From Data to Diversity

The Demographics of New Jersey's Appointed Officials

Findings

Download NJ Appointed Officials Public Dataset (2022) (xlsx)

Data Findings | Process Findings

Data Findings: Demographic Representation of New Jersey’s Public Officials

This report analyzes the gender and racial/ethnic demographics of appointed officials on state boards and commissions. The findings below are from a subset of 57 boards and commissions CAWP has tracked throughout the years as part of our Bipartisan Coalition for Women’s Appointments project.4 These boards are among the most visible boards and commissions in the state, have high levels of responsibility and policymaking authority, or require financial disclosure. It is worth noting, however, that this subset was created in 2005 strictly for feasibility purposes and does not reflect a judgment on the value of the boards and commissions not included on this list. The list of boards can be found in the dataset linked above.

Additionally, it is important to note that the data below does not include the relatively high number of vacancies within these select boards and commissions that was found at the time of our data collection. Vacancies made up 13.1% of the positions on the selected boards and commissions.

Gender Diversity

Women make up just 33.1% of the appointed officials on boards included in our study. For historical context, CAWP’s 2005 study of appointees found that women made up 22% of appointees on selected boards and commissions, and by 2019, this proportion had risen to 27%. While the current data illustrates a promising trend in women’s representation on appointed boards, significant work is still needed to achieve parity.

Racial Diversity

This study provides, for the first time, data on the racial/ethnic demographics of state appointed officials. White men account for 44.6% of appointees on selected boards and commissions. According to 2021 U.S. Census population estimates, white men comprise 27% of New Jersey’s population. Not only are white men the only overrepresented group among appointees, they are substantially overrepresented relative to their share of the population.

No other group in the state achieves appointed representation exceeding or even commensurate with their population size. Asian American/Pacific Islanders and Latino women and men in New Jersey face the greatest disparities between representation in government and representation in the population. Asian American/Pacific Islanders hold under 3% of the state’s appointed offices despite comprising just over 11% of the population. Latino men and women comprise 22% of the population but are only 6% of appointees. Given that New Jersey currently has the fourth largest Asian American population and the eighth largest Hispanic population in the country5, the marked underrepresentation signals a critical need for appointing authorities to make an intentional effort to ensure that representation in the state’s governing bodies reflect the communities who reside here.

Coding for race in this project follows CAWP’s current method for race data collection. Appointees who identify as more than one race/ethnicity are included in each group with which they identify. As a result, percentages may not add up to 100% across levels.

Process Findings: Creating a Model for State Appointed Officials’ Demographic Data Collection

The findings below reflect our experience seeking appointee demographic information from all New Jersey state boards and commissions, not just the selection included in the demographic findings above. As is evident in the findings presented in this section, the process challenges we encountered in identifying and contacting all appointees explain the need to use a selected list for this report’s assessment of appointee demographic diversity. As noted below, the compounding obstacles of an unavailable centralized database of active boards, inadequate contact lists, and a low survey response rate along with lack of participation by the governor’s office meant that a full dataset was not possible. That led us to narrow our focus to the boards and commissions that we have analyzed in the past and to expand our reporting on those boards to include race as well as gender. We also needed to go beyond the legislation’s mandate and employ proxy coding – collecting data through public statements, direct contact, and other means – in addition to the survey. 

Compulsory Participation 

A low survey response rate prevented the creation of a complete or near-complete dataset, and one contributor to the low response was that appointees were not legally compelled to participate. In addition, the original version of the legislation passed by the legislature required the governor or other appointing authority to sign the request to complete the survey, thus giving the request the weight and authority of the state government. This portion of the legislation was deleted by the governor’s office in a conditional veto. While this provision did not compel appointees to participate, it did provide an endorsement of the survey that would have likely improved the response rate.

Without the full-throated endorsement of the project by the state or, ideally, compulsory participation of appointed officials, a self-report approach to collecting demographic information on appointees will yield insufficient data to fully analyze the diversity of appointed officials.

While we are grateful to the many appointed officials who replied to our survey and voluntarily provided their information, the participant survey response rate was just 20.7%. This figure only accounts for the over 2,500 appointees that we were able to contact; it does not include appointees for whom we had insufficient contact information and thus never received the survey.  

Limitations of Surveys and Need for Proxy Coding

Another limitation of the existing legislation is its reliance on a survey alone. Surveys are an excellent tool to gather information about various populations, but they also have some practical disadvantages. As noted, survey response rates are typically low, which can create flawed results when used on a finite population. Because participation was voluntary, response rates were low, and CAWP researchers had to employ expert proxy coding – collecting data through public statements, direct contact, and other means – to determine gender and racial identification of the appointees on the narrowed selection of boards reported on in the first section. Due to the size of the dataset and the absence of a master list of appointees, it was not possible to conduct proxy coding for the full population of political appointees. Demographic information determined via survey accounts for 8.9% of the dataset of selected boards (38 of the 426 appointees; figures do not include vacancies). As a result, proxy coding was employed to avoid reporting results from a limited sample that likely contains response bias. A requirement for this type of expert proxy coding was not included in the legislative language.

Proxy coding allows us to report far more extensively on the demographics of the selected boards and commissions. While proxy coding is feasible, it is both time-consuming and labor intensive. In addition, this type of coding for personal identity data increases the risk of misidentification. Self-reporting of gender and racial identity is preferred.

Contact Lists

Another major challenge to collecting demographic information on appointees was the dearth of contact information for appointees that was both readily available and in a uniform style. During the course of this study, we ran into several roadblocks in getting contact information for state appointees, including not being able to get a comprehensive list of currently active boards. We found via outreach to the governor’s appointments office that there is no centralized database of state appointees or at least none that could be provided to researchers. We then turned to the state’s publicly available Boards, Commissions, and Authorities Directory. This directory includes 473 boards (excluding county election boards). However, we found that 94 of those 473 boards are inactive. We also utilized the Fitzgerald’s New Jersey Legislative Manual, which includes a list of operational and study boards and commissions. This source helped to fill information gaps but also includes neither a fully comprehensive list of current boards, commissions, and authorities nor contact information for their members.

Additionally, due to changes in the legislation during the conditional veto, the state administration was not required to provide us with contact information for the state’s appointees. The governor’s appointments office instead connected us with state department heads for board membership and contact information for the boards and commissions that fall under each department’s purview. We conducted outreach to each department contact during the spring and summer of 2022; the list of board members used for this study is as of that time period. The process of following up with each state department and assembling a full contact list was laborious and time-consuming; it took several months to pull together the contact lists into one dataset. Unfortunately, because of the decentralized process, the lists had different types of contact information, and there were gaps in available information. Department heads also sent information on boards that were not included in the public state directory. Additionally, CAWP was unable to obtain any contact information for 156 boards listed on the public state directory because they either did not fall under any department’s purview or we could not find staff members to provide the information. In addition, of the over 3,000 board members that we were able to compile, 702 did not have sufficient contact information


4 The original Bipartisan Coalition for Women’s Appointments list of boards and commissions included 63 boards; only 57 of those boards are currently active.
5 U.S. Census Bureau. "Selected Population Profile in the United States." American Community Survey, ACS 1-Year Estimates Selected Population Profiles, Table S0201, 2022, https://data.census.gov/table/ACSSPP1Y2022.S0201?q=S0201&g=010XX00US,$0…. Accessed on October 20, 2023.