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The South Caucasus occupies the divide between ancient Mesopotamia and prehistoric Europe, and was thus crucial in the development of Old World societies. Chronologies for the region, however, have lacked the definition achieved in surrounding areas. Concentrating on the Tsaghkahovit Plain of north-western Armenia, Project ArAGATS's multi-site radiocarbon dataset has now produced Bayesian modelling, which provides tight chronometric support for tracing the transmission of technology, population movement and social developments that shaped the Eurasian Bronze and Iron Ages.
To describe the process by which the 12 community-based primary health care (CBPHC) research teams worked together and fostered cross-jurisdictional collaboration, including collection of common indicators with the goal of using the same measures and data sources.
A pan-Canadian mechanism for common measurement of the impact of primary care innovations across Canada is lacking. The Canadian Institutes for Health Research and its partners funded 12 teams to conduct research and collaborate on development of a set of commonly collected indicators.
A working group representing the 12 teams was established. They undertook an iterative process to consider existing primary care indicators identified from the literature and by stakeholders. Indicators were agreed upon with the intention of addressing three objectives across the 12 teams: (1) describing the impact of improving access to CBPHC; (2) examining the impact of alternative models of chronic disease prevention and management in CBPHC; and (3) describing the structures and context that influence the implementation, delivery, cost, and potential for scale-up of CBPHC innovations.
Nineteen common indicators within the core dimensions of primary care were identified: access, comprehensiveness, coordination, effectiveness, and equity. We also agreed to collect data on health care costs and utilization within each team. Data sources include surveys, health administrative data, interviews, focus groups, and case studies. Collaboration across these teams sets the foundation for a unique opportunity for new knowledge generation, over and above any knowledge developed by any one team. Keys to success are each team’s willingness to engage and commitment to working across teams, funding to support this collaboration, and distributed leadership across the working group. Reaching consensus on collection of common indicators is challenging but achievable.
In response to increased international collaboration in archaeological research of the South Caucases, a recent workshop has addressed important issues in applying GIS to the study of heavily modified landscapes in the former Soviet republics of Armenia, Azerbaijan and Georgia.
Undernutrition and non-communicable disease (NCD) are important public health issues in India, yet their relationship with dietary patterns is poorly understood. The current study identified distinct dietary patterns and their association with micronutrient undernutrition (Ca, Fe, Zn) and NCD risk factors (underweight, obesity, waist:hip ratio, hypertension, total:HDL cholesterol, diabetes).
Data were from the cross-sectional Indian Migration Study, including semi-quantitative FFQ. Distinct dietary patterns were identified using finite mixture modelling; associations with NCD risk factors were assessed using mixed-effects logistic regression models.
Migrant factory workers, their rural-dwelling siblings and urban non-migrants. Participants (7067 adults) resided mainly in Karnataka, Andhra Pradesh, Maharashtra and Uttar Pradesh.
Five distinct, regionally distributed, dietary patterns were identified, with rice-based patterns in the south and wheat-based patterns in the north-west. A rice-based pattern characterised by low energy consumption and dietary diversity (‘Rice & low diversity’) was consumed predominantly by adults with little formal education in rural settings, while a rice-based pattern with high fruit consumption (‘Rice & fruit’) was consumed by more educated adults in urban settings. Dietary patterns met WHO macronutrient recommendations, but some had low micronutrient contents. Dietary pattern membership was associated with several NCD risk factors.
Five distinct dietary patterns were identified, supporting sub-national assessments of the implications of dietary patterns for various health, food system or environment outcomes.
Missing outcome data plague many randomized experiments. Common solutions rely on ignorability assumptions that may not be credible in all applications. We propose a method for confronting missing outcome data that makes fairly weak assumptions but can still yield informative bounds on the average treatment effect. Our approach is based on a combination of the double sampling design and nonparametric worst-case bounds. We derive a worst-case bounds estimator under double sampling and provide analytic expressions for variance estimators and confidence intervals. We also propose a method for covariate adjustment using poststratification and a sensitivity analysis for nonignorable missingness. Finally, we illustrate the utility of our approach using Monte Carlo simulations and a placebo-controlled randomized field experiment on the effects of persuasion on social attitudes with survey-based outcome measures.
