races. 1.31% of the population were Hispanic or Latino of any race.

There were 6,828 households, out of which 30.50% had children under the age of 18 living with them, 57.70% were married couples living together, 7.70% had a female householder with no husband present, and 31.00% were non-families. 28.00% of all households were made up of individuals, and 14.60% had someone living alone who was 65 years of age or older. The average household size was 2.40 and the average family size was 2.92.

In the county, the population was spread out, with 25.10% under the age of 18, 7.00% from 18 to 24, 24.40% from 25 to 44, 24.20% from 45 to 64, and 19.20% who were 65 years of age or older. The median age was 40 years. For every 100 females there were 93.50 males. For every 100 females age 18 and over, there were 90.40 males.

The median income for a household in the county was $35,237, and the median income for a family was $41,133. Males had a median income of $30,285 versus $20,867 for females. The per capita income for the county was $17,091. About 6.50% of families and 9.30% of the population were below the poverty line, including 13.00% of those under age 18 and 5.70% of those age 65 or over.

Cities

 * Charles City
 * Colwell
 * Floyd
 * Marble Rock
 * Nora Springs
 * Rockford
 * Rudd

Unincorporated communities

 * Midway
 * Powersville
 * Roseville (a census-designated place)

Townships
Floyd County is divided into twelve townships:

 * Cedar
 * Floyd
 * Niles
 * Pleasant Grove
 * Riverton
 * Rock Grove
 * Rockford
 * Rudd
 * Saint Charles
 * Scott
 * Ulster
 * Union

Population ranking
The population ranking of the following table is based on the 2020 census of Floyd County.

† county seat

Politics
Prior to 1988, Floyd County was strongly Republican in presidential elections. In only four elections from 1896 to 1984 did a Republican presidential candidate fail to win the county. Starting with the 1988 election, the county consistently backed Democratic Party presidential candidates up until the 2016 election. In that presidential election, the county swung 29.5 points Republican with Donald Trump winning the county by over 14 points after Barack Obama won the county by a similar margin 4 years earlier.

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/

title: Floyd County, Iowa


text:
Fayette County, Iowa

Fayette County is a county located in the U.S. state of Iowa. As of the 2020 census, the population was 19,509. The county seat is West Union.

History
Fayette County was founded on December 21, 1837, as a part of Wisconsin Territory. It was named after Gilbert du Motier, marquis de La Fayette, a French general and politician, who came to America in 1777 to fight in the Revolutionary War, and who was named Major General of the Continental Army. The county was formed as part of a large reorganization of Dubuque County, which at that time comprised most of the northern half of Iowa, Minnesota, and parts of the Dakotas. Fayette County was granted the Minnesota and Dakotas territory on that date. It became part of Iowa Territory when it was formed on July 4, 1838. Fayette County's size was drastically reduced into land that was part of the modern state of Iowa in 1843, then further split in 1847 after Iowa had achieved statehood. The county was organized in 1850.

Geography
According to the U.S. Census Bureau, the county has a total area of 731 sqmi, of which 731 sqmi is land and 0.5 sqmi (0.07%) is water.

Major highways

 * US 18.svg U.S. Highway 18
 * Circle sign 3.svg Iowa Highway 3
 * Elongated circle 56.svg Iowa Highway 56
 * Elongated circle 93.svg Iowa Highway 93
 * Elongated circle 150.svg Iowa Highway 150
 * Elongated circle 187.svg Iowa Highway 187
 * Elongated circle 281.svg Iowa Highway 281

Adjacent counties

 * Allamakee County (northeast)
 * Black Hawk County (southwest)
 * Buchanan County (south)
 * Bremer County (west)
 * Chickasaw County (northwest)
 * Clayton County (east)
 * Delaware County (southeast)
 * Winneshiek County (north)

2020 census
The 2020 census recorded a population of 19,509 in the county, with a population density of. 96.09% of the population reported being of one race. There were 9,298 housing units of which 8,174 were occupied.

2010 census
The 2010 census recorded a population of 20,880 in the county, with a population density of. There were 9,558 housing units, of which 8,634 were occupied.

2000 census
As of the census of 2000, there were 22,008 people, 8,778 households, and 5,951 families residing in the county. The population density was 30 /mi2. There were 9,505 housing units at an average density of 13 /mi2. The racial makeup of the county was 97.71% White, 0.53% Black or African American, 0.13% Native American, 0.40% Asian, 0.03% Pacific Islander, 0.43% from other races, and 0.77% from two or more races. 1.50% of the population were Hispanic or Latino of any race.

There were 8,778 households, out of which 30.40% had children under the age of 18 living with them, 56.80% were married couples living together, 7.40% had a female householder with no husband present, and 32.20% were non-families. 28.20% of all households were made up of individuals, and 15.00% had someone living alone who was 65 years of age or older. The average household size was 2.41 and the average family size was 2.96.

In the county, the population was spread out, with 25.00% under the age of 18, 8.60% from 18 to 24, 24.90% from 25 to 44, 22.40% from 45 to 64, and 19.00% who were 65 years of age or older. The median age was 39 years. For every 100 females there were 97.50 males. For every 100 females age 18 and over, there were 95.10 males.

The median income for a household in the county was $32,453, and the median income for a family was $39,960. Males had a median income of $27,493 versus $20,099 for females. The per capita income for the county was $17,271. About 8.20% of families and 10.80% of the population were below the poverty line, including 12.30% of those under age 18 and 12.00% of those age 65 or over.

Cities

 * Arlington
 * Clermont
 * Elgin
 * Fayette
 * Fairbank
 * Hawkeye
 * Maynard
 * Oelwein
 * Randalia
 * St. Lucas
 * Stanley
 * Wadena
 * Waucoma
 * West Union
 * Westgate

Unincorporated communities

 * Alpha
 * Donnan
 * Oran
 * Richfield

Townships
Fayette County is divided into twenty townships:

 * Auburn
 * Banks
 * Bethel
 * Center
 * Clermont
 * Dover
 * Eden
 * Fairfield
 * Fremont
 * Harlan
 * Illyria
 * Jefferson
 * Oran
 * Pleasant Valley
 * Putnam
 * Scott
 * Smithfield
 * Union
 * Westfield
 * Windsor

Population ranking
The population ranking of the following table is based on the 2020 census of Fayette County.

† county seat

title: Fayette County, Iowa


text:
Emmet County, Iowa

Emmet County is a county located in the U.S. state of Iowa. As of the 2020 census, the population was 9,388. The county seat is Estherville.

History
Emmet County was created by authority of the Iowa Legislature in 1851. There were finally enough settlers in the area to organize the county in 1859. The county was named for the Irish patriot Robert Emmet, who was hanged as a traitor to the British government at the age of 25.

Geography
According to the U.S. Census Bureau, the county has a total area of 403 sqmi, of which 396 sqmi is land and 6.6 sqmi (1.4=6%) is water. It is the second-smallest county by land area in Iowa, and the fourth-smallest by total area.

Major highways

 * Circle sign 4.svg Iowa Highway 4
 * Circle sign 9.svg Iowa Highway 9
 * Elongated circle 15.svg Iowa Highway 15

Adjacent counties

 * Jackson County, Minnesota (northwest)
 * Martin County, Minnesota (northeast)
 * Kossuth County (east)
 * Palo Alto County (south)
 * Dickinson County (west)

2020 census
The 2020 census recorded a population of 9,388 in the county, with a population density of. 94.84% of the population reported being of one race. There were 4,475 housing units of which 3,972 were occupied.

2010 census
The 2010 census recorded a population of 10,302 in the county, with a population density of. There were 4,758 housing units, of which 4,236 were occupied.

2000 census
As of the census of 2000, there were 11,027 people, 4,450 households, and 2,910 families residing in the county. The population density was 28 /mi2. There were 4,889 housing units at an average density of 12 /mi2. The racial makeup of the county was 97.38% White, 0.24% Black or African American, 0.28% Native American, 0.30% Asian, 0.01% Pacific Islander, 1.25% from other races, and 0.54% from two or more races. 4.31% of the population were Hispanic or Latino of any race.

There were 4,450 households, out of which 27.90% had children under the age of 18 living with them, 55.00% were married couples living together, 7.80% had a female householder with no husband present, and 34.60% were non-families. 30.30% of all households were made up of individuals, and 15.30% had someone living alone who was 65 years of age or older. The average household size was 2.36 and the average family size was 2.93.

In the county, the population was spread out, with 24.20% under the age of 18, 10.10% from 18 to 24, 23.80% from 25 to 44, 22.50% from 45 to 64, and 19.40% who were 65 years of age or older. The median age was 40 years. For every 100 females there were 94.40 males. For every 100 females age 18 and over, there were 93.30 males.

The median income for a household in the county was $33,305, and the median income for a family was $41,296. Males had a median income of $27,495 versus $20,278 for females. The per capita income for the county was $16,619. About 5.20% of families and 8.20% of the population were below the poverty line, including 9.40% of those under age 18 and 9.10% of those age 65 or over.

