Examining the Impact and Equity of
Seniority-Based Teacher Layoff Notices in
Washington State: 2008-09 to 2009-10
A Report Submitted to the Harry Bridges Center for Labor Studies
Prepared by:
Margaret L. Plecki
Associate Professor
Matthew Finster
Graduate Research Assistant
University of Washington
College of Education
November 2010
Table of Contents
Abstract and Acknowledgements…………………………………….…………… iii
I.
Purpose of the Research……………………………………………………..….1
II. Summary of Relevant Literature about Reduction in Force………………...1
III. Research Questions…………………………………………………………….2
IV. Data Sources and Methods…………………………………………………….3
V. Study Findings…………………………………………………………………...5
A. Characteristics of Teachers Receiving RIF notices……………………...……5
B. Characteristics of Schools with RIF staff……………………………………..7
C. Impact of RIF on Retention, Mobility and Attrition…………………....……..9
D. Comparison of Districts’ Collective Bargaining Agreements……………….. 11
E. Initial Comparison of 2009 and 2010 RIF Lists…………………………...….13
VI. Summary ………………..……………………………………...……………….15
References………………………………………………………………….…………17
Appendices
Appendix A-RIF Schools by District
Appendix B-Teachers by School Demographics by District
Appendix C-Teacher Rehire Rate by School Demographics
ii
Abstract
In the current economic downturn, a process known as Reduction in Force (RIF) has been used
by districts to alleviate growing financial pressures. As mandated by policies of collective
bargaining agreements, seniority is the primary criterion for determining who receives a RIF
notice. Some research indicates that inequalities result from seniority-based RIF processes in
large urban settings. However, given a lack of empirical evidence examining the impact of the
RIF process at the school level in settings other than large urban districts, our guiding research
question is: Are different types of schools impacted disproportionally, and, if so, which types of
schools and to what degree? This primarily quantitative study examined the impact and equity of
the distribution of RIF notices across schools in ten districts in Washington state. Overall, our
data suggests that while there is some evidence of inequities of the RIF process at the school
level, it is not uniformly present across all districts. Additionally, variations in the methods used
to conduct seniority-based layoffs create slight differences in the identification of teachers who
receive a RIF notice. As the current economic climate continues, RIF is likely to reoccur in
districts and schools. Research examining the equity of the distribution of seniority-based RIF
notices may help inform district staffing policies.
Acknowledgements
The authors gratefully acknowledge support for this research that was provided by the Harry S.
Bridges Labor Research Center at the University of Washington. However, the analyses and
opinions provided in this report are the sole responsibilities of the authors.
iii
I. Purpose of the Research
While teacher layoffs in K-12 education have occurred multiple times across the nation
over the past three decades, there is limited research that examines the characteristics of teachers
who receive Reduction in Force (RIF) notifications, the impact of teacher layoffs on teacher
quality, and the implications for the equity of access to education. In recent years, questions
about the role of seniority in determining who receives layoff notices have sparked considerable
debate in education policy circles. However, little empirical work exists as to whether senioritybased teacher layoffs create distributional inequities on specific types of schools and the students
who attend them. This research report expands on our initial analysis of RIF notices issued by
Washington school districts in the Spring of 2009. We expanded this initial descriptive work to
include an examination of whether the 2009 layoff notices and the subsequent re-hiring rates had
a disproportionate impact on students located in high-poverty or racially/ethnically diverse
schools. In doing so, we examined the impact of layoff notices at the individual school level. We
focused on the individual school level because often inequities among schools within the same
district (intra-district differences) are more pronounced than inequities found across different
districts. Evidence as to whether such disparities exist in Washington state can help inform the
policy debate regarding any unintended consequences of seniority-based layoff procedures.
