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Evidence from V-Dem suggests cases of growing illiberalism in recent decades - but also some countries where democracy has proved stable or even strengthened during these years. What has been driving these diverse trajectories? This chapter starts to unpack the theoretical debates and considers new empirical evidence analyzed using mixed methods to explore the links potentially connecting populist governments and backsliding. Part I defines the concept and logic of populist discourse and summarizes the previous theoretical and empirical literature. Part II compares the position of a wide range of political parties towards both liberal democracy and populism. The comparison further confirms that many, but not all, political parties employing populist discourse often oppose checks and balances on executive power, as well as liberal democratic principles, norms and practices. Part III analyses longitudinal cross-national data during the first quarter of the 21st century to determine the dynamic trajectories of democratic regimes worldwide under both populist and non-populist governments. To replicate previous studies in Europe and Latin America, difference-in-difference time-series panel regression models are employed to estimate causal effects through a quasi-experimental technique using observational data from treatment (populist-led governments) and control groups (non-populist governments) in power for heterogeneous periods during the last 25 years. Part V explores the processes of backsliding in more depth, comparing six case-studies of populist governments, including longitudinal trends in the horizontal and vertical checks designed to prevent the executive abuse of power. The selected examples include presidential executives in Jair Bolsonaro’s Brazil, Recep Erdogan’s Turkey, and Donald Trump’s USA, as well as prime ministerial governments in Viktor Orban’s Hungary, Narendra Modi’s India, and Jarosław Kaczyński’s Poland. The conclusion in Part VI summarizes the key findings and considers their broader theoretical and policy implications. The chapter provides further evidence confirming the links connecting the rhetoric of populist parties with their endorsement of illiberal policies; at the same time, many exceptions to these findings can be observed, suggesting that diverse varieties of populist parties exist, even among neighboring states. The paper is drawn from Chapter 4 of my forthcoming book on The Cultural Roots of Democratic Backsliding (OUP 2027)

Categorization studies, in which stimuli vary along a category continuum, are becoming increasingly popular in psychological science. These studies demonstrate the effect of category ambiguity on various behavioral and neural measures. In such studies, researchers manipulate objective category levels by varying the physical properties of the stimuli, and then use these levels as predictors of behavior—assuming they map directly onto participants’ perceived locations along the category continuum. This approach might not be optimal, considering the variability in participants’ category boundary locations (their point of subjective equality, or PSE). In this tutorial, we propose addressing this issue by estimating participants’ individual points of subjective equality, adjusting category levels relative to these points, and conducting statistical analyses on the subjective category levels. Implementing this method significantly improves the statistical power of the analysis in both experimental and simulated data. Adjusting stimulus levels by the points of subjective equality is highly suited for social categorization studies, in which points of subjective equality vary significantly. On a broader scale, it can be applied to a variety of categorization, discrimination, and decision-making studies.

Intelligence organizations often fail to anticipate strategic developments even when relevant information is available because signals remain fragmented, ambiguous, overwhelming, or filtered through entrenched assumptions. The September 11 attacks, Russia’s 2022 invasion of Ukraine, and the October 7, 2023 Hamas attack illustrate how, even within some of the world’s most capable intelligence organizations, available indicators do not reliably translate into effective strategic warning, with outcomes shaped by differences in collection, interpretation, dissemination, and uptake. This article examines these failures and introduces AI-INT, or Artificial Intelligence Intelligence, as a response. AI-INT is an integrated, actor-specific synthesis-and-simulation layer within all-source analysis. It assembles and fuses relevant multi-source intelligence to build and update actor models, then uses them to run simulations at scale under systematically varied assumptions and conditions. It builds on wargaming’s value in deepening understanding, challenging assumptions, exposing blind spots, and exploring alternative trajectories by combining fused intelligence with LLM- and ML-based methods to expand the scenario space. As a bounded architectural illustration, the article presents SESBot, a Behavioral-AI framework for simulating the decision-making of selected Semi-State Terrorist Organizations (SESTOs). SESBot combines LLM-based agents with machine-learning behavioral anchors, illustrating one implementation of intelligence-grounded actor simulation within AI-INT. AI-INT’s promise lies not in predicting the future with certainty or replacing human judgment, but in helping analysts and decision-makers test assumptions, compare alternative scenarios, identify analytic blind spots, surface overlooked trajectories, connect them to monitorable indicators, and communicate uncertainty rigorously.

