Methodology

Terminology

The District Readiness Index displays scores for three different levels of data. Indicator scores are used to calculate Domain Ratings, which are then used to generate a District Readiness Rating.

1. Indicator Scores:

There are 30 quantitative and qualitative measures collected for each school district. Each measure was converted into “indicators” on a two-point scale that were used to calculate Domain Ratings. Indicators can receive a Yes, Some, or No response. “Yes” responses earn the district 2 points; “Some” responses earn the district 1 point; and “No” responses earn the district 0 points. Learn more about each of these measures and our calculations below.

2. Domain Rating: 

These 30 indicators were then compiled to calculate each district’s 5 Domain Ratings:

• Family & Community Engagement
• Financial Management
• Leadership & Governance
• School Personnel
• Work Environment

For each domain, a district can earn one of the following Domain Ratings:

• Strong Foundations: ≥70% of Indicator points possible
• Partial Foundations: 50-69.99% of Indicator points possible
• Few Foundations: <50% of Indicator points possible

You can learn more about how districts earned their Domain Ratings below.

3. District Readiness Rating: 

Domain Ratings were then aggregated to generate overall District Readiness ratings.

• Strong Foundations to Improve Education
• Partial Foundations to Improve Education
• Few Foundations to Improve Education

About the DRI District Sample

For the DRI’s initial iteration, the database only includes traditional Elementary, Unified, and High School Districts. The DRI does not include: 

• Districts with student enrollment under 2,500
• Charter schools
• County Offices of Education
• Private schools
• Unique Local Educational Agencies (e.g., State Special Schools; Regional Occupation Center)

The 2,500 enrollment threshold was used to focus on a manageable data collection scope, and because school districts with enrollments below this threshold yielded enough one-school districts to distort indicator collection procedures.

Calculating Domain Ratings

The District Readiness Index compiles 30 measures across five domains to help education leaders across California better understand the conditions for launching and sustaining improvement and innovation initiatives. It does this by bringing together quantitative and qualitative information into meaningful Domain Ratings across the five domains, and then aggregating those Domain Ratings into an overall District Readiness rating. In this section, you will learn more about Pivot Learning’s process for generating Domain Ratings.

Researchers began by reviewing other tools’ procedures about how to reduce lots of information into a meaningful rating. In California, the Fiscal Crisis & Management Assistance Team (FCMAT) uses a Fiscal Health Risk Analysis protocol for school districts to assess their evidence of potential future fiscal insolvency. Their protocol reduces indicators of districts’ internal financial systems, practices, and processes into “Yes/No” questions that district leaders answer and then tally to calculate their level of risk. This method offers an intuitive way to easily reduce lots of complex information.

Building on FCMAT’s methodology, researchers reduced each domain’s indicator into affirmative statements that would be associated with greater district readiness to scale innovations and improve educational outcomes. Affirmative statements were designed around meaningful thresholds found either in the literature or through review of the collected data. Unlike FCMAT, each indicator was worth 2 points with three possible responses: a “Yes” response earned 2 points; a “Some” response earned 1 point; and a “No” response earned 0 points. 

However, research and practice suggests that some indicators are more central to and are better measures of the relevant domain. Further, indicators within a domain are ordered according to their importance. Following Great Schools’s methodology, the tool cardinally ranks each indicator with 1 or 2 points wherein indicators with substantial support in the literature and from experts and experience are attributed 2x weight and all other indicators are weighted at 1x. 

After weighting each indicator, researchers then summed the weighted responses to calculate the total number of points earned by a school district. The total number of points will vary not only by what a district “earned” but also by missingness (see more below). To calculate comparable measures, researchers also calculated the total number of points possible per domain by summing the weighted points of indicators with available information. Finally, researchers divided the total number of points earned by the total number of points possible to calculate domain-specific Percent Points Earned scores. Iterative reviews of the distributions were then reviewed by researchers to identify the final cutoffs for the Domain Ratings which are outlined below in Table 1.

Table 1: Criteria for Domain Rating

Rating	Criteria
Strong Foundations	≥70% of points possible
Partial Foundations	50-69.99% of points possible
Few Foundations	<50% of points possible

Importantly, missingness is always a concern in calculating composite measures. Other ratings systems drop cases with a single instance of missing data or measures with substantial missingness, or impute values in the empty cell. To avoid penalizing or rewarding districts for missing data, researchers remove the weighted points from both the total points earned and total points possible. Thus, Percent Points Earned for districts with missing data is calculated by dividing the total number of points earned by the available points possible. Information about data missingness can be found in the Full Report on California district readiness.

An example will help illustrate this approach. Research and experience points to the importance of consistent and supported district leaders to oversee initiatives over time. Thus, researchers looked for ways to measure different components of Leadership and Governance. One key measure of consistent leadership is superintendent turnover. Superintendent turnover was calculated by adding the total number of superintendents hired by a school district over seven years (see description for how superintendent turnover data was collected for more information). Research based on nationally representative samples of superintendents shows that the average superintendent’s tenure is between three and four years (Chingos et al., 2014). Review of the data collected by Pivot Learning also illustrated that very few districts hired more than three superintendents during the observation period. 

Based on this information, the data were “asked” whether the district:

• Hired two or fewer superintendents?
• Hired three or fewer superintendents?

If the district “answered” “Yes” to both questions, it earned 2 points. If it answered “Yes” only to the second question (three or fewer superintendents), it earned 1 point. If the district “answered” “No” to both questions, it earned 0 points.

Because superintendent tenure is an especially important characteristic in the research and practitioners’ experience, it was weighted twice as much as other indicators within the domain. District’s points were multiplied by two for their final “score” on this measure.

This process was repeated for every indicator within each domain. The points were then summed to calculate the total points earned by the district. The total number of points possible were then calculated by summing together the weighted available points for measures in which the district was not missing information. Finally, the total points earned were divided by the total number of points possible to calculate the percentage of points earned for the Leadership & Governance domain. The thresholds identified in Table 1 were then used to categorize the district as  having “Strong Foundations,” “Partial Foundations,” or “Few Foundations” on this domain.

By drawing from available resources in creative ways, the tool shows easily interpretable and meaningful domain-level readiness ratings that can be compared across several districts across California.

District Readiness Rating

Alongside the five domains’ Readiness ratings, the DRI generates a summative District Readiness rating for districts in the DRI sample. The District Readiness rating allows users to compare school districts’ organizational conditions both to important research- and experienced-based conditions and to other districts across the state. 