II. Summary of Relevant Literature about Teacher Layoffs
Much of the current debate about Reduction in Force (RIF) centers on the traditional role
of seniority as the primary determinant in decisions regarding who receives layoff notices. While
some specific elements of the RIF process are dictated by state statute, state board of education
regulations, collective bargaining agreements, and/or local school board policies, the widely
accepted practice of basing layoffs on seniority alone is not necessarily legally required (Wood,
1986). In Washington state, collective bargaining agreements between school districts and
education associations establish seniority as the controlling factor in determining which teachers
should receive a RIF notice. State statutes in Washington clarify the meaning of seniority in
layoff procedures, including a ruling in how seniority status is to be calculated. In Oak Harbor
School District v. Oak Harbor Education Association (1976), a Washington Superior Court ruled
that school districts using seniority lists as a determinant in layoff procedures are required to
compute seniority with reference to total years of service within the state of Washington rather
than years of service in the profession (including years spent working out of state) or years of
service within a district. However, state statutes do not require the use of seniority as the sole or
primary criterion. Thus, from a legal perspective, alternatives to seniority-based layoff
procedures are potentially available for local school boards and employee associations to
consider (Wood, 1986).
Even though alternatives are possible, seniority-based procedures have dominated layoff
practices and policies across the nation. In 2009, nearly 60,000 teachers were laid off by districts
using seniority as the primary determinant (National Center for Teaching Quality, 2010). Some
policymakers wish to curtail or amend the predominant role of seniority in determining layoffs,
including efforts in the U.S. Congress to tie federal aid to the elimination of seniority-based
layoffs (Sawchuck, 2010). Advocates of this approach argue that seniority-based practices
1 exacerbate the number of jobs lost and raise concerns about ignoring the role of teacher
performance in determining layoffs (Chait & Miller, 2009; Roza, 2009; NCTQ, 2010). These
concerns are supported by a recent empirical example provided by Boyd, Lankford, Loeb &
Wyckoff (2010) which demonstrates that using a seniority-based layoff procedure compared to a
value-added system results in more layoffs and a less effective workforce.
Additionally, there is some evidence which suggests that teacher layoffs
disproportionately impact high-poverty and high-minority schools (Chait & Miller, 2009; Sepe &
Roza, 2010) and further exacerbate problems with recruiting and retaining teachers to work in
challenging schools. This claim is supported by evidence that in some large urban districts,
inexperienced teachers are disproportionately located in high-poverty schools and in schools
serving high proportions of students of color (Lankford, Loeb & Wyckoff, 2002; Peske &
Haycock, 2006; Levin, Mulhern & Schunck, 2005). Recently in California, a class-action
lawsuit, Reed v. State of California, was brought against the state and the Los Angles Unified
School District concerning the impact of teacher layoffs at three of the district’s middle schools.
The lawsuit claimed that the teacher layoffs implemented by the district resulted in a negative
and disparate impact on middle schools serving primarily students of color and students in
poverty, as compared to the district’s more affluent schools. The Superior Court agreed that the
teacher turnover associated with the layoff procedures did impose severe harm on the students in
the three middle schools, denying them the right to equal educational opportunity (National
Access Foundation, 2010). The tentative settlement reached between LAUSD and the plaintiffs’
attempts to make layoffs more equitable by capping the number of teachers that can be laid off
from a particular school (Llanos, 2010).
However, the evidence regarding the disparate impact of seniority-based layoffs is based
on studies of very large urban school districts such as New York and Los Angeles. Thus, we do
not know whether, or in what specific ways, this research is applicable to conditions in a variety
of districts in Washington state. In fact, our initial analysis of the data regarding layoff notices in
2009 indicates that not all teachers who received layoff notices were inexperienced. Nearly onefifth of teachers that received a RIF notice in Washington state had more than five years of
experience, and of these, nearly half had more than 10 years of experience (Plecki, Elfers, &
Finster, 2010). This provides some aggregate data that questions whether the “last hired, first
fired” rule is uniformly present. We have a hypothesis that the findings from our aggregate data
is in part a function of the fact that in Washington, layoff procedures favor those whose years of
teaching experience are within the state over total experience acquired both in and out of state
(Oak Harbor School District v. Oak Harbor Education Association, 1976).