This article challenges the idea, both in domestic and international law, of defining terrorism. Using section 1 of the UK's Terrorism Act 2000 as an illustrative example, this article argues that a single definition of terrorism is invariably broad owing to the need to accommodate the lowest common denominator. This is damaging to the ‘principle of legality’ as recognized in British public law and the ECHR. Moreover, this problem is further exacerbated by the increasing application of counterterrorism legislation to non-international armed conflicts. This article therefore suggests an alternative solution: multiple definitions of terrorism whose breadth is dependent upon the specific circumstances for which they are designed. Fears that such an approach may amount to an ‘expression of inconsistency’ will be addressed by arguing that law's capacity to shape and frame public and political debate on the concept of terrorism is over-exaggerated. Legal definitions of terrorism therefore should remain primarily concerned with the legal rather than political function of defining terrorism.
In the social sciences, randomized experimentation is the optimal research design for establishing causation. However, for a number of practical reasons, researchers are sometimes unable to conduct experiments and must rely on observational data. In an effort to develop estimators that can approximate experimental results using observational data, scholars have given increasing attention to matching. In this article, we test the performance of matching by gauging the success with which matching approximates experimental results. The voter mobilization experiment presented here comprises a large number of observations (60,000 randomly assigned to the treatment group and nearly two million assigned to the control group) and a rich set of covariates. This study is analyzed in two ways. The first method, instrumental variables estimation, takes advantage of random assignment in order to produce consistent estimates. The second method, matching estimation, ignores random assignment and analyzes the data as though they were nonexperimental. Matching is found to produce biased results in this application because even a rich set of covariates is insufficient to control for preexisting differences between the treatment and control group. Matching, in fact, produces estimates that are no more accurate than those generated by ordinary least squares regression. The experimental findings show that brief paid get-out-the-vote phone calls do not increase turnout, while matching and regression show a large and significant effect.
Randomized experiments commonly compare subjects receiving a treatment to subjects receiving a placebo. An alternative design, frequently used in field experimentation, compares subjects assigned to an untreated baseline group to subjects assigned to a treatment group, adjusting statistically for the fact that some members of the treatment group may fail to receive the treatment. This article shows the potential advantages of a three-group design (baseline, placebo, and treatment). We present a maximum likelihood estimator of the treatment effect for this three-group design and illustrate its use with a field experiment that gauges the effect of prerecorded phone calls on voter turnout. The three-group design offers efficiency advantages over two-group designs while at the same time guarding against unanticipated placebo effects (which would undermine the placebo-treatment comparison) and unexpectedly low rates of compliance with the treatment assignment (which would undermine the baseline-treatment comparison).
Regression discontinuity (RD) designs enable researchers to estimate causal effects using observational data. These causal effects are identified at the point of discontinuity that distinguishes those observations that do or do not receive the treatment. One challenge in applying RD in practice is that data may be sparse in the immediate vicinity of the discontinuity. Expanding the analysis to observations outside this immediate vicinity may improve the statistical precision with which treatment effects are estimated, but including more distant observations also increases the risk of bias. Model specification is another source of uncertainty; as the bandwidth around the cutoff point expands, linear approximations may break down, requiring more flexible functional forms. Using data from a large randomized experiment conducted by Gerber, Green, and Larimer (2008), this study attempts to recover an experimental benchmark using RD and assesses the uncertainty introduced by various aspects of model and bandwidth selection. More generally, we demonstrate how experimental benchmarks can be used to gauge and improve the reliability of RD analyses.
The debate about the cost-effectiveness of randomized field experimentation ignores one of the most important potential uses of experimental data. This article defines and illustrates “downstream” experimental analysis—that is, analysis of the indirect effects of experimental interventions. We argue that downstream analysis may be as valuable as conventional analysis, perhaps even more so in the case of laboratory experimentation.
