Hiring is an opportunity for school districts to find educators with values and beliefs that align with district goals. Yet beliefs are difficult to measure. We use administrative data from more than ten thousand applications to certificated positions in an urban California school district in which applicants submitted essays about closing achievement gaps. Using structural topic modeling (STM) to code these essays, we examine whether applicants systematically differ in their use of these themes and whether themes predict hiring outcomes. Relative to white applicants, Hispanic and African American applicants are more likely to identify structural causes of inequities and discuss educators' responsibilities for addressing inequality. Similar differences in themes emerge between applicants to schools with different student populations. Techniques like STM can decipher hard-to-measure beliefs from administrative data, providing valuable information for hiring and decision making.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6545989 | PMC |
| http://dx.doi.org/10.7758/RSF.2019.5.3.06 | DOI Listing |
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