Further empirical research is also needed to determine if there is a disparate, negative
impact of teacher layoffs on particular schools and particular subgroups of students within
specific districts in Washington State. If disparities do indeed exist, then perhaps alternatives to
seniority-based layoff procedures are in need of consideration to address equity concerns.
III. Research Questions
In order to assess the impact of the 2009 RIF notification process on schools, teachers and
students, our research addressed the following questions:
2 1. What are the individual characteristics of teachers who received RIF notices? Why did
teachers with more than five years of experience receive a layoff notice?
2. What are the characteristics of individual schools where RIF notices occurred? What are
the characteristics of students most impacted by teacher layoff notices?
3. Do teacher layoff notices differentially impact particular schools within the same district?
If so, in what specific ways?
4. Are high-poverty, high-minority and/or high-performing schools more likely to be
impacted by RIF notices than other types of schools?
5. How did the re-hire rates of teachers who received RIF notices vary among schools
within and across districts? What factors are associated with these differences?
6. In what ways do collective bargaining agreements affect the RIF process in a sample of
districts that issued layoff notices?
7. What can we learn from initial district and teacher-level data about layoff notices issued
in 2010 as compared to those issued to 2009?
IV. Data Sources and Methods
This is primarily a quantitative study that integrates a variety of large scale, state-level
databases maintained by the Sate of Washington’s Office of the Superintendent of Public
Instruction and the Professional Educator Standards Board. These state data sources include
administrative data for all education personnel, the state’s teacher certification database, and
school and district data regarding fiscal indicators and student and teacher demographics.
Drawing from a list of all school personnel in the state of Washington who received a layoff
notice in the Spring of 2009, we constructed datasets and conducted analyses that addressed our
research questions.
To analyze the individual characteristics of teachers that received a RIF notice (RIF
teachers), we compared RIF teachers to all teachers statewide in regards to age, ethnicity, levels
of education, and experience. Additionally, we examined how teachers who received a RIF
notice were distributed across schools within individual districts. As previously mentioned, our
initial analysis found that nearly one-fifth of RIF teachers had more than five years of
experience. After securing and examining the state’s teacher certification database, we were
unable to verify whether teachers had out of state teaching experience. In order to gauge the
discrepancy between in-state and out-of-state experience levels of teachers in one district, we
compared the experience levels in the state personnel database (S-275) and the in-state
experience listed on the individual district seniority lists created for the RIF process. This
provides some information on why one-fifth of the teachers that received a RIF notice had more
than five years of experience.
In order to examine the characteristics of individual schools and determine how layoff
notices may have differentially impacted schools within the same district, we created a database
which links the teachers that received a RIF notice to their school building, allowing us to
compare schools which experienced a RIF and schools which did not, within our sample
districts. We compared these schools to their respective district average student poverty and
percent of students of color. An analysis was conducted to determine if novice teachers who
received a RIF notice are overrepresented in high-poverty, high-minority schools.
3 With our data on the subsequent employment of the teachers that received a RIF notice,
we were able to examine how teachers who were re-hired in the subsequent year (2009-10) were
distributed in schools within and across districts. This data also allows us to compare the re-hire
rates of teachers receiving a RIF notice by school poverty and student ethnicity.
As part of our extended analysis, we reviewed the collective bargaining contracts from
selected districts to examine whether any specific differences in collective bargaining contracts
resulted in a different selection of teachers who received a RIF notice. We obtained the collective
bargaining agreements for our ten sample districts and analyzed their individual layoff
procedures. Specifically, we examined the ways in which layoff procedures may differentially
identify those who receive a RIF notice in the sample districts.
Lastly, we recently received the preliminary list of those who received RIF notices in
2010. This preliminary data contains 97% (286 of 295) of the school districts’ responses. As part
of an initial analysis of this data, we compared some basic teacher and district information from
2009-10 with the prior year’s RIF list.
