Why create the Local Government Diversity Dashboard?
Stakeholders pursuing diversity, equity, and inclusion (DEI) in local government lack a clear, publicly available benchmarking resource. The Local Government Diversity Dashboard—which will initially focus on gender diversity of local government leadership—seeks to fill this gap by providing a one-stop shop for tracking and discussing diversity in local government.
How do I use the LGDD?
Here's a short video with four ways you can quickly engage with the LGDD to learn more and share your thoughts.
Who made the LGDD?
Which local governments are included in the LGDD?
All 21,000+ municipalities, townships and counties in the United States with a population of 1,000 or more.
What local government roles are covered in the LGDD?
The first role we are covering is ‘Top Appointed Official’ (e.g., city manager, county administrator, etc.) To be considered a top appointed official in this dataset, a person must be appointed by the governing body and be responsible for running the day-to-day operations of the government. Whether a person is a top appointed official is not based on a person’s title but rather an assessment of their duties and responsibilities.
CivicPulse and ELGL are seeking funding for adding sixteen other positions:
Top Elected Officials
Governing Board Members
Head of Finance
Head of Information Technology
Head of Law Enforcement
Head of Clerk's Office
Head of Human Resources
Head of Purchasing/Procurement
Head of Fire Protection Services
Head of Public Works
Head Building Official
Head of Communications
Head of Water
Head of Parks and Recreation
Head of Local Economic Development
Head of Planning/Zoning
If you are interested in sponsoring a position, please reach out to Kirsten Wyatt at email@example.com.
How often is the data updated on LGDD?
The data will be updated every six months. The next update will be October 2022. However, specific data corrections not associated with turnover will be made on a monthly basis.
Where does LGDD data come from?
LGDD data is derived from a dynamically, comprehensive list of local government leaders developed and maintained by Power Almanac.
How is ‘Top Appointed Official’ defined?
To be considered a top appointed official in this dataset, a person must be appointed by the governing body and be responsible for running the day-to-day operations of the government. Whether a person is a top appointed official is not based on a person’s title but rather an assessment of their duties and responsibilities done by Power Almanac when the data was collected.
Can you explain the name-based gender coding methodology you use?
The gender coding was done by comparing the first name of each official to historical records from the Social Security Administration baby name data. The probability that a person’s first name belongs to a man or a woman is calculated for each record in the dataset. If the probability is greater than 97 percent that a name is associated with a specific gender, then that gender is assigned to that record. The CivicPulse team uses the Gender1 package available for the R statistical programming language to perform these calculations.
Of the baby names in the Social Security Administration database, at least 97% of the time, the name Bob will have the gender listed as “man”. For the officials named Bob, we will code them as “man”.
Of the baby names in the Social Security Administration database, less than 97% of the time, the name Sam will have the gender listed as “woman”. Because this is a more gender-neutral name, the algorithm will not code any official named Sam as man or woman. We are not looking up people’s names in the Social Security Administration database. That’s illegal!
What are the limitations to the name-based gender coding methodology?
This methodology has two significant limitations.
Some records are not coded. We are only able to code 92% of all local governments in our dataset of top appointed officials because the remaining 8% of records do not meet our confidence threshold.
Some records are miscoded. The records that are coded are only 97% accurate. This means 3% of records might be given the wrong gender assignment, particularly if the official identifies as nonbinary.
If you identify a record that may need updating, please use this form to submit a correction.
How do you address the fact that gender is a spectrum?
CivicPulse and ELGL both recognize that gender is a spectrum. To generate the initial gender coding, we compare the first name of each official to historical records from de-identified Social Security Administration data. Unfortunately, this methodology only provides binary gender labels. If you identify a record that may need updating—particularly if the gender label of an official is nonbinary—please use this form to submit a correction.
Are you going to expand LGDD to race, ethnicity, and age?
We are in conversation with several researchers and local government practitioners around the country on how to collect race/ethnicity and age data in a responsible and accurate way. If you’re interested in discussing this with our research team, please email us.