Interrupted Terms, Frustrated Careers? The Political Continuity of Cabinet Ministers Affected by Presidential Interruptions

Legislative efforts to bring consistency to criminal sentencing outcomes has been much discussed in academic literature and Congressional hearings alike. Despite these efforts disparate sentencing outcomes persist. Researchers have studied many variables seeking to understand these disparities but have been unable to form a consensus around the cause. Perhaps because of the lack of a firm understanding of the issue among researchers, legislative intervention at both the state and federal level has largely failed to address the issue of judicial characteristics that may drive sentencing disparities. As a result, absent from the conversation on criminal sentencing reform is empirical and anecdotal evidence about how judges make determinations within the range of outcomes specified by the legislature. New data on federal sentencing outcomes collected by Harvard researchers, however, finds a direct connection between the political party of the President who appointed the federal judge and the length of a defendant’s sentence. As the Harvard study reports, federal judges appointed by Republican presidents sentence defendants on average to three more months in prison than federal judges appointed by Democratic presidents. Republican-appointed judges in the federal system also sentence black defendants more harshly than Democratic-appointed judges. As will be discussed in this Article, the central premise of the Harvard political sentencing study – that judicial political affiliation influences sentencing outcomes, even those that are highly guided by legislative criteria – also holds true on the state level with respect to elected, rather than appointed, judges. As we report, empirical evidence from the state of Ohio demonstrates that elected Republican judges sentence defendants to lengthier terms of incarceration than elected Democratic judges by a statistically significant margin. This evidence suggests that, rather than being entirely guided by specified statutory criteria, judges bring preexisting sentencing ideologies to the bench and make decisions with a range of sentencing outcomes based at least in part on their individual philosophies and beliefs. Based on these findings, we argue that in order to address the issue of sentencing disparities, reform efforts should take action to specifically address the behavior and motivation of individual judges.

Recent advancements in computing power and machine learning techniques have facilitated the digitization of new corpora, as well as new methods for studying high-dimensional data. This has enabled empirical investigations of fundamental questions in the social sciences that were previously restricted by technical limitations or data availability. In this note, we introduce a new dataset covering debates in the Norwegian Parliament in the 1945-2024 period. This dataset, which covers close to one million speeches, includes information about speeches (full text, date of speech, and chamber), speakers’ status (parliamentary president, member of parliament, deputy member of parliament, or cabinet minister), as well as speaker background characteristics (party affiliation, committee membership, district affiliation, rank on electoral lists, gender, and birth year). This dataset will enable extensive research into political representation in a party-centered electoral framework. More broadly, this dataset serves as a vital resource for interdisciplinary research, enabling studies on the evolution of language, rhetoric, and the broader socio-economic factors influencing legislative behavior.

Governor's Party, Policies, and COVID-19 Outcomes: Further Evidence of an Effect

During the last 50 years, political polarization in the US House of Representatives has intensified. One explanation for this trend emphasizes the importance of congressional redistricting. This paper analyzes the relationship between political polarization and redistricting in the context of two trade liberalization bills. The results of the paper indicate that redistricting has not contributed significantly to party polarization over trade policy although it has produced a partisan shift in favor of trade liberalization. Redistricting does not appear to impact political polarization largely because district-level characteristics currently are dominated by broader, national factors such as party affiliation. The results of the paper clearly demonstrate this point by showing that changes in party affiliation have a much greater impact on voting behavior than changes in district characteristics. The paper also finds, however, that institutional control of the redistricting process at the state level has influenced political polarization with respect to trade policy.

Response to intervention (RTI) is receiving significant national attention. For many schools and districts, and even a few states, RTI has been “in the works” for several years. While empirical evidence regarding RTI continues to be collected and reviewed, its popularity with parents and educators can be viewed as a function of dissatisfaction with the traditional approach (i.e., achievement— ability discrepancy) and a desire for more immediate and meaningful solutions for struggling students. Questions surrounding RTI implementation at the building level are practical in nature. What are the time and resource requirements to carry out effective interventions? What constitutes research-based interventions and practices? What is the relevant definition of “response”? How does RTI impact regular education? And how does RTI impact special education resources within a building? At the district and state levels, RTI raises additional issues, including how it will impact the percentage of students who qualify for special education, how to provide large-scale trainings and support, and how to ensure proper and uniform practice within schools. This chapter provides insights to the questions posed regarding implementation and ongoing practice of RTI, both at the state and local levels. It provides a description of Idaho’s statewide implementation of RTI, also known in Idaho as the Results-Based Model (RBM). This chapter emphasizes the major lessons learned at the local and state levels as a result of experience, program evaluation, and school feedback. Cautionary recommendations along with implications for practice are offered.