District Sample
For our school level analysis, we selected the ten districts in the state that issued the
greatest number of RIF notices in 2009. The ten districts are: Auburn, Battle Ground, Bethel,
Highline, Issaquah, Marysville, Peninsula, Puyallup, Seattle, and Spokane school district. The
number of RIF notices issued by these ten districts ranged from 219 to 47 teachers. The school
districts vary in the proportions of students of color and students living in poverty. The majority
of the selected districts (70 percent) are located in the Puget Sound region. A majority of the
sample districts (80 percent) are located in suburbs, while two are located in cities. Most sample
districts have a student enrollment greater than 10,000 students.
Table 1
Demographic Characteristics of Sample Districts
District Name
Bethel
Issaquah
Seattle
Spokane
Battle Ground
Puyallup
Peninsula
Highline
Marysville
Auburn
# RIF
Notices
197
132
128
75
72
65
59
57
54
47
ULocale
Code
21
21
11
12
21
21
21
21
22
21
Enrollment
08-09
18032
16696
45968
29692
13268
21676
9456
17548
11923
14937
Student
Poverty
40.0
8.3
41.3
53.5
33.2
27.5
20.5
60.3
40.4
44.3
Percent
Minority
35.7
30.1
56.6
22.8
12.5
30.7
19.9
66.7
32.5
55.7
4 V. Study Findings
The findings are presented in five sections. First, we examine the characteristics of
teachers receiving a RIF notice and the types of schools in which they work and provide
comparisons with all the teachers in the districts. Second, we look at the characteristics of
schools with RIF staff and compare them to all schools within the districts. Next, we analyze the
impact of RIF notices on teacher retention by examining the re-hire rates of teachers receiving a
RIF notice in different types of schools. Fourth, we examine differences in district collective
bargaining agreements with respect to who receives a RIF notice. The report concludes with an
initial comparison of the 2009 and 2010 RIF lists.
A. Characteristics of Teachers Receiving RIF Notices
Our first set of analyses examines whether higher proportions of RIF teachers were
located in a district’s higher poverty schools. In five of the ten districts, teachers that received a
RIF notice are overrepresented in schools with a poverty rate higher than the district’s average.
As Figure 1 illustrates, in the Auburn School District, 55 percent of all teachers in the district
work at schools below the district average poverty level, but only 34 percent of teachers
receiving a RIF were at schools below the average poverty level. In the other four school districts
in which teachers receiving a RIF notice are overrepresented in schools at or above the average
district poverty levels, the differences between the percentage of RIF teachers and all teachers in
the district’s higher poverty schools ranges from 7 percent to 9 percent.
Figure 1:
RIF Teachers and All Teachers by Student Poverty in the Auburn School District
100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% RIF Teachers All Teachers FRPL students below 44.3% 34.0% 55.4% FRPL students above 44.3% 66.0% 44.6% 5 In contrast, in the other five districts, RIF teachers are under-represented in the district’s
higher poverty schools. In other words, in these five districts, the proportion of RIF teachers in
the district’s higher poverty schools is less than the proportion of all district teachers in higher
poverty schools. In the Seattle School District, 49 percent of the teachers work in schools at or
above the average district poverty level, but only 43 percent of the teachers that received a RIF
notice were in a higher poverty school. Figure 2 shows the RIF teachers and all teachers by
district average poverty level for all ten sample districts.
Figure 2
Proportion of RIF Teachers Compared to All Teachers by Districts' Respective Average
Poverty Levels
Below district average FRPL Above district average FRPL 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% Auburn BaEle Ground Bethel Highline Issaquah Marysville Peninsula Puyallup SeaEle All Teachers RIF teachers All Teachers RIF teachers All Teachers RIF teachers All Teachers RIF teachers All Teachers RIF teachers All Teachers RIF teachers All Teachers RIF teachers All Teachers RIF teachers All Teachers RIF teachers All Teachers RIF teachers 0% Spokane We conducted a similar analysis that examines the distribution of RIF teachers by the
proportion of students of color in the district’s schools. In 80 percent of our sample districts, the
proportion of RIF teachers in schools at or above the districts’ average percent of students of
color is greater than the proportion of teachers working in these types of schools. In these
districts, the differences range from 18 percent to 4 percent, with Spokane representing the
greatest difference. Figure 3 displays the proportion of RIF teachers compared to all teachers by
percent of students of color for each district.