District Readiness ratings are generated based on the total number of a district’s “Strong Foundations” Domain Ratings. Each District Readiness Rating’s criteria can be found below in Table 2.

Table 2: District Readiness Rating Criteria

Rating	Criteria
Strong Foundations to Improve Education	1. Strong Foundations in at least 4 domains AND 2. Few Foundations in 0 domains
Partial Foundations to Improve Education	1. Strong Foundations in 3 or fewer domains  AND  2. Few Foundations in 1 or fewer domains
Few Foundations to Improve Education	1. Few Foundations in 2 or more domains

More information about the overall distribution of district readiness across California can be found in the Companion Report.

Family & Community Engagement

Posts a recent budget to its website

Research and experience show that greater family and community engagement in their local education in part requires access to information about their school district’s practices and policies (Mapp & Kuttner, 2014). Although Parental Involvement is a statewide educational priority area, Local Education Agencies often do not provide adequate or equitable support for parents to access, interpret, and engage with this important information (Cottingham, 2020). Posting adopted budgets online is one important way that local educators can share this information with the community.

Data for this indicator were collected between May 2021 and September 2021. A team of researchers collected the school districts’ 2020-21 adopted budgets as available on their or the parent county office of education’s website. Researchers also looked for and collected alternate budget materials. Districts with found adopted budgets were coded as 2; districts without budgets or with only alternate budget materials were coded as 0.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 1. Points earned by the district for this indicator were multiplied by one before summing the total points earned in the domain. More information about the rating process can be found in Calculating Domain Ratings.

Family and community involvement in decision-making

Research and experience show that opportunities for collaborative decision-making between educators, families, and the community is a critical aspect of developing and strengthening relationships (Ishimaru, 2019) and promoting greater involvement in local educational affairs (Ishimaru, 2014; Marsh & Hall, 2018). 

Data for this indicator were collected in August 2021 from the California Department of Education’s 2019 Local Control and Accountability Plan Priority 3 survey responses. The CDE also publishes this information for each school district on the California School Dashboard. In these surveys, the California Department of Education asks school districts to “rate the LEA’s progress in providing opportunities to have families, teachers, principals, and district administrators work together to plan, design, implement, and evaluate family engagement activities at school and district levels.” Districts were given five options corresponding with ascending levels of implementation:

• 1= Exploration and Research Phase
• 2= Beginning Development
• 3= Initial Implementation
• 4= Full Implementation
• 5= Full Implementation and Sustainability

For the DRI, districts that responded with “Full Implementation” and above are coded as 2; districts that responded with “Initial Implementation” as 1; and districts that responded with “Beginning Development” and below as 0. All districts that did not submit usable data before database publication are coded as Missing. 

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 2. Points earned by the district for this indicator were multiplied by two before summing the total points earned in the domain. More information about the rating process can be found in Calculating Domain Ratings.

Opportunities for two-way communication with families

Research and experience show that a key barrier to greater engagement with families and communities is untranslated and difficult-to-understand language (Marsh, 2007; Marsh et al., 2015). Moreover, families’ competing obligations require varied entry points for communicating with educators (Posey-Maddox & Haley-Lock, 2016). When educators and families regularly communicate with each other, they can better understand each other’s needs to support students (Baker et al., 2016).

Data for this indicator were collected in August 2021 from the California Department of Education’s 2019 Local Control and Accountability Plan Priority 3 survey responses. The CDE also publishes this information for each school district on the California School Dashboard. In these surveys, the California Department of Education asks school districts to “rate the LEA’s progress in developing multiple opportunities for the LEA and school sites to engage in two-way communication between families and educators using language that is understandable and accessible to families.” Districts were given five options corresponding with ascending levels of implementation:

• 1= Exploration and Research Phase
• 2= Beginning Development
• 3= Initial Implementation
• 4= Full Implementation
• 5= Full Implementation and Sustainability

For the DRI, districts that responded with “Full Implementation” and above were coded as 2; districts that responded with “Initial Implementation” as 1; and districts that responded with “Beginning Development” and below as 0. All districts that did not submit usable data before database publication were coded as Missing.  

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 2. Points earned by the district for this indicator were multiplied by two before summing the total points earned in the domain. More information about the rating process can be found in Calculating Domain Ratings.

Readiness to develop relationships with families

Research and experience show that educators can play an important role in laying the groundwork for trusting and respectful relationships with the families they serve (Auerbach, 2010; Ishimaru, 2013). These kinds of relationships can help educators replace deficit approaches to families’ capacities (Baquedano-Lopez et al., 2013) with a view that values the assets they bring to their children’s education (Mapp & Kuttner, 2014). 

Data for this indicator were collected in August 2021 from the California Department of Education’s 2019 Local Control and Accountability Plan Priority 3 survey responses. The CDE also publishes this information for each school district on the California School Dashboard. In these surveys, the California Department of Education asks school districts to “rate the LEA’s progress in developing the capacity of staff (i.e., administrators, teachers, and classified staff) to build trusting and respectful relationships with families.” Districts were given five options corresponding with ascending levels of implementation:

• 1= Exploration and Research Phase
• 2= Beginning Development
• 3= Initial Implementation
• 4= Full Implementation
• 5= Full Implementation and Sustainability

For the DRI, districts that responded with “Full Implementation” and above were coded as 2; districts that responded with “Initial Implementation” as 1; and districts that responded with “Beginning Development” and below as 0. All districts that did not submit usable data before database publication were coded as Missing.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 2. Points earned by the district for this indicator were multiplied by two before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Created a student member seat on its board of education

Research and experience show that an important first step in including students in a school district’s reform process is to give students the right to speak for themselves about their educational experiences, and the opportunity to be heard by those in places of power (Feuer & Mayer, 2009). California Education Code (section 35012) states that at school districts where there are one or more high schools, students may submit a petition to the Board of Education requesting that they appoint one or more student members to the board.

