This study examines the impact of parliamentary thresholds on the Indonesian political system through the lens of the Routine Policy Implementation Model and the Strategic Policy Implementation Model. The main objective is to evaluate the effectiveness of parliamentary thresholds in managing political fragmentation, assess their impact on stability and representation in the legislative system, and understand their implementation’s technical and strategic implications. Using a qualitative approach supported by interview studies and field observations, this research combines analysis of election data in the 2009, 2014, and 2019 elections with a qualitative assessment of policy changes and political dynamics. The Routine Policy Implementation Model focuses on the technical aspects of threshold implementation, including vote counting procedures and seat allocation efficiency. Meanwhile, the Strategic Policy Implementation Model examines the broader implications of these thresholds for political consolidation, government effectiveness, and the representation of minor parties. The results show that the parliamentary threshold has significantly reduced political fragmentation by consolidating the number of parties in Parliament, resulting in a legislative system that is cleaner and easier to administer. However, this consolidation has also marginalized small parties and limited political diversity. The novelty of this study lies in its comprehensive analysis of how parliamentary thresholds affect administrative efficiency and strategic political stability in Indonesia, compared to democratic countries in transition, such as Slovenia and Montenegro. In conclusion, although parliamentary thresholds have increased political stability and government effectiveness, they have also raised concerns about the reduced representation of small and regional parties. The study recommends maintaining balanced thresholds that ensure stability and diversity, implementing mechanisms to review thresholds periodically, and involving diverse stakeholders in adjusting policies to reflect evolving political dynamics. This approach will help balance the need for a stable legislative environment with broad representation.

Although the problems created by exceeding Earth’s carrying capacity are real, a too-small population also creates problems. The convergence of a nation’s population into small areas (i.e., cities) via processes such as urbanization can accelerate the evolution of a more advanced economy by promoting new divisions of labor and the evolution of new industries. The degree to which population density contributes to this evolution remains unclear. To provide insights into whether an optimal “threshold” population exists, we quantified the relationships between population density and economic development using threshold regression model based on the panel data for 295 Chinese cities from 2007 to 2019. We found that when the population density of the whole city (urban and rural areas combined) exceeded 866 km⁻², the impact of industrial upgrading on the economy decreased; however, when the population density exceeded 15,131 km⁻² in the urban part of the cities, the impact of industrial upgrading increased. Moreover, it appears that different regions in China may have different population density thresholds. Our results provide important insights into urban economic evolution, while also supporting the development of more effective population policies.

The MENA region, known for its significant oil and gas production, has been widely acknowledged for its reliance on fossil fuels. The dependence on fossil fuels has led to significant environmental pollution. Therefore, the shift towards a more environmentally friendly and enduring future is crucial. Thus, the current study tries to investigate the effect of green technology innovations on green growth in MENA region. Specifically, we examine whether the effect of green technology innovations on green growth depend on the threshold level of income. To this end, a panel threshold model is estimated for a sample of 10 MENA countries over the period 1998–2022. Our main findings show that only countries with income level beyond the threshold can benefit significantly from green technology innovations in term of green growth. Nevertheless, our findings indicate a substantial and adverse impact of green technology innovation on countries where income levels fall below the specified threshold.

Digital labor, as a new theoretical form of "audience commodity theory" in the digital media era, represents a new form of production and labor. This paper explores the unique features of digital labor in labor form, labor products and labor time, and combining Marx's theory, it further reveals the alienation and exploitation of human social relations, emotional value and social class in the process of digital labor, and finally makes suggestions on the unequal relationship between platform and workers in the process of digital labor.

Every year, hundreds of fires occur in the forests and rangelands across the world and damage thousands hectare of trees, shrubs, and plants which cause environmental and economic damages. This study aims to establish a real time forest fire alert system for better forest management and monitoring in Golestan Province. In this study, in order to prepare fire hazard maps, the required layers were produced based on fire data in Golestan forests and MODIS sensor data. At first, the natural fire data was divided into two categories of training and test samples randomly. Then, the vegetation moisture stresses and greenness were considered using six indexes of NDVI, MSI, WDVI, OSAVI, GVMI and NDWI in natural fire area of training category on the day before fire occurrence and a long period of 15 years, and the risk threshold of the parameters was considered in addition to selecting the best spectral index of vegetation. Finally, the model output was validated for fire occurrences of the test category. The results showed the possibility of prediction of fire site before occurrence of fire with more than 80 percent accuracy.