Evaluation Review最新文献

This paper presents the process of conducting a community-wide needs assessment that initially focused on soliciting information about childcare needs of families with school-aged children. The researchers were interested in understanding whether the method designed to conduct the needs assessment helped to foster collaboration, trust, and increased participation amongst multiple levels of stakeholders and subcommunities. Utilizing community-based participatory research principles, the authors will present a 3-phase approach to gaining community support through multiple levels of stakeholder engagement. While initially the needs assessment was focused on childcare, the scope broadened to learning about other needs that families with school-aged children faced. The strategic use of Survey Ambassadors throughout the community who could access families that were typically underrepresented and could provide feedback to the researchers in real time regarding modifications to the process was vital. Lessons learned included the need for further investigation into strategic methods for gaining family voices in underrepresented populations.

With an educational issue that has caught the attention of many countries in the world (study load), a population of 8th graders from a typical Chinese metropolitan city (40,536 from 118 schools), and an advanced statistical strategy (multilevel piecewise regression), we examined whether there was a turning point in terms of the effects of study load on science achievement. We did identify a turning point for each and every measure of study load. For weekday learning on science achievement, we identified a turning point of 22.50 hr for the effects of in-school learning, 7.50 hr for the effects of homework, and 12 hr for the effects of after-school learning. For weekend learning on science achievement, we identified a turning point of 1.50 hr for the effects of in-school learning, 5 hr for the effects of homework, and 1 hr for the effects of after-school learning. In each case, the difference in effects before and after the turning point was statistically significant, indicating that the effects of study load on science achievement were nonlinear. All of these turning points offered important implications for science education.

Intelligence-led policing (ILP) was introduced in the 1990s as a proactive approach to policing, but to date, there is a lack of studies that have synthesized and summarized the central characteristics and insights of (quasi-)experimental studies related to ILP. This study aims to address this gap by synthesizing and characterizing the central characteristics of 38 quasi-experimental and experimental studies related to ILP. In this study, a scoping review is conducted on different quasi-experimental and experimental studies that relate to the framework of ILP. It was found that most studies within the domain of ILP focus on testing the crime reduction effects of using spatio-temporal crime intelligence to deploy police resources more efficiently and effectively. However, some studies have combined different types of crime intelligence or used solely offender-related intelligence. Several statistical-methodological challenges were also identified that should be considered when designing experimental research within the domain of ILP. Additionally, most studies focused solely on measuring crime reduction, with few focusing on secondary effects of interventions. The review concludes that future evaluation studies should consider evaluating the use of different types of crime intelligence and establish specific, objective, and realistic criteria for measuring specific performance measures such as crime disruption. Future experimental research within the domain of ILP should consider applying the 3-i model, evaluating each leg of ILP thoroughly. The limitations of the study are also discussed. This review provides valuable insights for future research and development of ILP-related approaches.

This study examines the relationship between foreign direct investment (FDI), institutional quality and human development) in host countries from 2002 to 2019, using the Human Development Index [HDI] as the measure of human development. This study utilized a panel dataset of 143 countries, including both developed and developing economies, over a 17-year period. Additionally, the study employed a GMM (generalized method of moments) estimator to address unobservable heterogeneity and simultaneity. This study reveals a significant positive relationship between FDI and human development, with a stronger effect observed in developing countries compared to in developed countries. Notably, the impact of FDI-HDI nexus is larger in countries with moderately high-quality institutions, irrespective of their income level. Furthermore, good governance plays a crucial role in enhancing human development, as developing economies with high governance quality experience a greater impact of FDI on HDI compared to other countries. The findings of this study suggest that attracting FDI can be beneficial for enhancing the HDI, especially in developing countries. Additionally, the study highlights governance as a moderating factor in the relationship between FDI and HDI. Improving governance quality can enhance the positive impact of FDI on human development in host countries, especially in developing countries.