Data for this indicator were collected between May 2021 and September 2021. A team of researchers reviewed the websites of school districts with at least one operating high school for evidence about policies regarding student membership on the Board of Education or Board of Trustees. Next, researchers located and reviewed the Board’s Governance Policies for bylaws requiring student board members. Districts with policies that created a standing student member seat on the board of education were coded as 2; districts with bylaws stipulating that students could petition for a seat on the Board were coded as 1; districts with no evidence of bylaws outlining how student members could be seated were coded as 0. School districts that did not currently operate at least one high school were coded as Missing.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 1. Points earned by the district for this indicator were multiplied by one before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Publishes a translated Budget Overview for Parents

Research and experience show that a key barrier to greater engagement with families and communities is untranslated and difficult-to-understand language (Marsh, 2007; Marsh et al., 2015). Providing translated documents about educational practices and decisions like the Budget Overview for Parents meets basic statutory mandates for California education (Education Code Section 48985) and creates valuable opportunities to engage often marginalized families (Mapp & Kuttner, 2014).  

Data for this indicator were collected between May 2021 and September 2021. California Education Code Section 48985 requires school districts that enroll 15% or more students whose first language is not English to translate parental notifications into that language. A team of researchers reviewed school districts’ websites for the 2019-20 Local Control and Accountability Plan and the Local Control Funding Formula Budget Overview for Parents (BOP). Once relevant materials were collected, researchers coded whether the school district provided a translated BOP. If school districts met the threshold for any student group and they provided a translated BOP, they were coded as 2; if districts did not enroll a student group that met the language threshold but still published a translated BOP, they also were coded as 2. If a school district enrolled a student group that met the language threshold but did not publish a translated BOP, they were coded as 0. Districts that did not enroll a student group that met the language threshold and did not publish a translated BOP were coded as Missing.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 1. Points earned by the district for this indicator were multiplied by one before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Financial Management

Spends a smaller share of the budget than the average DRI school district on benefits

Research and experience show that, although school districts may try to attract teachers by spending more on benefits (Bruno, 2019), these expenditures direct a district’s finite resources away from direct classroom spending (Marchitello et al., 2018). Although districts’ pension contributions are fixed by the state, districts typically have greater say over how to spend on other benefits, like healthcare benefits. Spending a relatively small share of the district’s budget on benefits can be a marker of sound financial practices.

Data for this indicator were collected in August 2021 from the 2019-20 California Department of Education’s Standardized Account Code Structure (SACS) Annual Unaudited Actual finances database. First, the dataset was limited to only expenditures (Object Codes < 7600). Then, Total Expenditures were calculated by summing all Values from the General Funds (Fund==01) except CalSTRS on-behalf payments (Resource Code==7690). Separately, the total amount of spending on benefits was calculated by summing all Values for Employee Benefits (Object Codes = 3000-3999). Finally, % Budget Spent on Benefits was calculated by dividing the Total Spent on Employee Benefits by the Total Expenditures then multiplied by 100. Districts that spent less than one standard deviation below the sample’s mean on benefits were coded as 2; districts that spent between one standard deviation below and above the sample’s mean were coded as 1; and districts that spent one standard deviation above the sample’s mean were coded as 0.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 1. Points earned by the district for this indicator were multiplied by one before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Spends a smaller share of the budget than the average DRI school district on its central office

Research and experience show that although the share of central office expenditures often vary by district size and accounting practices (Legislative Analyst’s Office, 2011), educators and advocates tend to look toward – and have more flexibility in – reducing spending on central district office expenditures to manage local finances. This is an especially fertile area for fiscal management after the number of central office administrators has grown significantly over the last two decades (Stoll, 2020). 

Data for this indicator were collected in August 2021 from the 2019-20 California Department of Education’s Standardized Account Code Structure (SACS) Annual Unaudited Actual finances database. First, the dataset was limited to only expenditures (Object Codes < 7600). Then, Total Expenditures were calculated by summing all Values from the General Funds (Fund==01) except CalSTRS on-behalf payments (Resource Code==7690). Separately, the total amount of spending on the central office was calculated by summing all Values for General Administration (Function Codes = 7000-7999). Finally, % Budget Spent on Central Office was calculated by dividing the Total Spent on Central Office by the Total Expenditures then multiplied by 100. Districts that spent less than one standard deviation below the sample’s mean on the central office were coded as 2; districts that spent between one standard deviation below and above the sample’s mean were coded as 1; and districts that spent one standard deviation above the sample’s mean were coded as 0.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 1. Points earned by the district for this indicator were multiplied by one before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Enrollments declined less than the average DRI school district over the last 10 years

Research and experience show that declines in enrollments force school districts to try to quickly scale down services with fewer on-hand resources to varying degrees of success, often precipitating financial strain (Warren & Lafortune, 2020).

Data for this indicator were collected in August 2021 from the California Department of Education’s Census Day Enrollment databases. Data from the 2010-11 and 2020-21 school years were downloaded. Each dataset was grouped by the seven-digit County-District Codes and then its total number of students were summed for Total Census Day Enrollment. The Percentage Change in Enrollment was then calculated using the following formula:

[(Total 2020-21 Enrollment – Total 2010-11 Enrollment)/(Total 2010-11 Enrollment)]*100.  

Districts that experienced enrollment changes greater than one standard deviation above the sample’s mean were coded as 2; districts that experienced enrollment changes that were within one standard deviation above and below the sample’s mean were coded as 1; and districts that experienced enrollment changes one standard deviation below the sample’s mean were coded as 0.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 2. Points earned by the district for this indicator were multiplied by two before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Caps employees’ and retirees’ healthcare benefits spending

Research and experience show that rising healthcare costs account for increasing proportions of districts’ budgets (Marchitello, 2018) that can create financial strain on school districts. Conversely, limiting spending on healthcare benefits can help districts apply savings toward additional innovative solutions and other instructional programs (Melnicoe et al., 2019). 

Data for this indicator were collected between May 2021 and September 2021. First, a team of researchers collected the school districts’ 2020-21 budgets as available on their or the parent county office of education’s website. Data associates then reviewed the district budget for the Criteria and Standards Review section. If found, they then searched for Section A6, “Additional Fiscal Indicators.” In this section, districts were asked to answer “Does the district provide uncapped (100% employer paid) health benefits for current or retired employees?” District “Yes/No” responses were coded as 0 for “Yes” and 2 for “No.” If a district’s budget could not be found or it was missing the Criteria and Standards Review section, the response was coded as Missing.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 1. Points earned by the district for this indicator were multiplied by one before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Does not cover retirees’ lifetime health benefits

Research and experience show that, as aging cohorts of retirees’ healthcare costs increase, school districts can struggle to meet “substantial long-term debt commitments” like promised benefits alongside their current costs (FCMAT, 2004; Melnicoe et al., 2019; Perry et al., 2007). These obligations often limit the amount of money available for innovative programs that can sustain improvements in educational outcomes.