Cities

 * Armstrong
 * Dolliver
 * Estherville
 * Gruver
 * Ringsted
 * Wallingford

Unincorporated communities

 * Forsyth
 * Gridley
 * Halfa
 * Hoprig
 * Huntington
 * Island Grove
 * Maple Hill
 * Raleigh

Townships
Emmet County is divided into twelve townships:

 * Armstrong Grove
 * Center
 * Denmark
 * Ellsworth
 * Emmet
 * Estherville
 * High Lake
 * Iowa Lake
 * Jack Creek
 * Lincoln
 * Swan Lake
 * Twelve Mile Lake

Population ranking
The population ranking of the following table is based on the 2020 census of Emmet County. † county seat

title: Emmet County, Iowa


text:
Dubuque County, Iowa

Dubuque County is a county located in the U.S. state of Iowa. As of the 2020 census, the population was 99,266, making it the eighth-most populous county in Iowa. The county seat is Dubuque. The county is named for Julien Dubuque, the first European settler of Iowa.

Dubuque County comprises the Dubuque, IA Metropolitan Statistical Area.

Early history
Dubuque County is named for French trader Julien Dubuque, the first European settler of Iowa, and an early lead mining pioneer in what is now Dubuque County. Dubuque was French Canadian, and had (by most accounts) a friendly relationship with the local Fox tribe of Native Americans. He and other early pioneers established a lucrative mining and trading industry in the area. When lead deposits began becoming exhausted, the pioneers developed boat building, lumber yards, milling, brewing, and machinery manufacturing to take its place.

The city of Dubuque was chartered in 1833 as the first city in Iowa. The establishment of the City of Dubuque in 1833 led to large-scale settlement of the surrounding area. This was greatly encouraged by the Roman Catholic Church, which sent priests, bishops, and nuns to establish churches in the unpopulated countryside. Primarily, Irish and German (many of whom were Catholic) immigrants came to the region.

At an extra session of the Sixth Legislative Assembly of Michigan Territory held in September 1834, the Iowa District was divided into two counties by running a line due west from the lower end of Rock Island in the Mississippi River. The territory north of this line (which started just south of the present-day Davenport) was named Dubuque County, and all south of it was Demoine County [sic]. Thus, at that time Dubuque County nominally included not only much of what is now the state of Minnesota but portions of what are now North Dakota and South Dakota.

Dubuque County became part of Wisconsin Territory once it was split off from Michigan Territory on July 3, 1836. A massive reorganization and reduction of the county's size was executed on December 21, 1837, when its original area was separated into 13 named new counties and a "non-county area". The land in present day Minnesota and the Dakotas was transferred to the newly created Fayette County in this action. Dubuque County became a part of Iowa Territory upon its creation on July 4, 1838.

In 1858, Saint Francis Catholic Church was established in Dubuque County.

Middle history
In the 1980s, the farm crisis set in, and devastated large sections of the Midwest, including Dubuque County. Since the area was heavily dependent on agriculture-related industries like Deere and Company and the Dubuque Packing Company, unemployment soared. In one month of 1982, Dubuque County had 23% unemployment, the highest in the nation. The county experienced huge population losses during this time, as workers left the area. It would not fully recover from this until the late 1990s, when the economy diversified, shifting away from manufacturing, and toward various service-related establishments.

Modern history
Since the 1990s, the area has become much more prosperous. Today, the county boasts record employment levels and a growing population. The surging economy can especially be seen in the West Side of the City of Dubuque, and in neighboring Peosta and Asbury. These areas have expanded so much that concerns now lie with trying to manage the growth, a sharp change from just 20 years ago.

It is one of Iowa's two original counties along with Des Moines County; both were organized by the Michigan Territorial legislature in 1834.

In 2021, the Dubuque County Minutemen baseball team advanced to the American Legion World Series semi-finals, the first team from Iowa to advance that far since Cedar Rapids, IA in 1975.

Government
Dubuque County is governed by a three-member Board of Supervisors elected at large. Current supervisors include Ann McDonough, Wayne Kenniker and Harley Pothoff (chairperson). They meet the 1st and 3rd Monday of each month at 9:00 a.m. in the Dubuque County Courthouse.

The current county attorney is Scott Nelson, who succeeded C.J. May in 2023.

The current county auditor is Kevin Dragotto, who succeeded Denise Dolan in 2021.

The current county treasurer is Michael Clasen, who succeeded Eric Steirman in 2022

Law enforcement
The county sheriff's office provides law enforcement services for unincorporated areas of Dubuque County, as well as providing courthouse security, operating the county jail, and performing civil procedures. The Sheriff's Department is located at the Dubuque City/County Law Enforcement Center. The department shares facilities and other resources with the Dubuque Police Department.

Geographic features
The county borders on Illinois and Wisconsin, and is bounded on the northeast by the Mississippi River. According to the U.S. Census Bureau, the county has a total area of 617 sqmi, of which 608 sqmi is land and 8.3 sqmi (1.4%) is water. The county is drained by north and south forks of the Maquoketa River.

The county seat is Dubuque, Iowa, which is located along the Mississippi River in the east-central portion of the county. Eastern Dubuque County is markedly different from the western portion in that its topography is very uneven. The city of Dubuque and surrounding areas adjacent to the Mississippi River have many steep hills, bluffs, and ravines. Also, the eastern portion is more heavily wooded than the west, which is mostly rolling farmland.

Dubuque County is widely known for its impressive bluffs along the Mississippi River, which run along the entire length of the county's riverbanks. These form part of Iowa's Coulee Region, otherwise known as the Driftless Area. During the last ice age, much of the Mississippi Valley near Dubuque County was bypassed by glacial flows, which flattened the surrounding land in eastern Illinois, Wisconsin, and western Iowa, leaving the Driftless Area unusually rugged.

Major parks
The Iowa Department of Natural Resources administers 3 park and preserve areas in the county: The Dubuque County Conservation Board administers 11 park and recreation areas in the county:
 * Little Maquoketa River Mounds State Preserve
 * Mines of Spain State Recreation Area/E. B. Lyons Nature Center
 * White Pine Hollow State Forest

 * Bankston Park
 * Fillmore Recreation Area & Fairways
 * Finley's Landing Park
 * Heritage Trail & Pond
 * Interstate Power Forest Preserve
 * Massey Marina Park
 * Mud Lake Park
 * New Wine Park
 * Pohlman Prairie Preserve
 * Swiss Valley Nature Park & Preserve
 * Whitewater Canyon Park

The City of Dubuque and other towns in the county also operate public park systems of their own. (see Parks in Dubuque, Iowa)

Major highways

 * US 20.svg U.S. Highway 20
 * US 52.svg U.S. Highway 52
 * US 61.svg U.S. Highway 61
 * US 151.svg U.S. Highway 151
 * Circle sign 3.svg Iowa Highway 3
 * Elongated circle 32.svg Iowa Highway 32
 * Elongated circle 136.svg Iowa Highway 136

Transit

 * The Jule
 * List of intercity bus stops in Iowa

Adjacent counties

 * Clayton County (north)
 * Grant County, Wisconsin (northeast)
 * Jo Daviess County, Illinois (east)
 * Jackson County (southeast)
 * Jones County (southwest)
 * Delaware County (west)

National protected areas

 * Driftless Area National Wildlife Refuge (part)
 * Upper Mississippi River National Wildlife and Fish Refuge (part)

2020 census
The 2020 census recorded a population of 99,266 in the county, with a population density of. There were 42,630 housing units of which 39,891 were occupied.

2010 census
The 2010 census recorded a population of 93,653 in the county, with a population density of. There were 38,951 housing units, of which 36,815 were occupied.

2000 census
At the 2000 census, there were 89,143 people, 33,690 households and 23,111 families residing in the county. The population density was 147 /mi2. There were 35,505 housing units at an average density of 58 /mi2. The racial makeup of the county was 97.07% White, 0.86% Black or African American, 0.15% Native American, 0.58% Asian, 0.09% Pacific Islander, 0.50% from other races, and 0.76% from two or more races. 1.19% of the population were Hispanic or Latino of any race.

2005 estimates by the census indicated that Dubuque had a population that identified itself as being 95.5% non-Hispanic white, 1.3% African American, 0.7% Asian and 1.5% Latino.

There were 33,690 households, of which 33.10% had children under the age of 18 living with them, 56.80% were married couples living together, 8.70% had a female householder with no husband present, and 31.40% were non-families. 26.70% of all households were made up of individuals, and 10.80% had someone living alone who was 65 years of age or older. The average household size was 2.51 and the average family size was 3.07.

25.60% of the population were under the age of 18, 10.20% from 18 to 24, 27.20% from 25 to 44, 22.30% from 45 to 64, and 14.70% who were 65 years of age or older. The median age was 36 years. For every 100 females there were 94.40 males. For every 100 females age 18 and over, there were 91.30 males.

The median household income was $39,582 and the median family income was $48,742. Males had a median income of $31,977 versus $22,309 for females. The per capita income for the county was $19,600. About 4.90% of families and 7.80% of the population were below the poverty line, including 7.80% of those under age 18 and 11.00% of those age 65 or over.

Economy
Historically, Dubuque County's economy was driven by heavy industry, including, among others, Deere and Company, and the now-defunct Dubuque Packing Company. However, within the last 20 years, and especially within the last 10 years, the economy has diversified a great deal. Now, alongside manufacturing, which still employs thousands of workers, many county residents work in the tourism/gaming, health care, education, publishing, and financial service sectors.

