Selecting Constitutional Judges Randomly

This article discusses from the perspective of democratic theory an innovative proposal for the selection of constitutional, supreme court, or federal judges that aims at combining the values of expertise and political independence. It consists in combining a certification process – selecting a pool of properly qualified candidates – with a random selection among this pool. We argue that such selection procedure would better respect the separation of powers and the specific legitimacy of courts, and we champion this two‐stage mechanism vis‐à‐vis other, more traditionally employed, selection procedures. We then deal with a diversity of objections to our proposal and conclude by taking stock of both its virtues and limitations.     

Further Pseudo-Operational Trials with the Lumicyano Double- and Co-Fuming Process for the Detection of Latent Fingermarks

This study presents a number of pseudo-operational trials on plastic bags investigating the double- and co-fuming process of a one-step fluorescent cyanoacrylate (Lumicyano^TM) in comparisons with the two-step process with basic yellow 40 (BY40) staining for the detection of latent fingermarks. The results demonstrate that both Lumicyano solution and dye contribute to the increased detection of latent fingermarks during the double-fuming process (trial 1). Co-fuming the Lumicyano solution and dye separately (at a concentration of 8%) but simultaneously was less effective than 8% Lumicyano (trial 2). Co-fuming Lumicyano 8% and an additional 8% Lumicyano dye by weight was more effective than Lumicyano 8% (trial 3), possibly due to increased fluorescent material deposition during co-fuming allowing for better visualization. The use of BY40 after Lumicyano resulted in a considerable increase in detected fingermarks.     

An experimental trial of a dog-training program in a juvenile detention center

Journal of Experimental Criminology - This research examines the effect of a dog-training program among juveniles ordered to a county juvenile detention facility in a large, Midwestern city. A...     

Analyzing block randomized studies: the example of the Jersey City drug market analysis experiment

Objectives

While block randomized designs have become more common in place-based policing studies, there has been relatively little discussion of the assumptions employed and their implications for statistical analysis. Our paper seeks to illustrate these assumptions, and controversy regarding statistical approaches, in the context of one of the first block randomized studies in criminal justice—the Jersey City Drug Market Analysis Project (DMAP).

Methods

Using DMAP data, we show that there are multiple approaches that can be used in analyzing block randomized designs, and that those approaches will yield differing estimates of statistical significance. We develop outcomes using both models with and without interaction, and utilizing both Type I and Type III sums-of-squares approaches. We also examine the impacts of using randomization inference, an approach for estimating p values not based on approximations using normal distribution theory, to adjust for possible small N biases in estimating standard errors.

Results

The assumptions used for identifying the analytic approach produce a comparatively wide range of p values for the main DMAP program impacts on hot spots. Nonetheless, the overall conclusions drawn from our re-analysis remain consistent with the original analyses, albeit with more caution. Results were similar to the original analyses under different specifications supporting the identification of diffusion of benefits effects to nearby areas.

Conclusions

The major contribution of our article is to clarify statistical modeling in unbalanced block randomized studies. The introduction of blocking adds complexity to the models that are estimated, and care must be taken when including interaction effects in models, whether they are ANOVA models or regression models. Researchers need to recognize this complexity and provide transparent and alternative estimates of study outcomes.

     

Causal inference and American political development: common challenges and opportunities

Public Choice - The causal inference (CI) movement has forced political scientists to think far more seriously about what can be learned from a particular research design and to be more attentive...     

Exploring the Effects of North–South and South–South Research Collaboration in Emerging Economies,the Colombian Case

International research collaboration (IRC) is associated with both positive and negative effects on the performance of research in emerging economies. While some authors claim that North–South collaborations improve scientific quality and visibility for Southern countries, others claim that it may entail the reorientation of research to comply with Northern agendas. South–South collaborations are thought to increase the focus on local affairs, therefore leading to a relatively small number of scientific international publications appearing in “high quality” journals. Research on the impact of IRC beyond publications in international journals has been neglected despite the importance of other products in knowledge creation. This research uses a broad range of scientific outputs to empirically assess such assumptions and explore the outcomes of IRC in Colombia. Results from multivariate regressions and nonparametric analyses show that, contrary to common assumptions, Colombian research teams collaborating with partners from the global South report higher scientific production, while those collaborating with Northern countries seem to contribute to local knowledge the most.     

Varieties of consumer credit data regimes: A regulatory governance approach

Credit markets are expanding, and with them also the automated, large‐scale commercialization of personal credit data. The increasing use of data and scores for commodified decision making lends greater urgency to the study of credit data regulatory regimes. This article promotes a comparative regulatory governance perspective as the basis for theory‐driven, multidimensional measurement. In order to measure consumer protection, we distinguish three different subregimes (collection, profiling, and use) and construct a two‐dimensional index of consumer protection (market restriction and user empowerment). We then assess the index and demonstrate its applicability and validity, building on empirical analysis of the regulatory regimes in the United States, France, Sweden, and Israel for the year 2019. Our approach points to a new direction in researching and measuring regulatory regimes in a comparative manner, which looks beyond national analysis toward an in‐depth understanding of other, equally important, levels of variation.