School & District Management

Who Got Layoff Notices Under Washington State’s Criteria

By Stephen Sawchuk — January 10, 2011 3 min read
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Districts in Washington state sent out more than 2,000 layoff notices between 2008-09 and 2009-10, and seniority was by far the greatest determinant of which teachers they prioritized for cuts. But evidence suggests that districts attempted to protect certain teachers, including those in “high needs” subjects and those who held master’s degrees, according to a recent analysis of Washington state data.

What’s more, had the decision been based on effectiveness, rather than seniority, the teaching force would have been significantly more effective on average, authors Daniel Goldhaber and Roddy Theobold assert in the paper.

The analysis, from a working paper by the Center for Education Data & Research, at the University of Washington in Bothell, provides a glimpse into which teachers under the seniority system are most likely to get the ax in tough budget times. (In Washington, most of these layoffs never came to pass, thanks to the federal economic-stimulus bill.)

it’s also the latest salvo in the debate about layoff policies, which have come under fire from groups like the New Teacher Project. Such groups say that seniority-based layoffs could raise class sizes and negatively affect student achievement and disproportionately affect at-risk students. Recently, for instance, the American Civil Liberties Union and other partners won a lawsuit in Los Angeles alleging that such policies violated students’ civil rights.

The authors looked at a sample of about 2,000 teachers who received layoff notices in 2008-09 or 2009-10 and compared it with the teaching force as a whole. They broke out the information by teachers’ credentials, their license “endorsements,” and used other state and federal data to supply the demographic characteristics of each teacher’s school. They also used “value added” estimates on a subsample of teachers to create an alternate scenario looking at which teachers would have been cut based on presumed effectiveness, rather than seniority.

Among the findings:

• Teachers that received layoff notices were less experienced, by an average of 10 years in 2008-09 and eight years in 2009-10, not a surprising finding given the emphasis on seniority in local contracts. However, such teachers were also less likely to hold an advanced degree. The authors postulate that districts tried to hang on to teachers felt to have advanced skills.

• Evidence suggests that districts protected teachers in high-need subjects like math, science, and special education; having those credentials meant those teachers were less likely to be laid off. On the other hand, having an endorsement only in health/P.E. and the arts generally increased the likelihood of being laid off.

• Holding more than one endorsement generally decreased the likelihood of being laid off, signaling that districts may be trying to hold on to teachers who can be assigned flexibly to classes in the building.

• All that said, seniority swamped all other factors in predicting which teachers received a reduction-in-force notice, with a first-year teacher twice as likely as one in year 4-6 to receive a layoff notice.

• Value-added measures of teacher effectiveness were not correlated with the RIF notices, so administrators do not appear to have paid attention to effectiveness when targeting teachers for layoff. (All usual caveats about value-added not being a perfect measure of teacher effectiveness, etc., apply here.)

• In a subsample of teachers with value-added data, just 16 percent of teachers who received a RIF notice would also have received one had the decisions been based on value-added results. The results would also have affected some students less, with black students less likely to have their teacher laid off under the effectiveness scenario.

• A large differential in teacher effectiveness exists between those teachers who received RIFs and those who would have received them under the hypothetical, value-added-based model: 20 percent of a standard deviation of student achievement in math and 19 percent of one in reading.

Also, make sure to check out an earlier item for a summary of another paper looking at layoffs through a similar frame. It, too, found wide differences in who would be cut under two sets of layoff criteria.

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A version of this news article first appeared in the Teacher Beat blog.