The county's economy is largely centered around business and industry within the City of Dubuque. With the exception of industrial areas in Cascade, Dyersville, and Peosta, almost all of the rest of the county is rural and agriculturally driven. Some of the key industries in Dubuque County include: Deere and Company, Eagle Window & Door Co., Flexsteel Industries, Mi-T-M Corp., A.Y. McDonald Mfg. Co., Klauer Mfg., Georgia-Pacific, and Swiss Valley Farms, among others. Besides industry, large numbers of people work for the Dubuque Community School District, Mercy Medical Center - Dubuque, Medical Associates, Finley Hospital, Prudential Financial, the City of Dubuque, and Cottingham & Butler.

Growth
Dubuque County has, in recent years, enjoyed job growth, low unemployment, and the rapid expansion of business and commerce. Alongside these positives, the county is beginning to see a growing population, as well. Up from a recent low of 86,403 in 1990, the population is now about 97,000 and growing. This can be seen especially in the West Side of the City of Dubuque, and in nearby Asbury and Peosta. This fact is especially significant, considering that all of the counties surrounding Dubuque County have fewer people now than they did in 1900, with the exception of Grant County, Wisconsin.

Politics
Dubuque County was historically Democratic and supported every Democratic Party Presidential candidate from John F. Kennedy to Barack Obama, with President Obama winning the county by over 20 points in 2008. In 2016, it was narrowly won by Donald Trump, who became the first Republican to win the county since President Eisenhower in 1956. Trump won the county again in 2020, by a larger margin. In the 2022 elections, the county continued to trend rightward, with Republican governor Kim Reynolds winning reelection by a margin of over 16 points. The county additionally voted for Republican Chuck Grassley in U.S. Senate election and for Republican Ashley Hinson in the election for U.S. House of Representatives for Iowa's 1st congressional district.

Education
Tertiary education:

 * Capri Cosmetology College
 * Clarke University
 * Divine Word College
 * Emmaus Bible College
 * Loras College
 * Northeast Iowa Community College
 * University of Dubuque
 * Wartburg Theological Seminary

K-12 school districts include:
 * Dubuque Community School District
 * Maquoketa Community School District
 * Monticello Community School District
 * Western Dubuque Community School District

Religion
, Dubuque County has a large percentage of Catholic residents.

Cities

 * Asbury
 * Balltown
 * Bankston
 * Bernard
 * Cascade
 * Centralia
 * Dubuque
 * Durango
 * Dyersville
 * Epworth
 * Farley
 * Graf
 * Holy Cross
 * Luxemburg
 * New Vienna
 * Peosta
 * Rickardsville
 * Sageville
 * Sherrill
 * Worthington
 * Zwingle

Unincorporated communities

 * Fillmore
 * Key West
 * Washington Mills

Townships
Dubuque County is divided into eighteen townships:

 * Cascade
 * Center
 * Concord
 * Dodge
 * Dubuque
 * Iowa
 * Jefferson
 * Julien
 * Liberty
 * Mosalem
 * New Wine
 * Peru
 * Prairie Creek
 * Table Mound
 * Taylor
 * Vernon
 * Washington
 * Whitewater

title: Dubuque County, Iowa


text:
Dickinson County, Iowa

Dickinson County is a county located in the U.S. state of Iowa. As of the 2020 census, the population was 17,703. The county seat is Spirit Lake. The county was organized in 1857 and is named in honor of Daniel S. Dickinson, a U.S. Senator for New York.

Dickinson County comprises the Spirit Lake, IA Micropolitan Statistical Area.

Geography
According to the U.S. Census Bureau, the county has a total area of 404 sqmi, of which 381 sqmi is land and 23 sqmi (5.8%) is water. It is the smallest county by land area in Iowa, and the fifth-smallest by total area.

A region known as the Iowa Great Lakes is in Dickinson County, making it a popular vacation destination for Iowans, and explaining the recent high population growth in the area. The lakes include West Okoboji Lake, East Okoboji Lake, and Spirit Lake.

Major highways

 * [[Image:US 71.svg|x20px]] U.S. Highway 71
 * [[Image:Circle sign 9.svg|x20px]] Iowa Highway 9
 * [[Image:Elongated circle 86.svg|x20px]] Iowa Highway 86

Adjacent counties

 * Jackson County, Minnesota (north)
 * Emmet County (east)
 * Clay County (south)
 * Osceola County (west)

2020 census
The 2020 census recorded a population of 17,703 in the county, with a population density of. 96.84% of the population reported being of one race. 92.71% were non-Hispanic White, 0.45% were Black, 2.29% were Hispanic, 0.12% were Native American, 0.46% were Asian, 0.01% were Native Hawaiian or Pacific Islander, and 3.96% were some other race or more than one race. There were 13,691 housing units of which 7,976 were occupied.

2010 census
The 2010 census recorded a population of 16,667 in the county, with a population density of. There were 12,849 housing units, of which 7,554 were occupied.

2000 census
As of the census of 2000, there were 16,424 people, 7,103 households, and 4,759 families residing in the county. The population density was 43 PD/sqmi. There were 11,375 housing units at an average density of 30 /mi2. The racial makeup of the county was 98.90% White, 0.18% Black or African American, 0.21% Native American, 0.18% Asian, 0.01% Pacific Islander, 0.10% from other races, and 0.43% from two or more races. 0.66% of the population were Hispanic or Latino of any race.

There were 7,103 households, out of which 26.10% had children under the age of 18 living with them, 57.80% were married couples living together, 6.70% had a female householder with no husband present, and 33.00% were non-families. 28.60% of all households were made up of individuals, and 13.70% had someone living alone who was 65 years of age or older. The average household size was 2.27 and the average family size was 2.78.

In the county, the population was spread out, with 21.90% under the age of 18, 6.60% from 18 to 24, 23.90% from 25 to 44, 26.90% from 45 to 64, and 20.60% who were 65 years of age or older. The median age was 43 years. For every 100 females, there were 95.00 males. For every 100 females age 18 and over, there were 92.30 males.

The median income for a household in the county was $39,020, and the median income for a family was $47,739. Males had a median income of $30,523 versus $22,131 for females. The per capita income for the county was $21,929. 6.00% of the population and 4.20% of families were below the poverty line. Out of the total people living in poverty 5.90% of those under the age of 18 and 7.00% of those 65 and older were living below the poverty line.

Cities

 * Arnolds Park
 * Lake Park
 * Milford
 * Okoboji
 * Orleans
 * Spirit Lake
 * Superior
 * Terril
 * Wahpeton
 * West Okoboji

Unincorporated community

 * Montgomery

Townships
Dickinson County is divided into twelve townships:

 * Center Grove
 * Diamond Lake
 * Excelsior
 * Lakeville
 * Lloyd
 * Milford
 * Okoboji
 * Richland
 * Silver Lake
 * Spirit Lake
 * Superior
 * Westport

Population ranking
The population ranking of the following table is based on the 2020 census of Dickinson County. † county seat

title: Dickinson County, Iowa


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Emotional intelligence

Emotional intelligence (EI) is defined as the ability to perceive, use, understand, manage, and handle emotions. People with high emotional intelligence can recognize their own emotions and those of others, use emotional information to guide thinking and behavior, discern between different feelings and label them appropriately, and adjust emotions to adapt to environments.

Although the term first appeared in 1964, it gained popularity in the 1995 bestselling book Emotional Intelligence by science journalist Daniel Goleman. Goleman defined EI as the array of skills and characteristics that drive leadership performance. Some researchers suggest that emotional intelligence can be learned and strengthened, while others claim it is an inborn characteristic.

Various models have been developed to measure EI. In 1987, Keith Beasley used the term Emotional Quotient (EQ) in an article, named after the Intelligence Quotient (IQ). The trait model, developed by Konstantinos V. Petrides in 2001, focuses on self reporting of behavioral dispositions and perceived abilities. The ability model, (Mayeret al., 2023) focuses on the individual's ability to process emotional information and use it to navigate the social environment. Goleman's original model may now be considered a mixed model that combines what has since been modeled separately as ability EI and trait EI.

Recent research has focused on emotion recognition, which refers to the attribution of emotional states based on observations of visual and auditory nonverbal cues. In addition, neurological studies have sought to characterize the neural mechanisms of emotional intelligence.

Studies show that there is a correlation between people with high EI and positive workplace performance, although no causal relationships have been shown. EI is typically associated with empathy because it involves a person connecting their personal experiences with those of others. Since its popularization in recent decades, methods of developing EI have become sought by people seeking to become more effective leaders.

Criticisms have centered on whether EI is a real intelligence, and whether it has incremental validity over IQ and the Big Five personality traits. However, meta-analyses have found that certain measures of EI have validity even when controlling for IQ and personality.

History
The concept of Emotional Strength was introduced by Abraham Maslow in the 1950s. The term "emotional intelligence" seems first to have appeared in a 1964 paper by Michael Beldoch, and in the 1966 paper by B. Leuner titled Emotional Intelligence and Emancipation which appeared in the psychotherapeutic journal Practice of child psychology and child psychiatry.

In 1983, Howard Gardner's Frames of Mind: The Theory of Multiple Intelligences introduced the idea that traditional types of intelligence, such as IQ, fail to fully explain cognitive ability. He introduced the idea of multiple intelligences which included both interpersonal intelligence (the capacity to understand the intentions, motivations and desires of other people) and intrapersonal intelligence (the capacity to understand oneself, to appreciate one's feelings, fears and motivations).