Data for this indicator were collected in August 2021 from the California Department of Education’s Certificated Salaries and Benefits database. From the TSAL120 table, researchers limited the database to district responses for Ben_Life. This column lists responses to the J-90 form to the question “Does district cover retirees for life?” Districts who responded “No” were coded as 2, whereas districts who responded “Yes” were coded as 0. Districts without responses were coded as Missing.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 1. Points earned by the district for this indicator were multiplied by one before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

One or fewer qualified budget certifications in the last five years

Research and experience show that an important predictor of future financial uncertainty is prior financial concern (EdSource/School Services of California, 2006). As the California Department of Education explains, “a qualified certification is assigned [for a district’s budget] when the district may not meet its financial obligations for the current or two subsequent fiscal years” based on current projections. When districts predict they may not be able to meet their financial obligations, they may need to make financial adjustments and will likely have less flexibility to invest in innovative solutions (Burns et al., 2016). 

Data for this indicator were collected between May 2021 and September 2021 from the California Department of Education’s Certifications of Interim Financial Reports. Researchers first collected the biannual first and second Interim reports for each school year from 2015-16 to 2019-20. Each report lists districts that have been given Negative Certifications or Qualified Certifications for the reporting period. Researchers transcribed these certifications for each of the 10 reports. The Total Number of Qualified Certifications was then calculated by summing across the 10 reports that were coded as “Qualified.” Districts with no Qualified Certifications over the 10 reports were coded as 2; districts with one Qualified Certification were coded as 1; and districts with two or more Qualified Certifications were coded as 0.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 2. Points earned by the district for this indicator were multiplied by two before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

No negative budget certifications in the last five years

Research and experience show that an important predictor of future financial uncertainty is prior financial concern (EdSource/School Services of California, 2006). As the California Department of Education explains, “a negative certification is assigned [to a district’s budget] when a district will be unable to meet its financial obligations for the remainder of the current year or for the subsequent fiscal year” based on current projections. When districts predict they will be in such a dire financial situation, they will need to make significant cuts to remain financially sound and therefore will be unable to invest in innovative solutions (Burns et al., 2016).

Data for this indicator were collected between May 2021 and September 2021 from the California Department of Education’s Certifications of Interim Financial Reports. Researchers first collected the first and second Interim reports for each school year from 2015-16 to 2019-20. Each report lists districts that have been given Negative Certifications or Qualified Certifications for the reporting period. Researchers transcribed these certifications for each of the 10 reports. The Total Number of Negative Certifications was then calculated by summing across the 10 reports that were coded as “Negative.” Districts with no Negative Certifications over the 10 reports were coded as 2 and districts with one or more Negative Certifications were coded as 0.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 2. Points earned by the district for this indicator were multiplied by two before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Maintains financial reserves

Research and experience show that maintaining resource reserves to withstand unanticipated costs or changes that can affect expenditures is a hallmark of strong financial management practices (EdSource/School Services of California, 2006). Districts that do not maintain resource reserves may already be facing financial challenges that require them to spend below the statutorily mandated level or may leave the district open to future potential issues (Legislative Analyst’s Office, 2015).

Data for this indicator were collected between May 2021 and September 2021. First, a team of researchers collected the school districts’ 2020-21 budgets as available on their or the parent county office of education’s website. Data associates then reviewed the district budget for the Criteria and Standards Review section. If found, they then searched for Section 10D, “Comparison of District Reserve Amount to the Standard.” In this section, districts were asked to record whether their current financial reserves met the statutorily required standard based on their Average Daily Attendance. Districts that responded “Standard Met” were coded as 2, whereas districts that responded “Standard Not Met” were coded as 0. If a district’s budget could not be found or it was missing the Criteria and Standards Review section, the response was coded as Missing.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 2. Points earned by the district for this indicator were multiplied by two before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Leadership & Governance

No attempted or successful school board recalls in the last five years

Research and experience show that school boards of education that face attempted or successful school board recalls are more likely to face disruptions that forestall efforts to focus on a shared mission, especially in an era of political polarization (Ramanthan, 2022).

Data for this indicator were collected in March 2022 from Ballotpedia’s List of Recall Efforts. Recall attempts and successes for each year between 2016 and 2021 in California were collated in a central database. School districts with any attempted or successful recall during the observation period were then coded as 0; all other school districts were coded as 2. 

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 2. Points earned by the district for this indicator were multiplied by two before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Adopted a superintendent performance review policy

Research and experience show that school boards of education often conduct relatively informal, subjective evaluations that do little for promoting the superintendent’s personal and the local educational system’s growth (DiPaola, 2007). When school boards adopt clear policies guiding their end-of-year evaluation of superintendents, they are in a better position to more objectively evaluate their leadership’s progress toward their shared educational mission.  

Data for this indicator were collected between May 2021 and September 2021. A team of researchers reviewed school districts’ websites for the Board’s Governance Policies. Researchers then reviewed the Administration subsection for policies pertaining to superintendent evaluation. Typically this subsection was entitled “Evaluation of the Superintendent.” Districts with an adopted superintendent evaluation policy were coded as 2; districts with no evidence of such a policy were coded as 0. 

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 1. Points earned by the district for this indicator were multiplied by one before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Two or fewer superintendents between SY 2012-13 and 2018-19

Research and experience show that although superintendents may not have especially strong direct impacts on student achievement, (Chingos et al., 2014; Myers, 2011) they play an important role in setting an agenda for education (Alsbury, 2008). Districts that predominantly serve historically disadvantaged student groups that yield exceptionally high student performance are especially likely to benefit from stable leadership (Burns et al., 2019). 

Data for this indicator were collected in January 2022 from the California Department of Education’s Staff Assignment data from the Staff Assignment and Course databases. Good superintendent data is notoriously lacking (Sawachuk, 2021), but California’s adoption of the Local Control Funding Formula brought with it improvements to its data collection processes. One change includes using a uniquely identifiable Record ID for each employee to track their movement over time. Publicly accessible annual Staff Assignment data between 2012-13 and 2018-19 were first downloaded. Each year’s database was limited to the Staff Assignment code for superintendents (Assignment Code==0100). After cleaning these data, researchers then merged the annual sets into a longitudinal database. 