Since the enactment of the No Child Left Behind Act in 2001, states and public school districts have been held to increasingly higher accountability standards. This has led to more high-stakes assessments for students, and more focused attention on the achievement results data from those assessments. While the pressure to produce successful student outcomes continues to rise, two other factors have affected school districts’ ability to deliver. On the financial front, the past few years have seen greater budget constraints for public schools caused by the struggling American economy. Meanwhile, the rapidly increasing racial and ethnic diversification of the United States is outpacing school districts’ ability to adapt. Chesterfield County Public Schools, a large, suburban district in central Virginia, is experiencing each of these dynamics: increased accountability, a changing student population, and financial challenges. Although Chesterfield has traditionally been a high-performing school district, its overall student performance has declined in recent years. In an effort to sustain excellence, Chesterfield has increased its curriculum offerings and supports while maximizing its operational efficiency. However, those efforts have not turned the tide of declining test scores, particularly for its growing population of children of color. Education research has indicated that student achievement rises when teachers collaborate and use student data to plan and inform their instructional practice. The central question of this capstone is, how can student achievement data be used more effectively by teachers and administrators to drive instructional decision making in Chesterfield County’s schools? Chesterfield adopted the professional learning communities (PLC) model several years before the start of this project in 2013. However, the level of implementation of PLCs has been sporadic throughout the district. This capstone reviews the research on data use in education and the effectiveness of PLCs. It presents findings from the current state of data use in several schools based on interviews, focus groups, and observations, followed by an analysis of how Chesterfield can improve its data use for driving instruction. The capstone concludes with the study’s implications for myself, for Chesterfield, and for the education sector.

Despite efforts over the past twenty-five years at the federal, state and local level to create formal teacher leadership roles, the responsibilities of teachers in the public school system have remained stubbornly persistent. With few aberrations, the role of a teacher on his/her first day is likely to be very similar to her/his last (Donaldson et al., 2008). Recently, there are signs that this stability may be disrupted; new and diverse teacher leadership roles and career opportunities may be emerging in the sector. One prominent example of teachers taking significant leadership roles is Teach Plus’ Teacher Turnaround Team Initiative (T3). This program recruits, trains, and supports a cohort of effective and experienced teachers to play formal leadership roles within a turnaround school. T3 has a track record of results and is rapidly expanding to cities across the country. Designed as a three-year program, the initial cohort of schools in the first partner district is now ending the formal initiative and Teach Plus is faced with the important question of what type of support, if any, the organization should provide these schools post T3. My strategic project focused on creating a menu of options, in a fee for service model, in which the principals of schools exiting T3 could purchase is they desired to continue a level of partnership after the three year formal initiative ended. This Capstone Paper reviews the knowledge base surrounding teacher leadership with a particular focus on second stage teachers (70% of T3 Teacher Leaders have between 3-10 years experience). I then explain the strategic project in detail and offer an analysis with special attention to three different dimensions: 1) The impact on the specific project to the organization and the reasons for it’s success or failure. 2) The challenge of sustainability to the overall initiative. 3) The technical and adaptive challenges of expanding teacher leadership at scale in the education sector. Reviewing the lessons learned in research and through the project, I suggest that three main components would help shift T3 from a successful entrepreneurial start up to a sustainable approach to reform: 1) Identifying a permanent source of funding. 2) Incorporating principal leadership development into the program design. 3) Developing capacity at the district level to build an on-going system of support. I will also suggest that the T3 initiative has implications on the education sector at large. I argue that the T3 Initiative proves that with the proper support, teacher leadership has the potential to build the collective capacity for school turnarounds; that principal leadership matters and must be intentionally developed; and that scaling T3 requires districts to integrate innovative approaches to developing teacher leadership into the overall strategic human capital management of the district. Finally, I reflect on personal lessons learned and explain how the T3 Initiative reaffirmed my belief that ambitious reform initiatives require comprehensive support, collective ownership, and a plan for sustainability.