The first published use of the term "EQ" (Emotional Quotient) is an article by Keith Beasley in 1987 in the British Mensa magazine.

In 1989, Stanley Greenspan put forward a model to describe EI, followed by another by Peter Salovey and John Mayer the following year.

However, the term became widely known with the publication of Goleman's book: Emotional Intelligence – Why it can matter more than IQ (1995). It is to this book's bestselling status that the term can attribute its popularity. Goleman followed up with several similar publications that reinforce use of the term.

Late in 1998, Goleman's Harvard Business Review article entitled "What Makes a Leader?" caught the attention of senior management at Johnson & Johnson's Consumer Companies (JJCC). The article spoke to the importance of Emotional Intelligence (EI) in leadership success, and cited several studies that demonstrated that EI is often the distinguishing factor between great leaders and average leaders. JJCC funded a study which concluded that there was a strong relationship between superior performing leaders and emotional competence, supporting theorists' suggestions that the social, emotional, and relational competency set referred to as Emotional Intelligence is a distinguishing factor in leadership performance.

Tests measuring EI have not replaced IQ tests as a standard metric of intelligence, and Emotional Intelligence has received criticism regarding its role in leadership and business success.

Definitions
Emotional intelligence has been defined, by Peter Salovey and John Mayer, as "the ability to monitor one's own and other people's emotions, to discriminate between different emotions and label them appropriately, and to use emotional information to guide thinking and behavior". This definition was later broken down and refined into four proposed abilities: perceiving, using, understanding, and managing emotions. These abilities are distinct yet related.

Emotional intelligence also reflects abilities to join intelligence, empathy, and emotions to enhance thought and understanding of interpersonal dynamics. However, substantial disagreement exists regarding the definition of EI, with respect to both terminology and operationalization. Currently, there are three main models of EI:

 * 1) Ability model
 * 2) Mixed model (usually subsumed under trait EI)
 * 3) Trait model

Different models of EI have led to the development of various instruments for the assessment of the construct. While some of these measures may overlap, most researchers agree that they tap different constructs.

Specific ability models address the ways in which emotions facilitate thought and understanding. For example, emotions may interact with thinking and allow people to be better decision makers. A person who is more emotionally responsive to crucial issues will attend to the more crucial aspects of their life. The emotional facilitation factor also involves knowing how to include or exclude emotions from thought, depending on the context and situation. This ability is emotional reasoning and understanding in response to the people, environment, and circumstances one encounters.

Ability model
Salovey and Mayer's strive to define EI within the confines of the standard criteria for a new intelligence. Following their continuing research, their initial definition of EI was revised to "The ability to perceive emotion, integrate emotion to facilitate thought, understand emotions, and to regulate emotions to promote personal growth." However, after pursuing further research, their definition of EI evolved into "the capacity to reason about emotions, and of emotions, to enhance thinking. It includes the abilities to accurately perceive emotions, to access and generate emotions so as to assist thought, to understand emotions and emotional knowledge, and to reflectively regulate emotions so as to promote emotional and intellectual growth."

The ability-based model views emotions as useful sources of information that help one to make sense of and navigate the social environment. The model proposes that individuals vary in their ability to process information of an emotional nature and in their ability to relate emotional processing to wider cognition. This ability manifests itself in certain adaptive behaviors. The model claims that EI includes four types of abilities:
 * Perceiving emotions : the ability to detect and decipher emotions in faces, pictures, voices, and cultural artifacts—including the ability to identify one's own emotions. Perceiving emotions is a basic aspect of emotional intelligence, as it makes all other processing of emotional information possible.
 * Using emotions : the ability to harness emotions to facilitate various cognitive activities, such as thinking and problem-solving. The emotionally intelligent person can capitalize fully upon his or her changing moods in order to best fit the task at hand.
 * Understanding emotions : the ability to comprehend emotion language and to appreciate complicated relationships among emotions. For example, understanding emotions encompasses the ability to be sensitive to slight variations between emotions, and the ability to recognize and describe how emotions evolve over time.
 * Managing emotions : the ability to regulate emotions in both ourselves and in others. The emotionally intelligent person can harness emotions, even negative ones, and manage them to achieve intended goals.

The ability EI model has been criticized for lacking face and predictive validity in the workplace. However, in terms of construct validity, ability EI tests have great advantage over self-report scales of EI because they compare individual maximal performance to standard performance scales and do not rely on individuals' endorsement of descriptive statements about themselves.

Measurement
The current measure of Mayer and Salovey's model of EI, the Mayer–Salovey–Caruso Emotional Intelligence Test (MSCEIT), is based on a series of emotion-based problem-solving items. Consistent with the model's claim of EI as a type of intelligence, the test is modeled on ability-based IQ tests. By testing a person's abilities on each of the four branches of emotional intelligence, it generates scores for each of the branches as well as a total score.

Central to the four-branch model is the idea that EI requires attunement to social norms. Therefore, the MSCEIT is scored in a consensus fashion, with higher scores indicating higher overlap between an individual's answers and those provided by a worldwide sample of respondents. The MSCEIT can also be expert-scored so that the amount of overlap is calculated between an individual's answers and those provided by a group of 21 emotion researchers.

Although promoted as an ability test, the MSCEIT test is unlike standard IQ tests in that its items do not have objectively correct responses. Among other challenges, the consensus scoring criterion means that it is impossible to create items (questions) that only a minority of respondents can solve, because, by definition, responses are deemed emotionally "intelligent" only if the majority of the sample has endorsed them. This and other similar problems have led some cognitive ability experts to question the definition of EI as a genuine intelligence.

In a study by Føllesdal, the MSCEIT test results of 111 business leaders were compared with how their employees described their leader. It was found that there were no correlations between a leader's test results and how he or she was rated by the employees, with regard to empathy, ability to motivate, and leader effectiveness. Føllesdal also criticized the Canadian company Multi-Health Systems, which administers the test. The test contains 141 questions but it was found after publishing the test that 19 of these did not give the expected answers. This has led Multi-Health Systems to remove answers to these 19 questions before scoring but without stating this officially.

Other measurements
Various other specific measures also assess ability in emotional intelligence. These include:
 * Diagnostic Analysis of Non-verbal Accuracy (DANVA) : The Adult Facial version includes 24 photographs of equal amount of happy, sad, angry, and fearful facial expressions of both high and low intensities which are balanced by gender. The tasks of the participants is to answer which of the four emotions is present in the given stimuli.
 * Japanese and Caucasian Brief Affect Recognition Test (JACBART) : Participants try to identify 56 faces of Caucasian and Japanese individuals expressing seven emotions such happiness, contempt, disgust, sadness, anger, surprise, and fear, which may also trail off for 0.2 seconds to a different emotion.
 * Situational Test of Emotional Understanding (STEU) : Test-takers complete 42 multiple-choice items assessing whether they understand which of five emotions a person would be experiencing in a given situation. There is also a brief version (STEU-B) consisting of 19 items.
 * Situational Test of Emotion Management (STEM) : Test-takers complete 44 multiple-choice items in which they select which of four possible responses is the most effective action to manage emotions in a specified situation. There is also a brief version (STEM-B) consisting of 18 items.

Mixed model
The model introduced by Daniel Goleman focuses on EI as a wide array of competencies and skills that drive leadership performance. Goleman's model outlines five main EI constructs:

 * 1) Self-awareness – the ability to know one's emotions, strengths, weaknesses, drives, values, and goals and recognize their impact on others while using gut feelings to guide decisions
 * 2) Self-regulation – involves controlling or redirecting one's disruptive emotions and impulses and adapting to changing circumstances
 * 3) Social skill – managing relationships to get along with others
 * 4) Empathy – considering other people's feelings especially when making decisions
 * 5) Motivation – being aware of what motivates them

Goleman includes a set of emotional competencies within each construct of EI. Emotional competencies are not innate talents, but rather learned capabilities that must be worked on and can be developed to achieve outstanding performance. Goleman posits that individuals are born with a general emotional intelligence that determines their potential for learning emotional competencies. Goleman's model of EI has been criticized in the research literature as mere "pop psychology".

Measurement
Two measurement tools are based on the Goleman model:
 * 1) The Emotional Competence Inventory (ECI), which was created in 1999, and the Emotional and Social Competence Inventory (ESCI), a newer edition of the ECI, which was developed in 2007. The Emotional and Social Competence – University Edition (ESCI-U) is also available. These tools developed by Goleman and Boyatzis provide a behavioral measure of the Emotional and Social Competencies.
 * 2) The Emotional Intelligence Appraisal, which was created in 2001 and which can be taken as a self-report or 360-degree assessment.

Trait model
Konstantinos V. Petrides proposed a conceptual distinction between the ability-based model and a trait-based model of EI and has been developing the latter over many years in numerous publications. Trait EI is "a constellation of emotional self-perceptions located at the lower levels of personality." In layman's terms, trait EI refers to an individual's self-perceptions of their emotional abilities. This definition of EI encompasses behavioral dispositions and self-perceived abilities and is measured by self report, as opposed to the ability-based model which refers to actual abilities, which have proven highly resistant to scientific measurement. Trait EI should be investigated within a personality framework. An alternative label for the same construct is trait emotional self-efficacy.

The trait EI model is general and subsumes the Goleman model discussed above. The conceptualization of EI as a personality trait leads to a construct that lies outside the taxonomy of human cognitive ability. This is an important distinction in that it bears directly on the operationalization of the construct and the theories and hypotheses that are formulated about it.