The database was then reviewed for completeness; districts with at least one record for a superintendent each year were identified as complete (n = 259). Districts with incomplete records were then identified for further review (n = 165). A team of researchers explored district websites, board of education meeting notes, and local digital newspapers for information about the superintendents the district hired during the observation period. Districts still missing information about their superintendents were then contacted to share information about the superintendents they hired during the observation period. 

Once complete records were collected for each school district, researchers calculated the number of unique superintendents the district reported between 2012-13 and 2018-19. Analyses using nationally representative samples estimate superintendents on average stay in the position for between three and four years at a given school district (Chingos et al., 2014). Given the seven-year observation period, districts that hired two or fewer superintendents during it were coded as 2; districts with three superintendents were coded as 1; districts with four or more superintendents were coded as 0. 

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 2. Points earned by the district for this indicator were multiplied by two before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Bonus: Board of education adopted an equity policy

Research and experience show that equity policies are a useful marker of a school district’s commitment to closing historic opportunity gaps. Equity policies are associated with improved overall student outcomes and reducing some student groups’ test score gaps, like between Hispanic and white students (Kim, 2020). However, equity policies are relatively recent additions to school board practices and they may not have specific accountability mechanisms tied to them that encourage particular practices or systems that support students.

Data for this indicator were collected between May 2021 and September 2021. A team of researchers reviewed school districts’ websites for the Board’s Governance Policies. Once located, they then reviewed the “Philosophy, Goals, Objectives, and Comprehensive Plans” section to locate an “Equity” subsection or an “Equity Policy.” Non-discrimination policies were not considered. Districts that adopted an equity policy were coded as 2; districts without an adopted equity policy were coded as 0.

Because the tool treats this indicator as a signal but not one foundational to districts, it includes points from this measure as a “bonus” for districts. Researchers weighted this indicator at 1 for districts that adopted an equity policy. Points earned by the district for this indicator were multiplied by one before summing the total points earned for the Domain Rating. To avoid penalizing districts for not adopting an equity policy, the tool does not include the points available for this indicator into the total points possible. More information about the rating process can be found in Calculating Domain Ratings.

School Personnel

Employs 90% or more teachers with three or more years teaching experience

Research and experience show that students, especially African American and Hispanic ones (Podolsky et al., 2019), gain more from a substantially experienced teacher workforce (Carver-Thomas et al., 2020). Moreover, additional experienced teachers tend to benefit not just their classrooms but the school as a whole (Kini & Podolsky, 2016) as teachers support one another to improve their and each other’s practice.

Data for this indicator were collected in June 2021 from the California Department of Education’s Staff Demographic database. Researchers downloaded the 2018-19 file. Following Ed-Data, they included any case where the full-time equivalency teaching (“FTE Teaching”) was coded as greater than 0. To calculate the total number of teachers in the district, they grouped by the County-District Code and then summed the total number of cases. “Experienced Teachers” is defined as teachers with three or more years teaching (“YearsTeaching”). They then calculated Experienced Teachers separately by summing the total number of teachers where “YearsTeaching” was greater than or equal to three. 

Researchers then used the following formula to calculate the percentage of Experienced Teachers:

[Total # of Experienced Teachers / Total # of Teachers] * 100. 

Distributions of the share of experienced teachers were then iteratively reviewed for important cutoff points. Districts with experienced teaching staffs greater than or equal to 90% were coded as 2; districts with experienced teaching staffs greater than or equal to 80% but less than 89.9% were coded as 1; districts with experienced teaching staffs less than or equal to 79.9% were coded as 0.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 1. Points earned by the district for this indicator were multiplied by one before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Employs 95% or more teachers with full credentials

Research and experience show that districts in which students outperformed their peers employ fewer teachers on substandard credentials and permits than the state average (Carver-Thomas et al., 2020). These impacts are especially felt by African American and Latino/a students who often are systematically taught by teachers with the weakest credentials (Carver-Thomas et al., 2020). Ensuring classrooms are taught by fully credentialed staff is an important baseline for executing a shared educational program.

Data for this indicator were collected in June 2021 from the California Department of Education’s Staff Credential data in the Staff Demographic database. Researchers downloaded the 2018-19 file. This database lists all credentials that staff members hold as reported on Information Day. Researchers first limited the database to one case per Record ID and then grouped by the County-District Code and summed the total number of cases. “Fully Credentialed” was defined as any teacher who was assigned greater than 0 FTE status and reported they earned a full credential. They then calculated the total number of Fully Credentialed Teachers separately by summing the total number of teachers where “CredentialType” was equal to 10. 

Researchers then used the following formula to calculate the percentage of Fully Credentialed Teachers:

[Total # of Credentialed Teachers / Total # of Teachers] * 100. 

Distributions of the share of fully credentialed teachers were then iteratively reviewed for substantive cutoff points. Districts with fully credentialed teaching staffs greater than or equal to 95% were coded as 2; districts with fully credentialed teaching staffs greater than or equal to 90% but less than 94.9% were coded as 1; districts with fully credentialed teaching staffs less than or equal to 89.9% were coded as 0.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 1. Points earned by the district for this indicator were multiplied by one before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Principal retention rate greater than or equal to the national average

Research and experience show that principals play an important role in rolling out educational programs (Gates et al., 2019). Their turnover is often associated with significant declines in student achievement for at least two years after they leave their school (Miller, 2013). Conversely, principals who stay at their schools each year can apply their leadership skills on guiding their staff toward fulfilling their shared mission (Grissom et al., 2021).

Data for this indicator were collected in June 2021 from the California Department of Education’s 2017-18 and 2018-19 Staff Assignment data files collected through the California Longitudinal Pupil Data System (CALPADS). Following Grissom and Bartanen (2018), the school district’s annual principal retention rate is calculated by dividing the number of principals in a district who remain at the same school from the 2017-18 to 2018-19 school year by the total number of operational schools in the 2018-19 school year. 

After collecting both waves of data, researchers then filtered for all individual records identified as principal using the CALPADS coding system (“AssignmentCode” = 301). The 2017-18 and 2018-19 waves were appended together to create a longitudinal database. From there, each school was coded with a duplicate individual Record ID between the two years as 1 for “stayers” and 0 otherwise. The number of stayers in the school district was then counted. Finally, researchers divided by the total number of schools operating in the school district in the 2018-19 school year.