To improve one of the lowest rates of literacy and numeracy in the world, the government of Brazil has targeted public education reform, given the strong link between an educated population and economic growth. This study examines the academic performance of the Brazilian public primary school system. It addresses the empirical shortcomings of prior research to examine the dynamics of the relationship between academic performance scores and several demographic and institutional variables, such as socioeconomic characteristics, variations in school infrastructure and school complexity, and teachers' human capital. We employed quantile regression to explore the determinants of academic performance across 35,490 schools in rural and urban environments in Brazil. The dependent variable in our analysis captures the academic performance score, as measured by Brazil's education authorities, of each school in our dataset. The model includes several education-related indices used in prior research and, as explanatory factors, measures of teachers' human capital and the students' socioeconomic level, which synthesizes information on parents' education and household income. The results suggest that several institutional variables, including access to school libraries, computer facilities, projectors, and televisions, are positively and significantly related to the academic performance of primary students in Brazil's system of public education. Furthermore, students' socioeconomic level is positively associated with their academic performance.

Successfully designing and implementing a program is complex; it requires a reflexive balance between the available resources and the priorities of various stakeholders, both of which change over time. Logic models are theory-based evaluation approaches used to identify and address key challenges of a program. This article describes the process of building a logic model on advanced theories in complexity studies. The models aim to support a province-wide multispecies monitoring system of antimicrobial use (AMU), designed in collaboration with the animal health sector in Quebec (Canada). Based on a rigorous theoretical foundation, the logic model is built in three steps: (1) mapping, a narrative review of literature on similar programs in other jurisdictions; (2) framing, iterative consultations with project members to elaborate the logic model; (3) shaping, hypotheses based on the logic model. The model emerges from the reflexive balancing of current scientific knowledge and empirical insights to gather relevant information about stakeholders from interdisciplinary experts that led a 3-year consensus-building process within the community. Recognizing the challenge of unpacking theories for practical use, we illustrate how the process of an "open" logic model building could enable governance coordination in complex processes. Logic models are useful for evaluating public, private, and academic partnerships in One Health programs that characterize an adaptive governance process.

Sustainable agriculture is crucial for achieving SDG2 and building a resilient climate-food system. This study provides a nuanced understanding of factors that influence the adoption of precision agriculture technology by Vietnamese smallholder rice farmers as a sustainable agricultural solution. The study's objectives are: (1) to provide a nuanced understanding of factors that influence adoption of precision agriculture technology by Vietnamese smallholder rice farmers; and (2) to identify factors associated with agricultural practice in Vietnam that may impact the adoption of precision agriculture technology. The study conducted 35 semi-structured interviews with smallholder rice farmers and agriculture experts. Data were analyzed using iterative thematic analysis. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was used for empirical analysis. The UTAUT constructs of Performance expectancy, Effort expectancy, Government support, and Social influence were found to be determinants of adoption. Trialability and Observability impact Effort expectancy and Performance expectancy. We also discovered that the performance of agricultural cooperatives and support of lead firms play a crucial role in facilitating agricultural technology adoption by Vietnamese smallholder rice farmers. The results confirm the applicability of UTAUT in defining smallholders' behavioural intention and predicting agricultural technology adoption. The study also provides constructive feedback on the UTAUT model by highlighting the effect of agricultural cooperatives' performance as innovation intermediaries and of the support of lead firms.

The COVID-19 pandemic has exacerbated the local debt in Spanish municipalities with negative consequences on the macroeconomic financial stability at national and eurozone level. The main objective is to identify the causes of public debt per capita in four groups of Spanish municipalities according to size. It is based on a quantitative analysis based on correlational and causal-comparative approaches. It consists in the construction of panel quantile regressions (MMQ) and mean group (ME) estimators to explain public debt per capita in Spanish municipalities. Moreover, the Juodis test for causality analysis in panel data is applied. The research is constructed around various types of potential determinants related to economic factors (GDP per capita and unemployment rate), demographic factors (population under 15 and population over 65), and political factors (political party, ideology, and political strength). The results based on MMQR for the period 2011-2020 indicate common factors that reduce local debt (short-run economic growth), but also differences between clusters in what concerns factors that increase or decrease the debt. The Juodis et al. (2021) test shows that growth and unemployment are factors that influence the level of public debt in all groups of municipalities except one (5001-20,000 inhabitants) where political party affects debt. These empirical findings support policy proposals to reduce the local debt in Spanish municipalities. The main initiatives to reduce debt should be based on the promotion of economic growth and creation of new jobs, especially for young people.