Students at highest estimated risk of suspension felt safer when suspensions were reduced, while students at lowest risk saw the largest test score gains, with no evidence of overall academic harm¶

Claim · All claims
Evidence · 1 study (2 entries) · causal r2 · q2
Currency · newest study 2015 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Students at the highest estimated risk of suspension felt safer in their schools when suspensions for severe infractions were reduced. → Rebecca Hinze-Pifer and Lauren Sartain 2015 q2 i? Students at the lowest estimated risk of suspension saw the largest test score gains, and the article finds no evidence that achievement was harmed overall. → Rebecca Hinze-Pifer and Lauren Sartain 2015 (2)

Evidence¶

Rebecca Hinze-Pifer and Lauren Sartain 2015¶

Rebecca Hinze-Pifer and Lauren Sartain. (2015). Rethinking Universal Suspension for Severe Student Behavior. Stanford University and University of Chicago Consortium on School Research. https://consortium.uchicago.edu

q2 · i? · causal · r2

The study looked separately at outcomes of students with low and high risk of experiencing suspension to address concerns that misbehavior disrupts other students' learning. The article reports high-risk students "felt safer"; no effect size is printed.

"The students at the highest estimated risk of suspension felt safer in their schools when suspensions for severe infractions were reduced."

Rebecca Hinze-Pifer and Lauren Sartain 2015 (2)¶

Rebecca Hinze-Pifer and Lauren Sartain. (2015). Rethinking Universal Suspension for Severe Student Behavior. Stanford University and University of Chicago Consortium on School Research. https://consortium.uchicago.edu

q2 · i? · causal · r2

Risk-stratified analysis of test score outcomes for low-suspension-risk students in the same CPS student-fixed-effect framework. The article reports the largest gains among low-risk students and no evidence of overall academic harm; no effect size is printed.

"Students at the lowest estimated risk of suspension, meanwhile, saw the largest test score gains. We do not find evidence that, overall, students’ academic achievement was harmed by the policy changes."

Discussion¶

Related Claims¶

• A machine learning algorithm with 10-percent risk-score cutoffs better targets students most likely to experience academic problems and has the advantage in predicting suspensions — related
• School climate improved in predominantly Black schools but declined in predominantly Latino and racially diverse schools as suspension use for severe infractions fell — related