6 Figure 3
Proportion of RIF Teachers Compared to All Teachers by Districts' Respective Average
Percent of Students of Color
Auburn BaEle Ground Bethel Highline Issaquah Above district average ethniPcy level Marysville Peninsula Puyallup SeaEle All teachers RIF teachers All teachers RIF teachers All teachers RIF teachers All teachers RIFTeachers All teachers RIF teachers All teachers RIF teachers All teachers RIF teachers All teachers RIF teachers All teachers RIF teachers All teachers RIF teachers 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Spokane Below district average ethnicity level B. Characteristics of Schools with RIF staff
In addition to our analysis of the distribution of individual RIF teachers across schools,
we also examined the characteristics of schools with RIF staff (RIF schools) to those schools that
were unaffected by RIF notices (non-RIF schools) and all schools within the districts. For our
examination, we primarily contrast RIF schools to all the schools within their respective districts.
In nine of the ten sample districts, RIF schools are slightly overrepresented by poverty rate
compared to all schools in the district.
To illustrate this point, we will discuss the Battle Ground School District, which has one
of the larger proportional differences. In Battle Ground, RIF schools above the district poverty
level of 33.2% represent 61.1% of the RIF schools, as compared to the 50.0% of all schools in
the district that are above the poverty level. This information is depicted in Figure 4.
7 Figure 4
Percent of RIF Schools v. All Schools by Poverty Level in the Battle Ground School District
70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% Above average FRPL Below average FRPL RIF schools 61.1% 38.9% All schools 50.0% 45.5% *Note: 4.5% of schools FRPL unavailable or unreported
Looking across all ten districts, the differences in percentages between the RIF schools
and all schools range from 16 percent at higher than average poverty rates to 2 percent below the
district average poverty rate. In four school districts, the discrepancy exceeds 10%. For example,
in the Auburn School District, of the 18 RIF schools, 12 buildings (66.7%) were above the
district average poverty level of 44.3%, and 6 buildings (33.3%) were below the average poverty
rate. This compares to all schools in the district with 56 percent above and 43 percent below the
poverty rate. In these cases, RIF schools with higher levels of poverty were disproportionately
affected by the RIF process.
Also, in 8 of 10 districts, RIF schools above the respective average percent of students of
color are slightly overrepresented compared to all of the schools in the district. As an example, in
the Spokane School District, there is a 16.3% differential; 60 percent of the RIF schools were
above the average district ethnicity level of 22.8%, compared to 44 percent of all schools in the
districts. Conversely, two school districts, namely, Battle Ground and Issaquah, had no
discrepancies. This information is depicted in Figure 5, which overlays the percent of all schools
over RIF schools by district. Additional detailed information for comparing the percentages of
RIF schools and all schools below the respective district average is located in Appendix A.
8 Figure 5
Proportion of RIF Schools Compared to All Schools that are above
Districts' Average Percentage of Students of Color
In five districts, the number of non-RIF schools by grade group (e.g. elementary, middle,
and high schools) is too small to make comparisons between RIF schools and non-RIF schools.
Additionally, non-RIF schools are less likely to be traditional K-12 schools. Of the non-RIF
schools in all of the ten sample districts, a disproportionate number (54.9%) are small alternative
schools. In the other five districts which have a sufficient number to compare RIF and non-RIF
schools, alternative schools are a large proportion of the non-RIF schools ranging from 31
percent to 76 percent. Thus, our school-based analysis was limited by these factors.