California education’s limited data systems may raise questions about the reliability of such an approach (Phillips, Reber, & Rothstein, 2018). Researchers made several adjustments to increase confidence in the methodology. Because closed schools typically suspend operations in June of a given academic year (69.2%; author’s calculations using CDE Public Schools database), schools that were opened before or closed after May 2019 were omitted from the database. The database also restricts active schools to the categories in line with Ed-Data; Preschools and Adult Education Centers were thus from the data. To check for reliability, researchers compared calculations for the number of active schools in the database’s districts to the number of schools in operation as measured by Ed-Data.

Districts with a principal retention rate greater than or equal to the national average (78%) were coded as 2; districts with a principal retention rate greater than or equal to 50% but less than 77.9% were coded as 1; districts with a principal retention rate less than 49.9% were coded as 0.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 2. Points earned by the district for this indicator were multiplied by two before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Inexperienced teachers are not concentrated in high-need schools

Research and experience show that difficult-to-staff schools are typically staffed by a greater share of inexperienced teachers (Sutcher et al., 2019). Teachers with less classroom experience are less likely to possess important skills to teach students. Because these teachers are often concentrated in schools with greater shares of low-income students and Black and Latino/a students, inaccessibility to experienced teachers can widen achievement gaps (Knight, 2019; Peske & Haycock, 2006). When school districts equitably distribute experienced teachers to their high-need schools, they help ensure students receive the support they need to succeed.

Data for this indicator were collected in June 2021 from the California Department of Education’s Staff Demographic, Staff Assignment data from the Staff Assignment and Course, and CALPADS Unduplicated Pupil Count (UPC) Source File databases. Researchers downloaded the 2018-19 files for each set. Following Ed-Data, they included any case in the Staff Demographic data where the full-time equivalency teaching (“FTE Teaching”) was coded as greater than 0. They then merged the Staff Demographic with Staff Assignment databases to identify in which school each teacher taught. To calculate the total number of teachers in each school, they then grouped by the County-District-School Code before summing the total number of cases. Following the Learning Policy Institute (2019), “Experienced Teachers” were defined as teachers with three or more years teaching (“YearsTeaching”). “Inexperienced Teachers” were calculated separately by summing the total number of teachers where “YearsTeaching” was less than or equal to two. 

Following the Learning Policy Institute, the researchers identified high- and low-needs schools by percentage of Unduplicated Pupils served by each school. Researchers calculated this metric by dividing the total number of Unduplicated Pupils by the total number of enrolled students in the UPC Source File. Grouped by the County-District Code, the researchers then divided the schools into quartiles by percentage of Unduplicated Pupils. Low-needs schools were identified as enrolling shares of unduplicated pupils in the bottom 25% of the school district’s unduplicated pupil percentages; high-need schools enrolled shares of unduplicated pupils in the top 25% of the school district’s unduplicated pupil percentages.

Researchers then merged the school student-need quartile classifications with the teacher experience databases. The following formula was used to calculate the share of inexperienced teachers in high-need schools:

[Total # of Inexperienced Teachers_High-Need / Total # of Teachers_High-Need] * 100. 

This procedure was repeated to calculate the share of inexperienced teachers in low-needs schools.

Once these shares were calculated, researchers calculated a ratio of teacher inexperience using the following formula:

% Inexperienced Teachers_High-Need / % Inexperienced Teachers_Low-Need.

Ratios closer to 0 reflect a lower concentration of inexperienced teachers in high-need schools. Ratios equal 1 in districts where the share of inexperienced teachers is identical in high- and low-needs schools. Where school districts concentrate twice as many inexperienced teachers in high-need schools versus low-needs schools, the ratio will be 2.

Districts with ratios of inexperienced teachers less than 1 are coded as 2; districts with inexperienced teaching staffs greater than or equal to 1 but less than 1.99 are coded as 1; districts with ratios of inexperienced teachers greater than or equal to 2 are coded 0. Districts with fewer than four schools or missing other information to calculate this measure were coded as Missing.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 1. Points earned by the district for this indicator were multiplied by one before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Uncredentialed teachers are not concentrated in high-need schools

Research and experience show that teachers with less than full credentials are not equitably distributed throughout the state’s schools and are typically concentrated in urban areas with large shares of low-income and African American and Hispanic students (Darling-Hammond, 2004). These students’ outcomes are especially harmed when taught by teachers who do not receive important training for skills acquired through a credentialing program (Podolsky et al., 2019). When school districts do not concentrate their teachers with less than full credentials in schools with lots of high–needs students, they help promote a smoother rollout of programs that can support educational improvements.

Data for this indicator were collected in June 2021 from the California Department of Education’s Staff Demographic, Staff Assignment data from the Staff Assignment and Course, and CALPADS Unduplicated Pupil Count (UPC) Source File databases. Researchers downloaded the 2018-19 files for each set. The Staff Demographic database lists all credentials that staff members hold as reported on Information Day. Researchers first limited the database to one case per Record ID and then grouped by the County-District Code and summed the total number of cases. “Fully Credentialed” was defined as any teacher who was assigned greater than 0 FTE status and reported they earned a full credential. They then merged the Staff Demographic with Staff Assignment databases to identify in which school each teacher taught. To calculate the total number of teachers in each school, they then grouped by the County-District-School Code and then summed the total number of cases. Following the Learning Policy Institute (2019), “Uncredentialed Teachers” were defined as teachers who have not met all requirements for at least one credential. They then calculated Uncredentialed Teachers separately by summing the total number of teachers where CredentialType was not equal to 10. 

Following the Learning Policy Institute, the researchers identified high- and low-needs schools by the percentage of Unduplicated Pupils served by each school. Researchers calculated this metric by dividing the total number of Unduplicated Pupils by the total number of enrolled students in the UPC Source File. Grouped by the County-District Code, the researchers then divided the schools into quartiles by percentage of Unduplicated Pupils. Low-needs schools were identified as enrolling shares of unduplicated pupils in the bottom 25% of the school district’s unduplicated pupil percentages; high-need schools enrolled shares of unduplicated pupils in the top 25% of the school district’s unduplicated pupil percentages.

Researchers then merged the school student-need quartile classifications with the teacher credentialing databases. The following formula was used to calculate the share of uncredentialed teachers in high-need schools:

[Total # of Uncredentialed Teachers_High-Need / Total # of Teachers_High-Need] * 100. 