Measurement
There are many self-report measures of EI, including the EQ-i, the Swinburne University Emotional Intelligence Test (SUEIT), and the Schutte EI model. None of these assess intelligence, abilities, or skills (as their authors often claim), but rather, they are limited measures of trait emotional intelligence. The most widely used and widely researched measure of self-report or self-schema (as it is currently referred to) emotional intelligence is the EQ-i 2.0. Originally known as the BarOn EQ-i, it was the first self-report measure of emotional intelligence available, the only measure predating Goleman's bestselling book.

The Trait Emotional Intelligence Questionnaire (TEIQue) provides an operationalization for the model of Konstantinos V. Petrides and colleagues, that conceptualizes EI in terms of personality. The test encompasses 15 subscales organized under four factors: well-being, self-control, emotionality, and sociability. The psychometric properties of the TEIQue were investigated in a study on a French-speaking population, where it was reported that TEIQue scores were globally normally distributed and reliable.

The researchers found TEIQue scores were unrelated to nonverbal reasoning (Raven's matrices), which they interpreted as support for the personality trait view of EI (as opposed to the view that it is a form of intelligence). As expected, TEIQue scores were positively related to some of the Big Five personality traits (extraversion, agreeableness, openness, conscientiousness) as well as inversely related to others (alexithymia, neuroticism). A number of quantitative genetic studies have been carried out within the trait EI model, which have revealed significant genetic effects and heritabilities for all trait EI scores. Two studies (one a meta-analysis) involving direct comparisons of multiple EI tests yielded very favorable results for the TEIQue.

The Big Five Personality Traits theory offers a straightforward framework for understanding and enhancing relationships by uncovering the motivations behind people's behaviors. This theory is equally valuable for self-awareness and for improving interpersonal dynamics. Also referred to as the Five Factor Model, the Big Five Model is the most widely accepted personality theory. It suggests that personality can be distilled into five fundamental dimensions, often remembered as CANOE or OCEAN (conscientiousness, agreeableness, neuroticism, openness, extraversion). In contrast to other trait theories that sort individuals into binary categories (e.g. introvert or extrovert), the Big Five Model asserts that each personality trait exists on a spectrum. Consequently, individuals are positioned along a continuum between two contrasting poles.

General effects
A review published in the Annual Review of Psychology in 2008 found that higher emotional intelligence is positively correlated with:
 * 1) Better social relations for children – Among children and teens, emotional intelligence positively correlates with good social interactions and relationships, and negatively correlates with deviance from social norms and anti-social behavior measured both in and out of school as reported by children themselves, their own family members, and their teachers.
 * 2) Better social relations for adults – High emotional intelligence among adults is correlated with better self-perception of social ability and more successful interpersonal relationships, with less interpersonal aggression and problems.
 * 3) Highly emotionally intelligent people are perceived more positively by others – Other people perceive those with high EI to be more pleasant, socially skilled, and empathic.
 * 4) Better academic achievement – Emotional intelligence is correlated with greater achievement in academics as reported by teachers, but generally not higher grades once the factor of IQ is taken into account.
 * 5) Better social dynamics at work as well as better negotiating ability.
 * 6) Better well-being – Emotional intelligence is positively correlated with higher life satisfaction and self-esteem, and lower levels of insecurity or depression. It is also negatively correlated with poor health choices and behavior.

Emotionally intelligent people are more likely to have a better understanding of themselves and to make conscious decisions based on emotion and rationale combined. Overall, it leads a person to self-actualization.

The relevance and importance of emotional intelligence in contexts of business leadership, commercial negotiation, and dispute resolution has been recognized, and professional qualifications and continuous professional development have incorporated aspects of understanding emotions and developing greater insight into emotional interactions. Especially in the globalized world, the ability to be a world leader is becoming important. A high EQ allows business leaders to interact with various different cultures, and they must be comfortable in these diverse cultural environments, having diverse teams and organization. EQ has become an essential part of leading an organization.

Bullying
Bullying is an abusive social interaction between peers that can include aggression, harassment, and violence. Bullying is typically repetitive and enacted by those who are in a position of power over the victim. A growing body of research illustrates between bullying and emotional intelligence. It also shows that emotional intelligence is a key factor in cybervictimization.

Emotional intelligence (EI) is a set of abilities related to the understanding, use, and management of emotion as it relates to one's self and others. Mayer et al. define EI as: "accurately perceiving emotion, using emotions to facilitate thought, understanding emotion, and managing emotion". The concept combines emotional and intellectual processes. Lower emotional intelligence appears to be related to involvement in bullying, as the bully and/or the victim of bullying. EI seems to play an important role in both bullying behavior and victimization in bullying; given that EI is malleable, EI education could improve bullying prevention and intervention initiatives.

Job performance
A meta-analysis of emotional intelligence and job performance showed correlations of r=.20 (for job performance & ability EI) and r=.29 (for job performance and mixed EI). Earlier research on EI and job performance had shown mixed results: a positive relation has been found in some of the studies, while in others there was no relation or an inconsistent one. This led researchers Cote and Miners to offer a compensatory model between EI and IQ, that posits that the association between EI and job performance becomes more positive as cognitive intelligence decreases, an idea first proposed in the context of academic performance. The results of the former study supported the compensatory model: employees with low IQ get higher task performance and organizational citizenship behavior directed at the organization, the higher their EI. It has also been observed that there is no significant link between emotional intelligence and work attitude-behavior.

Another study suggests that EI is not necessarily a universally positive trait. The study found a negative correlation between EI ; while under low levels of managerial work demands, they found a negative relationship between EI and teamwork effectiveness. An explanation for this may be gender differences in EI, as women tend to score higher levels than men. This furthers the idea that job context plays a role in the relationships between EI, teamwork effectiveness, and job performance.

Another study assessed a possible link between EI and entrepreneurial behaviors and success.

Although studies between emotional intelligence (EI) and job performance have shown mixed results of high and low correlations, EI is an undeniably better predictor than most of the hiring methods commonly used in companies, such as letters of reference or cover letters. By 2008, 147 companies and consulting firms in the U.S. had developed programmes that involved EI for training and hiring employees. Van Rooy and Viswesvaran showed that EI correlated significantly with different domains in performance, ranging from .24 for job performance to .10 for academic performance. Employees high on EI would be more aware of their own emotions and others', which in turn, could lead companies to better profits and less unnecessary expenses. This is especially important for expatriate managers, who have to deal with mixed emotions and feelings, while adapting to a new working culture. Employees high in EI show more confidence in their roles, which allow them to face demanding tasks positively.

According to a science book by the journalist Daniel Goleman, emotional intelligence accounts for more career success than IQ. Other studies argued that employees high on EI perform substantially better than employees low in EI. This is measured by self-reports and different work performance indicators, such as wages, promotions and salary increase. According to Lopes et al. EI contributes to developing strong and positive relationships with co-workers and to performing efficiently in work teams. This benefits performance of workers by providing emotional support and instrumental resources needed to succeed in their roles. Emotionally intelligent employees have better resources to cope with stressing situations and demanding tasks, which enable them to outperform in those situations. For instance, Law et al. found that EI was the best predictor of job performance beyond general cognitive ability among IT scientists in a computer company in China.

When examining the connection between job performance and emotional intelligence, it's essential to take into account the impact of "managing up," which signifies a positive rapport between an employee and their supervisor. Previous research found that the quality of this relationship could influence subjective assessments of job performance. Employees with strong emotional intelligence tend to dedicate more time to cultivating their rapport with supervisors. As a result, those with higher EI are more likely to achieve favorable outcomes in performance evaluations compared to those with lower EI.

Based on theoretical and methodological approaches, EI measures are categorized in three main streams: (1) ability-based measures (e.g. MSCEIT), (2) self-reports of abilities measures (e.g. SREIT, SUEIT and WLEIS), and (3) mixed-models (e.g. AES, ECI, EI questionnaire, EIS, EQ-I and GENOS), which include measures of EI and traditional social skills. O'Boyle Jr. et al. found that the three EI streams together had a positive correlation of 0.28 with job performance. Similarly, each of EI streams independently obtained a positive correlation of 0.24, 0.30, and 0.28, respectively. Streams 2 and 3 showed an incremental validity for predicting job performance over and above personality (Five Factor model) and general cognitive ability. Both streams 2 and 3 were the second most important predictor of job performance, below general cognitive ability. Stream 2 explained 13.6% of the total variance, whereas stream 3 explained 13.2%. In order to examine the reliability of these findings, a publication bias analysis was developed. Results indicated that studies on EI-job performance correlation prior to 2010 do not present substantial evidence to suggest the presence of publication bias. Noting that O'Boyle Jr. et al. had included self-rated performance and academic performance in their meta-analysis, Joseph, Jin, Newman, & O'Boyle collaborated to update the meta-analysis to focus specifically on job performance; using measures of job performance, these authors showed r=.20 (for job performance & ability EI) and r=.29 (for job performance and mixed EI).