C. Impact of RIF on Retention, Mobility and Attrition
We now focus our attention on the impact of RIF notices on the employment status of
teachers in the following year in these ten districts. In a previous analysis of the 2009 layoff
notices (Plecki, Elfers, & Finster, 2010), it was determined that 87 percent of RIF teachers were
re-hired in the subsequent year. Additionally, 60 percent of the RIF individuals were rehired at
the same school. In this report, these individuals are referred to as “RIF stayers”. For each
sample district, in order to determine the impact of RIF notices on schools with different
characteristics, we linked the RIF teachers to their schools and determined the schools’ re-hire
rate of RIF teachers. We then assigned the schools within each district into two groups based on
the respective district average poverty rates and average percent of students of color.
9 The findings are mixed regarding the RIF teachers’ re-hire rates by school characteristics
(e.g., poverty and ethnicity). In four districts, the percentage of stayers is higher in schools above
the district average poverty level. The range of the percentage of RIF stayers at schools above
and below the respective district average poverty level is 42.8% to 0%. Marysville School
District has the largest differential between the percentage of stayers in schools above and below
the district average poverty level, with a RIF teacher retention rate of 78.3% in schools above
the district average poverty level compared to 35.5% in schools below the district average
poverty level. This information is depicted in Figure 6.
Figure 6
Percentage of RIF Stayers by Poverty Level in the Marysville School District
90.0% 80.0% 70.0% 60.0% 50.0% 40.0% Stayers 30.0% 20.0% 10.0% 0.0% In District In Schools above In Schools below District Average District Average Poverty Level Poverty Level In four school districts, of the teachers that received a RIF notice, the percentage of
stayers in schools exceeding the average district poverty level is larger than the percentage of
RIF stayers in schools below the average district poverty level. This is finding is portrayed in the
Auburn School District, in which, of the 31 RIF teachers in schools above the district average
poverty level, 90.3% were rehired at the same school compared with 68.8% of the 16 teachers in
schools below the district average poverty level. In two school districts, there is no difference
between the percentage of RIF stayers in schools above and below the respective district average
poverty level. In the remaining four school districts, there are higher percentages of RIF stayers
at schools below the district average poverty level. In the case of the Peninsula School District,
schools below the district average poverty level had a RIF teacher retention rate of 66.7%
compared to schools above the district average poverty level which had a retention rate of
43.5%. The various differentials for each district are shown in Figure 7. Negative percentages
indicate that the percentage of RIF stayers is greater in schools below the respective average
poverty level. As can be seen in Figure 7, results are mixed, providing additional evidence that
the impact of RIF varies greatly across the sample districts.
10 Figure 7
Differential of the Re-hire Rates at Schools above the District Average Poverty Level and
Schools below the District Average Poverty Level
50.0% 40.0% Auburn BaEle Ground 30.0% Bethel 20.0% Highline Issaquah 10.0% Marysville Penninsula 0.0% Percent Stayers ‐10.0% Puyallup SeaEle Spokane ‐20.0% ‐30.0% We can conclude from this analysis that, in most of the sample districts, RIF teachers
compared to all teachers in a district are disproportionately situated in schools with a respective
higher level of students of color. In the case of student poverty, while the evidence is not as
consistent across districts, in half of the districts, RIF teachers are more highly concentrated in
respectively higher poverty schools. Furthermore, the results of the examination of the rehire
rates of RIF teachers demonstrates that there does not appear to be a uniform pattern of RIF
teachers being rehired at certain types of schools.
In the next section, we depart from a descriptive analysis of RIF teachers and schools and
we attempt to elucidate the potential influence of collective bargaining agreements on some of
our findings regarding the characteristics of RIF teachers. In order to clarify our findings
regarding the experience level of RIF teachers, we examine the potential effects of collective
bargaining agreements on the RIF process and provide an explanation of how they may influence
who receives a layoff notice.