This procedure was repeated to calculate the share of uncredentialed teachers in low-needs schools.

Once these shares were calculated, researchers calculated a ratio of uncredentialed teachers using the following formula:

% Uncredentialed Teachers_High-Need / % Uncredentialed Teachers_Low-Need.

Ratios closer to 0 reflect a lower concentration of uncredentialed teachers in high-need schools. Ratios equal 1 in districts where the share of uncredentialed teachers is identical in high- and low-needs schools. Where school districts concentrate twice as many uncredentialed teachers in high-need schools versus low-needs schools, the ratio will be 2.

Districts with ratios of uncredentialed teachers less than 1 are coded as 2; districts with uncredentialed teaching staffs greater than or equal to 1 but less than 1.99 are coded as 1; districts with ratios of uncredentialed teachers greater than or equal to 2 are coded 0. Districts with fewer than four schools or missing other information to calculate this measure were coded as Missing.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 1. Points earned by the district for this indicator were multiplied by one before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Teacher composition is similar to student composition

Research and experience show that teachers who serve student bodies with shared backgrounds may be especially equipped to understand and meet these students’ needs. Specifically, Black and Hispanic students benefit from attending schools with teachers who look like them (Lindsay & Hart, 2017; Meier & Stewart, 1992; Pitts, 2007). If teachers better understand and are able to meet their unique student bodies’ needs, school districts may be especially effective at implementing and sustaining innovative programs.

Data for this indicator were collected in June 2021 from the California Department of Education’s Staff Demographics and Student Census Day Enrollment datasets. Researchers downloaded data from the 2018-19 school year.

Following Ed-Date, researchers then subsetted the Staff Demographics dataset to employees assigned to any amount of teaching (“FTE Teaching” > 0). They then calculated each district’s total number of teachers by grouping the dataset with the County-District Code and summing the number of cases. 

They then separately calculated the total number of teachers within each district by the CDE’s racial and ethnic groups. Grouping by the County-District Code and Ethnic Group codes, they summed the total number of rows to calculate the total number of teachers belonging to each racial and ethnic group. The CDE includes nine race and ethnicity groups:

• Not Reported
• American Indian or Alaskan Native 
• Asian, not Hispanic
• Pacific Islander, not Hispanic
• Filipino, not Hispanic
• Hispanic or Latino
• African American, not Hispanic
• White, not Hispanic
• Two or More Races, not Hispanic

Following Pitts (2005), researchers consolidated these nine groups into five groups for ease of calculation:

• Hispanic or Latino
• African American, not Hispanic
• White, not Hispanic
• Asian and other Pacific Islander: “Asian, not Hispanic;” “Pacific Islander, not Hispanic;” “Filipino, not Hispanic”
• Other race/ethnicity: “Not Reported,” “American Indian or Alaskan Native,” and “Two or More Races, not Hispanic”

Researchers then calculated the racial and ethnic proportions of each district’s teachers by dividing the total number of each racial and ethnic groups’ teachers by the total number of teachers in the district.

Using the Student Census Day Enrollment data, researchers then calculated the total number of students enrolled in each district by grouping the data by County-District Code and summing all students (“ENR_TOTAL”).

Like with teachers, they then separately grouped the dataset by County-District Code and Ethnic Group codes to calculate the total number of students belonging to each of CDE’s racial and ethnic groups. Once calculated, they then created the same combined race/ethnicity groups as outlined above for teachers. After that, researchers calculated the racial and ethnic proportions of each district’s students by dividing the total number of each racial and ethnic groups’ students by the total number of students in the district.

Once all proportions were calculated, the separate staff and student demographic proportions databases were merged together.

Using Pitts’s formula (2005) reproduced below, researchers then calculated each district’s Diverse Representation Index score:

[1-sqrt[(H_s-H_t)^2+(W_s-W_t)^2+(AA_s-AA_t)^2+(API_s-API_t)^2+(O_s-O_t)^2]] * 100, where

1. H_s = Proportion of Hispanic Students; H_t = Proportion of Hispanic Teachers; etc.

Finally, researchers rounded each district’s Diverse Representation Index score to the nearest hundredth. Diverse Representativeness Index scores closer to 100 represent school districts where the student and teacher demographic composition are more similar to each other; school districts where Diverse Representativeness Index scores are closer to 0 represent school districts where the student and teacher demographic composition are more dissimilar to each other.

Because districts with a Diverse Representativeness Index score equal to or greater than 50 employed teachers who were more racially and ethnically similar to their students than not, they were coded as 2. Because districts with a Diverse Representativeness Index score greater than or equal to 25 but less than 50 employed teachers who were somewhat similar to their students, they were coded as 1. Because districts with a Diverse Representativeness Index score less than 25 employed teachers who were especially racially and ethnically dissimilar from their students, they were coded as 0.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 1. Points earned by the district for this indicator were multiplied by one before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Teacher turnover rate is lower than the national average

Research and experience show that a high turnover in grades and schools is associated with lower student achievement and additional costs (Ronfeldt et al., 2013). Teacher shortages have long been a concern for ensuring adequate and equitable education that COVID-19 has exacerbated (Balow, 2021). A stable body of teachers should therefore mean that teachers feel valued by their leadership and are dedicated to their shared educational mission (Podolsky et al., 2019).

Data for this indicator were collected in June 2021 from the California Department of Education’s Staff Assignment data files collected through the California Longitudinal Pupil Achievement Data System (CALPADS). The school district’s annual teacher turnover rate was calculated by dividing the number of teachers in a district who remain at the same school from the 2017-18 to 2018-19 school year by the total number of operational schools in the 2018-19 school year. 

After collecting both waves of data, researchers subsetted each of the Staff Demographics datasets to employees assigned to any amount of teaching (“FTE Teaching” > 0). The 2017-18 and 2018-19 waves were appended together to create a longitudinal database. If a given Record ID is associated with multiple schools, researchers identified the Record ID with the greatest FTE for ease of calculation. Each Record ID with a County-District Code only in the 2017-18 and not the 2018-19 school year as a “leaver.” Next, the total number of leavers in the school district were counted. Finally, the total number of leavers were divided by the total number of teachers in the school district during the 2017-18 school year.