The Consortium for Research on Emotional Intelligence in Organizations argues that there is a business case in favor of emotional intelligence but, despite the validity of previous findings, some researchers still question whether EI-job performance correlation makes a real impact on business strategies. Critics argue that the popularity of EI studies is due to media advertising, rather than objective scientific findings. Also, the relationship between job performance and EI is not as strong as suggested. This relationship requires the presence of other constructs to raise important outcomes. For instance, studies found that EI is positively associated with teamwork effectiveness under job contexts of high managerial work demands, which improves job performance. This is due to the activation of strong emotions during the performance on this job context. In this scenario, emotionally intelligent individuals show a better set of resources to succeed in their roles. However, individuals with high EI show a similar level of performance than non-emotionally intelligent employees under different job contexts. Moreover, Joseph and Newman suggest that emotional perception and emotional regulation components of EI highly contribute to job performance under job contexts of high emotional demands. Moon and Hur found that emotional exhaustion ("burn-out") significantly influences the job performance-EI relationship. Emotional exhaustion showed a negative association with two components of EI (optimism and social skills). Hence, the job performance-EI relationship is stronger under contexts of high emotional exhaustion or burn-out; in other words, employees with high levels of optimism and social skills possess better resources to outperform when facing high emotional exhaustion contexts.

Leadership
Several studies attempt to study the relationship between EI and leadership. Although EI plays a positive role in leadership effectiveness, what makes a leader effective is what he/she does with his/her role, rather than his/her interpersonal skills and abilities. Although in the past a good or effective leader gave orders and controlled the overall performance of the organization, almost everything is different nowadays: leaders are now expected to motivate and create a sense of belonging that makes employees feel comfortable, thus, making them work more effectively.

This does not mean that actions are more important than emotional intelligence. Leaders still need to grow emotionally in order to handle stress, life balance, and other things. A proper way to grow emotionally, for instance, is developing a sense of empathy since empathy is a key factor when it comes to emotional intelligence. In a study conducted to analyze the relationship between school counselors' EI and leadership skills, it was concluded that several participants were good leaders because their emotional intelligence was developed in counselor preparations, where empathy is taught.

Health
A 2007 meta-analysis of 44 effect sizes by Schutte et al. found that emotional intelligence was associated with better mental and physical health. Particularly, trait EI had the stronger association with mental and physical health. This was replicated in 2010 by researcher Alexandra Martins who found trait EI is a strong predictor for health after conducting a meta-analysis based on 105 effect sizes and 19,815 participants. This meta-analysis also indicated that this line of research reached enough sufficiency and stability to conclude EI is a positive predictor for health.

An earlier study by Mayer and Salovey argued that high EI can increase one's well-being because of its role in enhancing relationships.

Self-esteem and drug dependence
A 2012 study in India cross-examined emotional intelligence, self-esteem, and marijuana dependence. Out of a sample of 200, 100 of whom were dependent on cannabis and the other 100 emotionally healthy, the dependent group scored exceptionally low on EI when compared to the control group. They also found that the dependent group also scored low on self-esteem when compared to the control.

Another study in 2010 examined whether or not low levels of EI had a relationship with the degree of drug and alcohol addiction in Australia. In the assessment of 103 residents in a drug rehabilitation center, they examined their EI along with other psychosocial factors in a one-month interval of treatment. They found that participants' EI scores improved as their levels of addiction lessened as part of their treatment.

Academic performance
A 2020 meta-analysis showed that students with higher emotional intelligence show higher academic performance at school. This was a summary of over 1,246 effects from 158 different studies, with a sample size of 42,529. Students with higher emotional intelligence had better scores on standardized tests and achieved higher grades. The effect was significantly larger for humanities than for science/maths areas of study, and significantly larger for ability emotional intelligence (measured with objective tasks), than for rating scales of emotional intelligence. The association of emotional intelligence with higher academic achievement was still significant even after considering the effect of students' Big Five personality and intelligence.

There are three reasons why greater emotional intelligence might predict stronger academic performance. First, emotionally intelligent students are able to regulate their emotions at school—they are able to control their anxiety surrounding tests and assessment, and their boredom when the material is not intrinsically interesting. This means their emotions do not impede their test scores or their ability to learn. Second, emotionally intelligent students are able to build better social relationships with other students and with instructors. This means that they have sources of help when needed—other students and teachers are more willing to help them when they get stuck. Third, some of the abilities of emotional intelligence (understanding emotions, for example) overlap with academic content, particularly in the humanities. That is, analyzing universal themes in literature or the social forces underpinning historic events require a knowledge of human emotions.

Criticisms
EI, and Goleman's original 1995 analysis, have been criticized within the scientific community:

Predictive power
Landy distinguishes between the "commercial" and "academic" discussion of EI, basing this distinction on the alleged predictive power of EI as seen by each of the two. According to Landy, the former makes expansive claims on the applied value of EI, while the latter is trying to warn users against these claims. As an example, Goleman (1998) asserts that "the most effective leaders are alike in one crucial way: they all have a high degree of what has come to be known as emotional intelligence.... emotional intelligence is the sine qua non of leadership." In contrast, Mayer (1999) cautions that "the popular literature's implication—that highly emotionally intelligent people possess an unqualified advantage in life—appears overly enthusiastic at present and unsubstantiated by reasonable scientific standards." Landy further reinforces this argument by noting that the data upon which these claims are based are held in "proprietary databases", which means they are unavailable to independent researchers for reanalysis, replication, or verification.

It is difficult to create objective measures of emotional intelligence and demonstrate its influence on leadership as many scales are self-report measures.

In a 2009 academic exchange, Antonakis and Ashkanasy/Dasborough mostly agreed that researchers who test whether EI matters for leadership have not done so using robust research designs; therefore, currently there is no strong evidence showing that EI predicts leadership outcomes when accounting for personality and IQ. Antonakis argued that EI might not be needed for leadership effectiveness (he referred to this as the "curse of emotion" phenomenon, because leaders who are too sensitive to their and others' emotional states might have difficulty making decisions that would result in emotional labor for the leader or followers). A 2010 meta-analysis seems to support the Antonakis position: it found that, using data free from problems of common source and common methods, EI measures correlated only ρ=0.11 with measures of transformational leadership. Barling, Slater, and Kelloway also support this position on transformational leadership.

Ability-measures of EI fared worst (i.e., ρ=0.04); the WLEIS (Wong-Law measure) did a bit better (ρ=0.08), and the Bar-On measure slightly better (ρ=0.18). However, the validity of these estimates does not include the effects of IQ or the big five personality, which correlate both with EI measures and leadership. A study analyzing the impact of EI on both job performance and leadership found that the meta-analytic validity estimates for EI dropped to zero when Big Five traits and IQ were controlled for. A meta-analysis showed the same result for Ability EI.

Self-reported and Trait EI measures retain a fair amount of predictive validity for job performance after controlling Big Five traits and IQ. However the greater predictive validity of Trait EI measures can be attributed to their inclusion of content related to achievement motivation, self efficacy, and self-rated performance. Meta-analytic evidence confirms that self-reported emotional intelligence predicting job performance is due to mixed-EI and trait-EI measures tapping into self-efficacy and self-rated performance, in addition to the domains of Neuroticism, Extraversion, Conscientiousness, and IQ. As such, the predictive ability of mixed EI to job performance drops to nil when controlling for these factors.

A study of the predictive ability of EI for job performance concluded that higher EI was associated with higher leadership effectiveness regarding achievement of organizational goals. This study shows that EI may serve an identifying tool in understanding who is (or is not) likely to deal effectively with colleagues. Furthermore, one can develop and enhance one's leadership qualities by advancing one's emotional intelligence. EI can be deliberately developed, specifically the facets of "facilitating thinking with emotions" and "monitoring and regulation of emotions" in the workplace.

Correlations with personality
Researchers raised concerns about the extent to which self-report EI measures correlate with established personality dimensions. Self-report EI measures and personality measures converge because they both purport to measure personality traits. Two dimensions of the Big Five stand out as most related to self-report EI: neuroticism and extraversion. Neuroticism relates to negative emotionality and anxiety. People who score high on neuroticism are likely to score low on self-report EI measures.

Studies examined the multivariate effects of personality and intelligence on EI and attempted to correct estimates for measurement error. For example, one study showed that general intelligence (measured with the Wonderlic Personnel Test), agreeableness (measured by the NEO-PI), as well as gender could reliably predict the measure of EI ability. They gave a multiple correlation (R) of .81 with the MSCEIT (perfect prediction would be 1). This result was replicated. The replication found a multiple R of .76 using Cattell's "Culture Fair" intelligence test and the Big Five Inventory (BFI); significant covariates were intelligence (standardized beta = .39), agreeableness (standardized beta = .54), and openness (standardized beta = .46).

A study of the Ability Emotional Intelligence Measure found similar results (Multiple R = .69), with significant predictors being intelligence, standardized beta = .69 (using the Swaps Test and a Wechsler scales subtest, the 40-item General Knowledge Task) and empathy, standardized beta = .26 (using the Questionnaire Measure of Empathic Tendency). Antonakis and Dietz (2011b) also show how including or excluding important controls variables can fundamentally change results.

Interpretations of the correlations between EI questionnaires and personality have been varied, but a prominent view is the Trait EI view, which re-interprets EI as a collection of personality traits.