D. Comparison of Districts’ Collective Bargaining Agreements
To examine the ways in which RIF procedures may differentially impact who receives a
RIF notice, we collected and compared the Collective Bargaining Agreements for the ten sample
districts. While all of the sample districts use seniority as the primarily layoff criteria (and often
times within category or endorsement area), the means by which the collective agreements
11 stipulate that “seniority” is calculated includes several variations which may contribute to some
variation in the experience levels of teachers that received a RIF notice. According to the ruling
from Oak Harbor School District vs. Oak Harbor Education Association (1976) districts are
required to compute seniority with reference to total years of service within the state of
Washington. While six of our sample districts define seniority similar to the Collective
Bargaining Agreement between Bethel School District #403 and the Bethel Education
Association, which states “length of service within Washington State” (Collective Bargaining
Agreement, 2009, p.36); four districts use the experience level “as stipulated in the S-275”
(Collective Bargaining Agreement Puyallup School District No.3 and the Puyallup Education
Association, 2008, p.56) or “as granted for salary purposes at time of initial employment”
(Negotiated Agreement between the Issaquah Education Association and the Issaquah School
District, 2007, p.76). In the state’s S-275 Personnel Reporting Instructions for School Year 200809, certificated years of experience are granted by professional education employment
determined by experience in public or private P-12 schools in certificated positions, in colleges
in comparable positions, and in governmental education agencies in professional positions. This
potentially allows out-of-state teaching experience to be included in a teacher’s listed experience.
These variations of the definition of “seniority” in the Collective Bargaining Agreements
potentially impact teachers with out-of-state experience differently with respect to their
placement on the seniority list used for layoff procedures.
To explore how these variations may impact teachers, we compare districts that used
different methods for calculating seniority. Of our ten sample districts, four school districts use
the state’s S-275 database, while six school districts do not. According to a previous analysis
(Plecki, Elfers, & Finster 2010), it was determined that one-fifth of RIF teachers had more than
five years of experience. In the school districts which do not use the S-275, 13 percent of the RIF
teachers had five years or more of experience. However, in the four school districts which use
the S-275, less than five percent of the RIF teachers had five or more years of experience. The
results indicate that in the sample districts that use the state’s personnel file (S-275) as the
determinant of teachers’ years of experience for the RIF process, our analysis shows a higher
percentage of RIF teachers with fewer years of experience.
To provide clarification on this matter, we examine the Spokane School District which
uses a seniority list based on Washington State public and private school experience. In school
districts in which the Collective Bargaining Agreements specifically define seniority as “the
length of service within Washington state” (such as theSpokane School District), teachers listed
with more experience in the S-275 may still have received a RIF notice over a teacher with less
experience. To examine this potential difference in Spokane, we compared the experience levels
listed in the state personnel database (S-275) and the in-state experience listed on the district’s
seniority list created for the RIF process. In Spokane, 15 percent of the teachers that received a
RIF notice had 5 or more years of experience as listed in the S-275. However, according to
Spokane’s 2008-2009 certificated seniority list, all of the teachers that received a RIF notice had
1 year or less of experience. This comparison is depicted in Figure 8.
12 Figure 8
Comparison of Experience Level by S-275 v. Certificated Seniority List of the Spokane
School District's RIF Staff
80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% 0 years .1‐1 1.1‐2 2.1‐3 S‐275 3.1‐4 4.1‐4.9 5‐9.9 10‐14.9 15‐24 08‐09 Seniority List By comparing the collective bargaining agreements in our sample districts we observe
that the calculation of previous relevant teaching experience in the RIF process varies by district,
depending on contract specifications.
Since the RIF process varies greatly from year to year, in the next section, we begin to
build an initial two year comparative analysis of the 2009 and 2010 RIF lists in order to describe
the impact of the RIF process on districts and teachers over time.
E. Initial Comparison of 2009 and 2010 RIF Lists
As budgetary woes and economic uncertainty persist, RIF notices continue to be used by
districts to mitigate financial pressures. To monitor the continuing impact of the RIF process and
to gauge its prevalence, we compare the 2008-2009 and 2009-2010 RIF lists at the district and
the individual teacher level.