Districts with a teacher turnover rate greater than or equal to the 16% national average (Carver-Thomas & Darling-Hammond, 2017) were coded as 2; districts with a teacher turnover rate greater than or equal to 16.1% but less than 25% were coded as 1; districts with a teacher turnover rate greater than 25.1% were coded as 0.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 2. Points earned by the district for this indicator were multiplied by two before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Work Environment

Offers contract bonus for special assignments or certifications

Research and experience show that financial incentives can be seen as a goodwill investment in recruiting teachers for hard-to-staff subjects like Special Education (Putnam & Gerber, 2022) and Bilingual assignments (Nittler, 2017) and with special qualifications like National Board Certification (Goldhaber & Anthony, 2007; Kelley & Kimball, 2001).  

Data for this indicator were collected in January 2022 from the California Department of Education’s 2019-20 Certificated Salaries and Benefits database. From the TSAL120 table, the database was limited to district responses on the J-90 form for the amount of money it offers for teachers who instruct Special Education (“TS1_SEbona”), are assigned to a Bilingual course (“TS1_BBonam”), and received a National Board Certification (“TS1_nbonam”). All columns were then converted into binary indicators where districts that offered any bonus for the special assignment or certification were coded as “Yes” and districts that did not offer any bonuses were coded as “No.” Districts that were coded as “Yes” to any of these indicators were coded as 2; districts that were coded as “No” to all of these bonuses were coded as 0. Districts without responses in the database were coded as Missing.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 1. Points earned by the district for this indicator were multiplied by one before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Signed a Distance Learning Memorandum of Understanding within 30 days of SY 2020-21 start

Research and experience show that districts wherein district administrators and teachers’ union officials could quickly formalize agreements for a COVID-19 teaching and learning environment exhibited signs of labor-management collaboration that encourages all actors to focus on their shared mission of educating students (Koppich, 2021). Conversely, school districts that experienced longer negotiations may hamper future negotiations as both sides remember the difficulties they faced navigating a tumultuous time (Hemphill & Marianno, 2020; Strunk & Marianno, 2019).

Data for this indicator were collected between May 2021 and January 2022. Researchers first collected district closure dates from EdSource’s Interactive Map: The closing of California school districts. A team of researchers then explored school districts’ and certificated unions’ websites for copies of signed/ratified Memoranda of Understanding (MOUs) that outlined temporary workplace conditions during distance learning. Researchers found relevant MOUs for 127 districts (30% of sample). 

Once found, researchers inputted the signed/ratified dates into a dataset alongside the closure dates. Researchers then searched the school district’s website for official calendars detailing the start date for the 2020-21 school year. These dates were then inputted along the other dates.

Finally, researchers calculated the number of days between when the MOU was signed or ratified and the official start date for the 2020-21 school year. Districts that signed or ratified a distance learning MOU up to 30 days after the school year started were coded as 2; districts that signed or ratified an MOU over 30 days after the school year concluded were coded as 0. Districts in which an MOU could not be located or were missing a signed or ratified MOU date or school year start date were coded as Missing.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 1. Points earned by the district for this indicator were multiplied by one before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

One or fewer formal impasses declared involving teacher’s union

Research and experience show that although the most intense labor-management disagreements come to a head in a formal work stoppage or strike, these rarely occur in California education (US Bureau of Labor Statistics, 2021). However, labor-management disagreements can be expressed in other lower-stakes ways like filing formal bargaining impasses to the statewide labor relations board. Such disagreements may inhibit educators from pursuing their shared mission of educating students. 

Data for this indicator were collected in July 2021 from the California Public Employment Relations Board’s online ePERB Cases portal. Researchers limited searches between July 1, 2016 and June 30, 2021, for all Impasse cases (Case Type = “IM”). They then manually collected all cases involving a school district’s certificated bargaining unit. After collecting the cases for this five-year period, researchers calculated the total number of formal impasses experienced by each school district. Districts that faced one or fewer impasses between 2016 and 2021 were coded as 2; districts that faced two impasses were coded as 1; districts that faced three or more impasses were coded as 0. 

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 2. Points earned by the district for this indicator were multiplied by two before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Teacher midpoint salary is greater than or equal to similar district’s statewide average

Research and experience show that an important way school districts can recruit teachers for long-term employment is by offering higher later-career salaries (Gritz & Theobald, 1996; Lin, 2010). Such compensation can encourage retention in school districts (Reed et al., 2006) to continue work toward a shared educational mission that yields strong student results (Dolton & Marcenarro-Gutierrez, 2011).

Data for this indicator were collected in February 2022 from the California Department of Education’s Certificated Salaries and Benefits database. Step 10 on a school district’s salary schedule is typically considered approximately the midpoint salary in a teacher’s career. From the TSAL120 table, the database was limited to district responses for “Salary at BA+60 Step 10.” Reported salaries were then compared to the average statewide salaries for school districts with similar Average Daily Attendances and of the same type. Districts who offered Step 10 salaries above their corresponding statewide average were coded as 2; districts that offered Step 10 salaries below their corresponding statewide average were coded as 0. Districts that did not report this information in their J-90 form were coded as Missing.

Based on a review of the literature, conversations with experts, and experience, researchers weighted this indicator at 1. Points earned by the district for this indicator were multiplied by one before summing the total points earned for the Domain Rating. More information about the rating process can be found in Calculating Domain Ratings.

Bonus: Participated in Labor Management Initiative

Research and experience show that student outcomes and fidelity to programs benefit when a school district’s administrators and teacher’s union work toward a shared mission together (Moore-Johnson & Kardos, 2000). If they cannot effectively collaborate, both sides may require support to better navigate their disagreements. Participation in efforts like the Labor Management Initiative is especially important if a school district already shows signs of conflict.  

Data for this indicator were shared in August 2020 by the Labor Management Initiative with District Readiness Index researchers.

Because the tool treats this indicator as a “bonus” for districts, researchers weighted this indicator at 1 for districts who participated in the Labor Management Initiative. Points earned by the district for this indicator were multiplied by one before summing the total points earned for the Domain Rating. To avoid penalizing districts for not participating in the Labor Management Initiative, the tool does not include the points available for this indicator into the total points possible. We awarded a single point to districts that met the threshold for the impasse indicator but still participated in the LMI. We did this in order to give these districts credit for participating in the LMI, without letting it outweigh the impasse indicator. More information about the rating process can be found in Calculating Domain Ratings.

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