A 2011 meta-analysis classified EI studies into three streams: "(1) ability‐based models that use objective test items; (2) self‐report or peer‐report measures based on the four‐branch model of EI; and (3) 'mixed models' of emotional competencies." It found that these "three streams have corrected correlations ranging from 0.24 to 0.30 with job performance. The three streams correlated differently with cognitive ability and with neuroticism, extraversion, openness, agreeableness, and conscientiousness. Streams 2 and 3 have the largest incremental validity beyond cognitive ability and the Five Factor Model (FFM)." The meta-analysis concluded that "all three streams of EI exhibited substantial relative importance in the presence of FFM and intelligence when predicting job performance." A follow-up meta-analysis in 2015 further substantiated these findings, and addressed concerns about "the questionable construct validity of mixed EI measures" by arguing that "mixed EI instruments assess a combination of ability EI and self-perceptions, in addition to personality and cognitive ability."

A 2017 meta-analysis of 142 data sources found a very large overlap between the general factor of personality and trait EI. The overlap was so large they concluded that "The findings suggest that the general factor of personality is very similar, perhaps even synonymous, to trait EI." However, the overlap between the general factor of personality and ability EI was more moderate, with a correlation of about 0.28.

In 2021, two review papers examined the relationship between emotional intelligence and the dark triad of personality traits (narcissism, Machiavellianism, and psychopathy). This research found that emotional intelligence showed negative associations with all three dark triad domains of personality. Of the four ability branches of emotional intelligence, the largest effects were for emotion management (versus emotion perception, use, or understanding) and for psychopathy (versus narcissism or Machiavellianism). The two different facets of narcissism showed different relationships with emotional intelligence. Vulnerable narcissism (characterized by anxiety and fragile self-esteem) was associated with lower emotional intelligence. However, grandiose narcissism (characterized by self-confidence, dominance, and an inflated sense of ego) related to higher levels of emotional intelligence. This indicates that not all "dark" personalities lack emotional intelligence.

A 2021 meta-analysis showed that emotional intelligence was positively associated with secure attachment in adults, but negatively associated with insecure attachment styles such as anxious attachment and avoidant attachment. The associations with anxious attachment and avoidant attachment were significant for both ability EI and for rating scales of EI. However, only rating scales of EI showed a significantly positive association with secure attachment. The authors suggest that the early development of attachment styles may facilitate (or hinder) the development of emotional abilities and traits involved in EI.

Socially desirable responding
Socially desirable responding (SDR), or "faking good", is a response pattern in which test-takers systematically represent themselves with an excessive positive bias. This bias has long been known to contaminate responses on personality inventories, acting as a mediator of the relationships between self-report measures.

It has been suggested that responding in a desirable way is a "response set"—a situational and temporary response pattern. This is contrasted with a "response style", which is a more long-term trait-like quality. Considering the contexts in which some self-report EI inventories are used (e.g., employment settings), the problems of response sets in high-stakes scenarios are clear.

There is evidence that people can ‘‘fake good’’ on emotional intelligence tests, resulting in inaccurate measurement with several studies showing people can distort their responses on both self-rated and informant-rated emotional intelligence measures when instructed to.

There are a few methods to prevent socially desirable responding on behavior inventories. Some researchers believe it is necessary to warn test-takers not to fake good before taking a personality test. Some inventories use validity scales in order to determine the likelihood or consistency of the responses across all items.

EI as behavior rather than intelligence
Goleman's early work has been criticized for assuming that EI is a type of intelligence or cognitive ability. Eysenck writes that Goleman's description of EI contains unsubstantiated assumptions about intelligence in general and that it even runs contrary to what researchers have come to expect when studying types of intelligence: "'[Goleman] exemplifies more clearly than most the fundamental absurdity of the tendency to class almost any type of behavior as an 'intelligence'... If these five 'abilities' define 'emotional intelligence', we would expect some evidence that they are highly correlated; Goleman admits that they might be quite uncorrelated, and in any case, if we cannot measure them, how do we know they are related? So the whole theory is built on quicksand: there is no sound scientific basis.'"

Similarly, Locke claims that the concept of EI is a misinterpretation of the intelligence construct, and he offers an alternative interpretation: it is not another form or type of intelligence, but intelligence—the ability to grasp abstractions—applied to a particular life domain: emotions. He suggests the concept should be re-labeled and referred to as a skill.

The essence of these criticisms is that scientific inquiry depends on valid and consistent construct utilization and that before the introduction of the term EI, psychologists had established theoretical distinctions between factors such as abilities and achievements, skills and habits, attitudes and values, and personality traits and emotional states. Some scholars believe that the term EI merges and conflates such accepted concepts and definitions.

EI as skill rather than moral quality
Adam Grant warned of the common but mistaken perception of EI as a desirable moral quality rather than a skill. Grant asserted that a well-developed EI is not only an instrumental tool for accomplishing goals, but can function as a weapon for manipulating others by robbing them of their capacity to reason.

EI as a measure of conformity
One criticism of the works of Mayer and Salovey comes from a study that suggests that the EI, as measured by the MSCEIT, may only be measuring conformity. This argument is rooted in the MSCEIT's use of consensus-based assessment, and in the fact that scores on the MSCEIT are negatively distributed (meaning that its scores differentiate between people with low EI better than people with high EI).

EI as a form of knowledge
Another criticism says that in contrast with tests of cognitive ability, the MSCEIT "tests knowledge of emotions but not necessarily the ability to perform tasks that are related to the knowledge that is assessed". If someone knows how they should behave in an emotionally laden situation, it does not necessarily follow that they could actually carry out the reported behavior.

NICHD pushes for consensus
The National Institute of Child Health and Human Development recognized that because there are divisions about the topic of EI, the mental health community needs to agree on some guidelines to describe good mental health and positive mental living conditions. In their section, "Positive Psychology and the Concept of Health", they explain: "Currently there are six competing models of positive health, which are based on concepts such as being above normal, character strengths and core virtues, developmental maturity, social-emotional intelligence, subjective well-being, and resilience. But these concepts define health in philosophical rather than empirical terms. Dr. [Lawrence] Becker suggested the need for a consensus on the concept of positive psychological health...".

title: Emotional intelligence


text:
Des Moines County, Iowa

Des Moines County is located in the U.S. state of Iowa. As of the 2020 census, the population was 38,910. The county seat and largest city is Burlington. It is one of Iowa's two original counties along with Dubuque County; both were organized by the Michigan Territorial legislature in 1834.

Des Moines County is part of the Burlington, IA–IL Micropolitan Statistical Area.

Des Moines County should not be confused with the city of Des Moines, which is the capital of Iowa. Des Moines County sits on Iowa's eastern border alongside the Mississippi River. The city of Des Moines is in Polk County in central Iowa. Both places derive their name from the Des Moines River, which flows through the city of Des Moines and originally flowed through the county. When the county was divided early in Iowa's history, the river ended up further west, forming the border between Lee County, Iowa and the state of Missouri.

History
At an extra session of the Sixth Legislative Assembly of Michigan Territory held in September 1834, the Iowa District was divided into two counties by running a line due west from the lower end of Rock Island in the Mississippi River. The territory north of this line (which started just south of the present-day Davenport) was named Dubuque County, and all south of it was Demoine County. It was named after the Des Moines River. From July 3, 1836, until July 3, 1838, Des Moines County was part of Wisconsin Territory. The county underwent various border changes during this time. July 4, 1838, the named county became part of Iowa Territory (later the state of Iowa).

The current Des Moines County Court House was completed in 1940. The Iowa Army Ammunition Plant was also established in 1940.

Geography

According to the U.S. Census Bureau, the county has a total area of 430 sqmi, of which 416 sqmi is land and 14 sqmi (3.2%) is water. The Mississippi River forms the east border; Skunk River, the south border; and the county is drained by Flint Creek.

Major highways

 * US 34.svg U.S. Highway 34
 * US 61.svg U.S. Highway 61

Transit

 * Burlington station
 * Burlington Urban Service
 * List of intercity bus stops in Iowa

Airport
The Southeast Iowa Regional Airport (IATA code BRL), is located on the southern side of Burlington.

Adjacent counties

 * Louisa County (north)
 * Hancock County, Illinois (southeast)
 * Henderson County, Illinois (east)
 * Lee County (south)
 * Henry County (west)

2020 census
The 2020 census recorded a population of 38,910 in the county, with a population density of. 94.26% of the population reported being of one race. 82.03% were non-Hispanic White, 6.51% were Black, 3.20% were Hispanic, 0.20% were Native American, 1.04% were Asian, 0.06% were Native Hawaiian or Pacific Islander and 6.97% were some other race or more than one race. There were 18,782 housing units of which 16,751 were occupied.

2010 census
The 2010 census recorded a population of 40,325 in the county, with a population density of. There were 18,535 housing units, of which 17,003 were occupied.

2000 census
As of the 2000 census, there were 42,351 people, 17,270 households, and 11,536 families residing in the county. The population density was 102 PD/sqmi. There were 18,643 housing units at an average density of 45 /mi2. The racial makeup of the county was 93.69% White, 3.57% Black or African American, 0.25% Native American, 0.59% Asian, 0.04% Pacific Islander, 0.68% from other races, and 1.18% from two or more races. 1.75% of the population were Hispanic or Latino of any race.

There were 17,270 households, out of which 29.60% had children under the age of 18 living with them, 52.70% were married couples living together, 10.50% had a female householder with no husband present, and 33.20% were non-families. 28.60% of all households were made up of individuals, and 12.60% had someone living alone who was 65 years of age or older. The average household size was 2.40 and the average family size was 2.94.