Preliminary data from 2010 indicates that the number of layoff notices decreased. In the
preliminary data about the 2009-2010 school year, 566 teachers received RIF notices in
Washington state.1 Nearly one quarter (23 percent) of districts report engaging in RIF as
opposed to 46 percent in the 2008-2009 school year. Figure 9 depicts the number of RIF districts
and teachers for 2008-2009 and 2009-2010. Of the 68 districts that reported engaging in RIF, 48
districts engaged in RIF the previous year; in other words, 71 percent of the districts are
repeaters. This information is shown in Figure 10. Fifty percent of the districts that we selected
for our analyses engaged in RIF both years, namely, Bethel, Highline, Maryville, Seattle, and
Spokane. However, the number of teachers receiving a RIF notice in each of these districts
1
This is preliminary data. Nine districts had not yet reported their status at the time of this writing. 13 declined substantially, ranging from a decrease of 47 percent to 95 percent. As examples, Seattle
allocated 128 RIF notices in spring of 2009 and only 35 in 2010, Highline issued 57 RIF notices
in spring of 2009 and 30 in 2010. A comparison of the number of teachers receiving a RIF
notice in 2009 and 2010 in these five districts is depicted in Figure 11.
Figure 9
RIF Districts and Teachers 2008-2010
2000 1800 1600 1400 1200 1000 800 600 400 200 0 2008‐2009 2009‐2010 1857 566 RIF Teachers Figure 10
Comparison of the Number of RIF Districts 2008-2010
160 140 120 100 80 New 60 Repeaters 40 20 0 RIF Districts 2008‐2009 RIF Districts 2009‐2010 14 Figure 11
Comparison of the Number of RIF Teachers in the Repeater Sample Districts
250 200 150 100 50 0 Bethel Highline Maryville # RIF Teachers 2008‐2009 SeaEle Spokane # RIF Teachers 2009‐2010 The data indicates that the number of districts engaging in RIF and the number of RIF
teachers declined substantially from the 2008-09 to 2009-10 school year. A majority of the
school districts engaging in RIF procedures in 2009-10 are repeaters, and slightly less than 30
percent are districts that did not engage in a RIF process in the prior year.
VI. Summary
This report provided data and analyses about the impact of teacher layoff notices in
selected schools and districts in Washington state. The common assumption is that layoff
notices mostly impact teachers with the fewest years of experience, as most district use senioritybased systems in their layoff procedures. However, our earlier analysis found that nearly onefifth of teachers that received a RIF notice in Washington state had more than five years of
experience, and of these, nearly half had more than 10 years of experience. In interpreting this
result, it is important to note that in Washington state, a specific legal interpretation of how to
construct seniority lists requires that years of teaching experience in Washington state prevails
over total years of teaching experience both within and outside Washington. In addition, our
examination of the collective bargaining agreements in our ten sample districts with the highest
number of layoff notices indicated that there are some other small differences that exist in the
methods used by districts to determine seniority lists.
The bulk of our inquiry examined the equity of the distribution of teacher layoffs across
schools within the same district. We examined whether higher poverty schools and schools
serving higher percentages of students of color in each of our ten sample districts were
disproportionately impacted by teacher layoffs. In summary, we found that there is a good deal
of variation by district with respect to this question. While there is some evidence of inequities
15 in the distribution of RIF teachers across schools, it is not uniformly present in the districts we
examined. We conclude that, while numerous factors and conditions influence how layoffs are
distributed across schools, districts should be aware of the potential inequities and give some
consideration to strategies which might help ameliorate the degree of disproportionality that
might result.
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18 Appendices
Appendix A-RIF Schools by District
Appendix B-Teachers by School Demographics by District
Appendix C-Teacher Rehire Rate by School Demographics
19 Appendix A- RIF Schools by District
20 Appendix B- Teachers by School Demographics by District
21 Appendix C‐Teacher Re‐hire Rate by School Demographics 22