We study the relationship between school organizational contexts, teacher turnover, and student achievement in New York City (NYC) middle schools. Using factor analysis, we construct measures of four distinct dimensions of school climate captured on the annual NYC School Survey. We identify credible estimates by isolating variation in organizational contexts within schools over time. We find that improvements in school leadership especially, as well as in academic expectations, teacher relationships, and school safety are all independently associated with corresponding reductions in teacher turnover. Increases in school safety and academic expectations also correspond with student achievement gains. These results are robust to a range of threats to validity suggesting that our findings are consistent with an underlying causal relationship.

With the use of a simple 8-variable scoring system, inpatient mortality estimates can be made for patients requiring emergent colectomy. When used judiciously, it can be used as a tool when counseling patients and family both before and after surgery.

Discretizing continuous distributions can lead to bias in parameter estimates. We present a case study from educational testing that illustrates dramatic consequences of discreteness when discretizing partitions differ across distributions. The percentage of test-takers who score above a certain cutoff score (percent above cutoff, or " ") often describes overall performance on a test. Year-over-year changes in , or Δ , have gained prominence under recent U.S. education policies, with public schools facing sanctions if they fail to meet targets. In this paper, we describe how test score distributions act as continuous distributions that are discretized inconsistently over time. We show that this can propagate considerable bias to trends, where positive Δ s appear negative, and vice versa, for a substantial number of actual tests. A simple model shows that this bias applies to any comparison of statistics in which values for one distribution are discretized differently from values for the other.

Some researchers have questioned whether there is a causal connection between Advanced Placement (AP) STEM coursetaking and the choice of a STEM college major and a STEM occupation. Their research findings strongly suggest that if prior interest in STEM as well as other possible confounders are taken into account, the relationships of taking AP mathematics to expecting to be in a STEM major and/or a STEM occupation are small to nonexistent. Results from the current study, which uses data from a national longitudinal sample—actual measures of who majors in STEM—and prior interest in STEM along with other possible confounders, indicate that taking AP mathematics and AP science courses is significantly related to majoring in STEM and/or expecting to be in a STEM occupation at age 30—the sole exception being the taking of AP statistics.

No abstract