The bacterial roots of the new autocracies: An essay on "Biopolitics".

A new wave of autocratic nationalisms has at least ten nations in its grip, and growing. Does this new impulse of authoritarianism have roots in a deep evolutionary past? The answer goes back to two algorithms roughly 3.85 billion years old.

The Validity of the Comparative Interrupted Time Series Design for Evaluating the Effect of School-Level Interventions.

Objective: In this article, we examine whether a well-executed comparative interrupted time series (CITS) design can produce valid inferences about the effectiveness of a school-level intervention. This article also explores the trade-off between bias reduction and precision loss across different methods of selecting comparison groups for the CITS design and assesses whether choosing matched comparison schools based only on preintervention test scores is sufficient to produce internally valid impact estimates.

Research Design: We conduct a validation study of the CITS design based on the federal Reading First program as implemented in one state using results from a regression discontinuity design as a causal benchmark.

When is the story in the subgroups? Strategies for interpreting and reporting intervention effects for subgroups.

This paper examines strategies for interpreting and reporting estimates of intervention effects for subgroups of a study sample. The paper considers: why and how subgroup findings are important for applied research, alternative ways to define subgroups, different research questions that motivate subgroup analyses, the importance of pre-specifying subgroups before analyses are conducted, the importance of using existing theory and prior research to distinguish between subgroups for whom study findings are confirmatory (hypothesis testing) as opposed to exploratory (hypothesis generating), and the conditions under which study findings should be considered confirmatory. Each issue is illustrated by selected empirical examples.

Using "short" interrupted time-series analysis to measure the impacts of whole-school reforms. With applications to a study of accelerated schools.

The present article introduces a new approach for measuring the impacts of whole-school reforms. The approach is based on "short" interrupted time-series analysis, which has been used to evaluate programs in many fields. The approach is used to measure impacts on three facets of student performance: (a) average (mean) test scores, which summarize impacts on total performance; (b) the distribution of scores across specific ranges, which helps to identify where in the distribution of student performance impacts were experienced; and (c) the variation (standard deviation) of scores, which indicates how the disparity in student performance was affected.