In the county, the population was spread out, with 24.40% under the age of 18, 8.50% from 18 to 24, 26.10% from 25 to 44, 24.30% from 45 to 64, and 16.70% who were 65 years of age or older. The median age was 39 years. For every 100 females, there were 93.50 males. For every 100 females age 18 and over, there were 90.30 males.

The median income for a household in the county was $36,790, and the median income for a family was $45,089. Males had a median income of $34,880 versus $22,530 for females. The per capita income for the county was $19,701. About 8.20% of families and 10.70% of the population were below the poverty line, including 17.30% of those under age 18 and 7.40% of those age 65 or over.

Cities

 * Burlington
 * Danville
 * Mediapolis
 * Middletown
 * West Burlington

Census-designated places

 * Augusta
 * Beaverdale
 * Kingston
 * Oak Hills
 * Sperry
 * Yarmouth

Other unincorporated communities

 * Dodgeville

Townships

 * Benton
 * Concordia
 * Danville
 * Flint River
 * Franklin
 * Huron
 * Jackson
 * Pleasant Grove
 * Tama
 * Union
 * Washington
 * Yellow Springs

Population ranking
The population ranking of the following table is based on the 2020 census of Des Moines County.

† county seat

Politics
From 1896 through 1960, Des Moines County was a primarily Republican county, backing Democratic nominees only four times in the period (Woodrow Wilson in 1912, with a low plurality; Franklin Roosevelt in his two landslides in 1932 and 1936; and Harry Truman in 1948). From 1964 through 2012, it became a Democratic stronghold, backing the Democratic nominee in every election in this period save in Nixon's 1972 landslide. In 2016, Donald Trump became the first Republican since 1972 to carry the county, despite narrowly losing the overall national popular vote; the county swung over 25% in his favor relative to its 2012 vote. The change to the GOP happened while the county experienced an economic decline. In 2020, Trump again carried the county, with an increased vote share, the first time the county has voted Republican twice in a row since 1956 and 1960.

title: Des Moines County, Iowa


text:
Delaware County, Iowa

Delaware County is a county located in the U.S. state of Iowa. As of the 2020 census, the population was 17,488. The county seat is Manchester. The county takes its name after the U.S. state of Delaware.

Geography

According to the U.S. Census Bureau, the county has a total area of 579 sqmi, of which 578 sqmi is land and 1.2 sqmi (0.2%) is water. It has a rough hilly surface.

Major highways

 * US 20.svg U.S. Highway 20
 * Circle sign 3.svg Iowa Highway 3
 * Elongated circle 13.svg Iowa Highway 13
 * Elongated circle 38.svg Iowa Highway 38

Adjacent counties

 * Buchanan County (west)
 * Clayton County (north)
 * Dubuque County (east)
 * Fayette County (northwest)
 * Jones County (southeast)
 * Linn County (southwest)

2020 census
The 2020 census recorded a population of 17,488 in the county, with a population density of. 97.75% of the population reported being of one race. 94.60% were non-Hispanic White, 0.70% were Black, 1.40% were Hispanic, 0.29% were Native American, 0.27% were Asian, 0.01% were Native Hawaiian or Pacific Islander and 2.74% were some other race or more than one race. There were 8,100 housing units of which 7,141 were occupied.

2010 census
The 2010 census recorded a population of 17,764 in the county, with a population density of. There were 8,028 housing units, of which 7,062 were occupied.

2000 census
As of the census of 2000, there were 18,404 people, 6,834 households, and 5,029 families residing in the county. The population density was 32 /mi2. There were 7,682 housing units at an average density of 13 /mi2. The racial makeup of the county was 99.28% White, 0.07% Black or African American, 0.10% Native American, 0.14% Asian, 0.01% Pacific Islander, 0.10% from other races, and 0.30% from two or more races. 0.66% of the population were Hispanic or Latino of any race.

There were 6,834 households, out of which 36.70% had children under the age of 18 living with them, 64.10% were married couples living together, 6.20% had a female householder with no husband present, and 26.40% were non-families. 23.00% of all households were made up of individuals, and 11.20% had someone living alone who was 65 years of age or older. The average household size was 2.66 and the average family size was 3.15.

In the county, the population was spread out, with 29.00% under the age of 18, 7.00% from 18 to 24, 27.60% from 25 to 44, 21.50% from 45 to 64, and 15.00% who were 65 years of age or older. The median age was 37 years. For every 100 females there were 98.40 males. For every 100 females age 18 and over, there were 96.60 males.

The median income for a household in the county was $37,168, and the median income for a family was $43,607. Males had a median income of $30,712 versus $19,685 for females. The per capita income for the county was $17,327. About 6.30% of families and 7.90% of the population were below the poverty line, including 8.50% of those under age 18 and 9.80% of those age 65 or over.

Cities

 * Colesburg
 * Delaware
 * Delhi
 * Dundee
 * Dyersville
 * Earlville
 * Edgewood
 * Greeley
 * Hopkinton
 * Manchester
 * Masonville
 * Ryan

Townships
Delaware County is divided into these townships:

 * Adams
 * Bremen
 * Coffins Grove
 * Colony
 * Delaware
 * Delhi
 * Elk
 * Hazel Green
 * Honey Creek
 * Milo
 * Prairie
 * Richland
 * South Fork
 * North Fork
 * Oneida
 * Union

Unincorporated Communities

 * Petersburg
 * Robinson
 * Rockville

Population ranking
The population ranking of the following table is based on the 2020 census of Delaware County.

† county seat

title: Delaware County, Iowa


text:
Decatur County, Iowa

Decatur County is a county located in the U.S. state of Iowa. As of the 2020 census, the population was 7,645. The county seat is Leon. This county is named for Stephen Decatur Jr., a hero in the War of 1812.

History
Decatur County was organized in 1850 and named for Stephen Decatur, a naval hero of the War of 1812. The current courthouse was dedicated in 1908.

Geography
According to the U.S. Census Bureau, the county has a total area of 533 sqmi, of which 532 sqmi is land and 1.6 sqmi (0.3%) is water.

Major highways

 * I-35.svg Interstate 35
 * US 69.svg U.S. Highway 69
 * Circle sign 2.svg Iowa Highway 2

Transit

 * Jefferson Lines
 * List of intercity bus stops in Iowa

Adjacent counties

 * Clarke County (north)
 * Wayne County (east)
 * Mercer County, Missouri (southeast)
 * Harrison County, Missouri (southwest)
 * Ringgold County (west)

2020 census
The 2020 census recorded a population of 7,645 in the county, with a population density of. 96.44% of the population reported being of one race. There were 3,653 housing units of which 2,986 were occupied.

2010 census
The 2010 census recorded a population of 8,457 in the county, with a population density of. There were 3,834 housing units, of which 3,223 were occupied.

2000 census
At the 2000 census, there were 8,689 people, 3,337 households and 2,149 families residing in the county. The population density was 16 /mi2. There were 3,833 housing units at an average density of 7 /mi2. The racial makeup of the county was 96.46% White, 0.98% Black or African American, 0.24% Native American, 0.63% Asian, 0.12% Pacific Islander, 0.46% from other races, and 1.12% from two or more races. 1.70% of the population were Hispanic or Latino of any race.

There were 3,337 households, of which 28.00% had children under the age of 18 living with them, 54.30% were married couples living together, 7.20% had a female householder with no husband present, and 35.60% were non-families. 30.30% of all households were made up of individuals, and 15.50% had someone living alone who was 65 years of age or older. The average household size was 2.37 and the average family size was 2.96.

23.00% of the population were under the age of 18, 16.30% from 18 to 24, 21.60% from 25 to 44, 21.50% from 45 to 64, and 17.70% who were 65 years of age or older. The median age was 36 years. For every 100 females there were 95.70 males. For every 100 females age 18 and over, there were 91.90 males.

The median household income was $27,343 and the median family income was $34,831. Males had a median income of $25,569 compared with $19,309 for females. The per capita income for the county was $14,209. About 10.90% of families and 15.50% of the population were below the poverty line, including 15.60% of those under age 18 and 13.70% of those age 65 or over.

Decatur County is considered to be the poorest in Iowa, reporting that almost 20% of its residents live in poverty.

County officials
Supervisors Steve Fulkerson Samuel Wengryn Ward Graham

Treasurer Janet Pierson

Attorney Alan Wilson

Auditor Charlene Hoover

Recorder Erica Cook

Sheriff Chris Lane

Assessor Justin Cornett

Engineer Vacant

Clerk of Court Traci Tharp

Public Health Administrator Shelley Bickel

Veterans Affairs Administrator Samantha Schaff

Conservation Director Kayla Clausen

Mental Health Director Kathy Lerma

Cities

 * Davis City
 * Decatur City
 * Garden Grove
 * Grand River
 * Lamoni
 * Leon
 * Le Roy
 * Pleasanton
 * Van Wert
 * Weldon

Townships
Decatur County is divided into these townships:

 * Bloomington
 * Burrell
 * Center
 * Decatur
 * Eden
 * Fayette
 * Franklin
 * Garden Grove
 * Grand River
 * Hamilton
 * High Point
 * Long Creek
 * Morgan
 * New Buda
 * Richland
 * Woodland

Population ranking
The population ranking of the following table is based on the 2020 census of Decatur County.

† county seat

title: Decatur County, Iowa