Is declining groundwater levels linked with the discontinuity of traditional water harvesting systems (tank irrigation)? Empirical evidence from West Bengal, India

PurposeThis paper is motivated by the gap between the extensive academic discussion of industrial resilience and the limited resilience observed in response to large disruptions. Its purpose is to investigate the relationship between the industrial resilience of manufacturing and service operations and the resilience of the supporting financial, legal and political systems. This research identifies the impact of high or low levels of resilience in these supporting systems on the ability of industrial operations to perform as required in disrupted environments.Design/methodology/approachThe authors combine a multi-disciplinary literature review with empirical data from four exploratory case studies. First, the authors review the literature on resilience in the fields of operations management, finance, law and political science to bring the terminology and concepts of these fields closer together. This review also defines the independent variables of the study: financial, legal and political resilience. Second, the authors use the framework from the literature to analyse data from four case studies of operations in difference contexts and sectors.FindingsIndustrial resilience is interdisciplinary, nuanced and complex. High levels of industrial resilience require high levels of financial, legal and political resilience. However, the activities required to improve the resilience of these supporting systems are often outside the locus of control of operations managers. Multiple perspectives on resilience must be coordinated to strengthen the response of industrial operations to large disruptions.Research limitations/implicationsAs a conceptual and exploratory study, this paper does not utilise quantitative data or in-depth case studies. The authors demonstrate the importance of an interdisciplinary perspective on industrial resilience and provide a theoretical framework that can serve as a foundation to further studies of resilience. The review of the literature provides a glossary of definitions of resilience that improves clarity in this disparate field.Practical implicationsManagers can apply the findings of this work to start cross-functional discussions in their firms that recognise the multiple dimensions of industrial resilience and improve the resilience of the supporting systems. The exploratory case studies provide concrete guidance for how managers in the fields of humanitarian and development operations, healthcare and manufacturing can improve industrial resilience by considering the interaction with the supporting financial, legal and political systems.Originality/valueThis study is the first to provide detailed conceptual discussion and empirical evidence for the interdisciplinary nature of industrial resilience in the context of public sector and non-governmental organisations. Combining evidence from different contexts and sectors demonstrates the broad industrial value of this work.

When it comes to environmental quality preferences, it is popularly believed that Democrats (and more generally, liberals) are “green” while Republicans” (conservatives) are “brown”. Does empirical evidence support this popular belief? We test the hypothesis that regional political identification leads to differences in concentration outcomes for several measures of California air pollution indicators, including CO, NO2, SO2, O3, PM10, and PM2.5 concentrations. We employ two alternative identification strategies on county-level cluster and year panel data that include proxy variables for political party preferences of the local populace, as well as controlling for the political party affiliations at the state-level legislative and executive branches. In general, we do not find a consistent and statistically significant relationship between pollution outcomes and political variables for California. The popular belief is empirically supported only for NO2 and O3, but not for any of the other pollutants, and even in these two cases the relationship only holds at the local regulatory level and not at the state policymaking level. At the state level, for most of the pollutants no significant effect of party affiliation is identified, and in the rare cases where such an effect exists, it is either too weak to be conclusive or is even counter to popular belief.

When it comes to environmental quality preferences, it is popularly believed that Democrats (and more generally, liberals) are “green” while Republicans” (conservatives) are “brown”. Does empirical evidence support this popular belief? We test the hypothesis that regional political identification leads to differences in concentration outcomes for several measures of California air pollution indicators, including CO, NO2, SO2, O3, PM10, and PM2.5 concentrations. We employ two alternative identification strategies on county-level cluster and year panel data that include proxy variables for political party preferences of the local populace, as well as controlling for the political party affiliations at the state-level legislative and executive branches. In general, we do not find a consistent and statistically significant relationship between pollution outcomes and political variables for California. The popular belief is empirically supported only for NO2 and O3, but not for any of the other pollutants, and even in these two cases the relationship only holds at the local regulatory level and not at the state policymaking level. At the state level, for most of the pollutants no significant effect of party affiliation is identified, and in the rare cases where such an effect exists, it is either too weak to be conclusive or is even counter to popular belief.

When it comes to environmental quality preferences, it is popularly believed that Democrats (and more generally, liberals) are “green” while Republicans” (conservatives) are “brown”. Does empirical evidence support this popular belief? We test the hypothesis that regional political identification leads to differences in concentration outcomes for several measures of California air pollution indicators, including CO, NO2, SO2, O3, PM10, and PM2.5 concentrations. We employ two alternative identification strategies on county-level cluster and year panel data that include proxy variables for political party preferences of the local populace, as well as controlling for the political party affiliations at the state-level legislative and executive branches. In general, we do not find a consistent and statistically significant relationship between pollution outcomes and political variables for California. The popular belief is empirically supported only for NO2 and O3, but not for any of the other pollutants, and even in these two cases the relationship only holds at the local regulatory level and not at the state policymaking level. At the state level, for most of the pollutants no significant effect of party affiliation is identified, and in the rare cases where such an effect exists, it is either too weak to be conclusive or is even counter to popular belief.