If the publication decisions of journals are a function of the statistical significance of research findings, the published literature may suffer from “publication bias.” This paper describes a method for detecting publication bias. We point out that to achieve statistical significance, the effect size must be larger in small samples. If publications tend to be biased against statistically insignificant results, we should observe that the effect size diminishes as sample sizes increase. This proposition is tested and confirmed using the experimental literature on voter mobilization.
Africa has seen a steady rise in democracy since the end of the Cold War. This paper investigates two possible implications of democratization in African countries: better economic growth through improved institutions and less civil conflict through increased political participation. Instrumental variables regressions are estimated with the spatial lag of democracy. This instrument varies over time, allowing for consideration of country fixed effects in IV regressions. Large positive impacts of institutions on economic growth and of political participation on reducing civil conflict are found in IV regressions with fixed effects. Further estimates show that both growth and civil violence effects may be driven by civil liberties.
Field experiments on voter mobilization enable researchers to test theoretical propositions while at the same time addressing practical questions that confront campaigns. This confluence of interests has led to increasing collaboration between researchers and campaign organizations, which in turn has produced a rapid accumulation of experiments on voting. This new evidence base makes possible translational works such as Get Out the Vote: How to Increase Voter Turnout that synthesize the burgeoning research literature and convey its conclusions to campaign practitioners. However, as political groups develop their own in-house capacity to conduct experiments whose results remain proprietary and may be reported selectively, the accumulation of an unbiased, public knowledge base is threatened. We discuss these challenges and the ways in which research that focuses on practical concerns may nonetheless speak to enduring theoretical questions.
We use newly available micro-data from the 1911 to 1941 Canadian Censuses to investigate the impact of immigration on the Canadian earnings distribution in the first half of the twentieth century. We show that Canadian inequality rose sharply in the inter-war years, particularly in the 1920s, coinciding with two of the largest immigration decades in Canadian history. We find that immigration was not the main force driving changes in the earnings distribution. This results from a combination of self-selection by immigrants, occupational adjustments after arrival, and general equilibrium adjustments in the economy.
Dietary patterns analysis is an emerging area of research. Identifying distinct patterns within a large dietary survey can give a more accurate representation of what people are eating. Furthermore, it allows researchers to analyse relationships between non-communicable diseases (NCD) and complete diets rather than individual food items or nutrients. However, few such studies have been conducted in developing countries including India, where the population has a high burden of diabetes and CVD. We undertook a systematic review of published and grey literature exploring dietary patterns and relationships with diet-related NCD in India. We identified eight studies, including eleven separate models of dietary patterns. Most dietary patterns were vegetarian with a predominance of fruit, vegetables and pulses, as well as cereals; dietary patterns based on high-fat, high-sugar foods and more meat were also identified. There was large variability between regions in dietary patterns, and there was some evidence of change in diets over time, although no evidence of different diets by sex or age was found. Consumers of high-fat dietary patterns were more likely to have greater BMI, and a dietary pattern high in sweets and snacks was associated with greater risk of diabetes compared with a traditional diet high in rice and pulses, but other relationships with NCD risk factors were less clear. This review shows that dietary pattern analyses can be highly valuable in assessing variability in national diets and diet–disease relationships. However, to date, most studies in India are limited by data and methodological shortcomings.
This paper compares and contrasts state emergency responses to national security crises with responses deployed in a period of economic crisis. Specifically, this paper challenges the appropriateness and legitimacy of the standard emergency response of legislative (as distinct from judicial) deference to the executive when confronting such economic crises. This will be done by questioning the significance in periods of economic crisis of the two principal factors that justify deferring to the executive during a state of emergency pertaining to national security: (i) the necessity of the action taken; and (ii) that the executive has an expertise in decision making in the specific area in question. Ultimately, this paper questions the application of the emergency paradigm to economic crises, arguing that such responses are rarely temporary and instead usher in a ‘new normalcy’.