Welfare reform has once again made its way to the top of the domestic policy agenda. While part of the motivation behind recent reform efforts is fiscally driven, there is also an interest in making changes that address two prominent criticisms of the existing system of public assistance in the United States. First, the system has significant, adverse work incentives. Second, the system discourages the formation of two-parent families and is responsible in a major part for the high and rising rates of female headship and out-of-wedlock birth rates. This paper explores the validity of these criticisms using available empirical evidence and in turn evaluates the impact of various reforms to the system. The programs examined include Aid to Families with Dependent Children Food Stamps and Medicaid programs. The paper relies on evidence based on three sources of variation in welfare policy: cross-state variation, over time variation, and demonstration projects at the state level. The paper concludes that current reforms aimed at reducing female headship and nonmarital births such as family caps, eliminating benefits for teens, and equal treatment of two-parent families are unlikely to create large effects. Changes to implicit tax rates and benefit formulas may increase work among current recipients, but overall work effort may not be affected. These predictions should be accompanied by a word of caution. Many of the proposed changes have never been implemented at the state or federal level and require out of sample predictions. Current state experimentation may help fill this gap.

What explains Romanian parties’ preference to form minority cabinets? Does the minority status of cabinets affect stability or performance? First, this chapter presents empirical evidence in favor of the important role of the country’s semi-presidential regime structure in minority cabinet formation. Second, the chapter finds that individual political goals and informal institutions—such as corruption and clientelism—play a fundamental role in making and breaking parliamentary alliances. These latter phenomena often shape legislative majorities, making individuals highly dependent on state resources and loosely bonded to a specific party. Third, this chapter comes in support of more recent scholarship that minority cabinets are neither situational nor do they necessarily perform poorly. However, even in this high volatility environment, minority cabinet duration and performance may improve when parties sign a substantive agreement that signals long-term commitment to shared governance, or when they have the support of the main ethno-regional parties.

Summary form only given. China has 53 Science and Technology Industrial Parks (STIPs) at state level. The purpose of the STIPs is to establish and develop new and high-tech industries in China with a market orientation. After a preliminary stage of development, the STIPs have greatly promoted China's economy. However, these parks differ in many respects, such as founding time, infrastructure, intelligence basis, operation mechanism, effects, investment environment, management level, economic scale, developing emphasis, etc. In order to strengthen the management of STIPs, it's very important for the government to know the difference and similarity among these parks. Evaluation should be considered as an essential component of management. The Chinese government has committed to evaluating the STIPs for years. Despite that, it has not found a perfect method to evaluate. As far as we know, no study of evaluation on these complex parks has been conducted with clustering methods, which we consider a valuable attempt. Cluster analysis is employed in this paper and some new methods are used to analyze the cluster results, such as multidimensional clustering and trend analysis by clusters changing. In this investigation, the principal component analysis is dealt with first, and then hierarchical agglomerative methods are applied to cluster STIPs, and finally we make use of discriminant analysis to determine whether the cluster results differ from each other.

The case for state-level drinking water affordability programs: Conceptual and empirical evidence from California

PurposeThe present paper makes an attempt to investigate the determinants that affect FDI inflows distribution among Indian states. Together with traditional determinants, the impact of institutional determinants on state-level FDI inflows distribution in India has been analysed.Design/methodology/approachThe study uses panel data for a period of 20 years (2000–2019) for 17 groups of Indian states (29 states and 7 UTs). The empirical evidence is based on the panel data method and the findings support Dunning's OLI theory. As the data for some indicators for the institutional environment is not available at the state level, hence we used component analysis to arrive at the single component for the institutional factor. The study takes into account corruption, legal system, industrial disputes, man-days lost, labour availability, political risk, protection of IPR and agglomeration as potential macroeconomic and institutional determinants.FindingsResults show that FDI inflows into Indian states is driven mainly by institutional environment. From our analysis, the author infers that the institutional variables such as legal system, IPR, corruption, political instability play an important role in determining the distribution of FDI inflows at the state level in India. Together with that GFCF and agglomeration are also important determinants of state-wise FDI inflows.Research limitations/implicationsThe major limitation of the study is that it doesn't include moderated impact of economic and institutional determinants of FDI inflows in Indian states, which can be an avenue for future research. Future research can also carried out taking district-level data to further examine the determinants at district level in India.Originality/valueThe contribution of the present paper is three-fold, first, the author constructs a measure of different institutional variables, after normalization of data for the period 2000–2019, and the author choose the highest explaining factor with the highest variance explained then we constructed the indices for select variable, which further has been used in the panel data analysis technique. The author has found that macroeconomic variables, as well as institutional variables, are significant to attract FDI at the state level in India. The paper shows that corruption, political risk, IPR and legal system are the major institutional determinants of FDI inflows in India at the state level. States with higher domestic investment attract more FDI inflows, moreover, agglomeration is a very important determinant as the investors are more confident in investing at the same location, the reason behind this may be that the investors want to avoid the registration procedure for new land, administrative formalities or they feel more secure at the same place and keen to invest at the same place again.