Local System Research Articles

УПРАВЛІННЯ ФІНАНСОВИМИ РЕСУРСАМИ ТЕРИТОРІАЛЬНИХ ГРОМАД У СИСТЕМІ ПУБЛІЧНИХ ФІНАНСІВ

The article examines the elements of managing the financial resources of territorial communities in the public finance system. The essence of the concept of public finance was analyzed, the classification of the sources of the formation of financial resources of territorial communities was considered, the level of effectiveness of local self-government bodies in the implementation of the functions and powers assigned to them and their role in managing the resource potential of socio-economic development of administrative-territorial units was investigated. It is established that local financial resources management is carried out using an integrated approach, which includes a combination of resources of the State and non-State sectors of the economy. This is done with a view to achieving the goals and indicators of socio-economic development set out in the planning process in the interests of the population of the administrative-territorial entity. In this context, it is important to apply the principles of financial support for the development of territorial communities in the activities of local public authorities. The analysis of the development of the local finance management system has led to the conclusion that it is advisable to determine a comprehensive indicator of the resource provision of local budgets. It should take into account the indicators of revenues per capita, the percentage of budget subsidies, the amount of funds raised through grant support project activities, the share of borrowing made to the local budget, the assessment of the communal property management indicators of the territorial community, etc. The generalised indicator will make it possible to compare the state of financial and resource provision of the territorial community in regions with different levels of economic, natural, recreational and social potential. At the same time, it should be clearly understood that the system of financial management of territorial communities is fundamentally determined by those who actually, not nominally, influence the development and implementation of management decisions and have actual levers of influence on it.

ЄВРОПЕЙСЬКА ХАРТІЯ МІСЦЕВОГО САМОВРЯДУВАННЯ ЯК ОСНОВА ДІЯЛЬНОСТІ ОРГАНІВ УПРАВЛІННЯ ТЕРИТОРІАЛЬНИМИ ГРОМАДАМИ В УКРАЇНІ

The article examines the topic of compliance of legal regulation and the actual activity of local self-government bodies with the European Charter of Local Self-Government from the point of view of the conceptual understanding of the place of the local self-government body in the system of local self-government, its authority to perform management functions, the possibility of external supervision of its activities and rights citizens to participate in local government, which is the fundamental basis that characterizes the condition and capacity of local authorities. It has been established that the competence of local self-government bodies to carry out management in the form of delegated authority provided by Ukrainian legislation does not correspond to the principle of subsidiarity, which is defined by the European Charter of Local Self-Government, and the lack of a real and effective mechanism of administrative supervision of local self-government bodies, as provided for by this international agreement, has also been revealed. In addition, the discrepancy in the approaches of the European Charter of Local Self-Government and acts of Ukrainian legislation to the conceptual understanding of the place of local self-government bodies in the local self-government system was analyzed, and the problem of involving internally displaced persons to life in new communities and their right as community residents to participate in local self-government was highlighted. The importance of developing specific proposals for full compliance with the principle of subsidiarity in part of delegated authorities and the implementation of the mechanism of administrative supervision over the activities of local self-government bodies into regulatory and legal circulation was emphasized. At the same time, emphasis is placed on the need for a unified approach to building a high-quality and effective regulatory framework on local self-government based on European standards, which is an important issue on the agenda in the context of Ukraine's movement towards the European community.

관광과 지역 정체성 정치

Despite being one of Korea's six major cities during the Japanese colonial era, Mokpo has declined to a small local city post-liberation. Since the establishment of the local government system, Mokpo has aimed to reinvent itself as a tourist destination. Over the past 20 years, the city has implemented six major tourism development and promotion projects, including night scenery lighting, a marine music fountain, urban regeneration of the old city center, a suspension cable car, hotel construction on Samhakdo Island, and branding Mokpo as a “romantic harbor city.” Throughout this process, there have been conflicts, competition, and cooperation with various civic and local interest groups. This research, based on related studies and Logan & Molotch's (2007) growth machine theory, analyzes how different groups formed growth and anti-growth coalitions and how they struggled over six key projects. Newspaper articles documenting these conflicts, competition, and cooperation were reviewed. To enhance reliability and validity, peer review and an interview with a local newspaper editor were conducted. The findings show that while the growth machine theory is useful in examining Mokpo's coalitions and their conflicts, it has limitations in fully explaining the phenomenon's complexity. The study concludes by discussing future research directions and the role of deliberative democracy in sustaining Mokpo's development as a tourist city.

Unmanned Floating Object Transportation Applying Multiple Dynamic Positioning Tugboats: A Novel Cooperative Control Algorithm

Abstract To promote the automation and intelligence of marine floating object transportation, this paper proposes a cooperative consensus control algorithm for multiple unmanned dynamic positioning (DP) tugboats to transport an unactuated floating structure object using cables. The major concept of present algorithm is to implement a leader-follower formation strategy among distributed tugboats, with the aim of effectively maneuvering the object by adjusting the relative position between the virtual leader and the object in a reasonable manner. A cooperative consensus controller is integrated into the feedback controller of each tugboat local DP system in order to facilitate cooperative coordination among tugboats in a formation. A customized DP system, which incorporates the radial basis function neural network supervisor control into the DP controller design and introduces nonlinear disturbance observer into the low-frequency motion state observer design, is proposed to address cable tension disturbances, and thus, the tracking performance of the DP tugboat is improved. Full-scale nonlinear time domain simulations are performed under variable environmental conditions, verifying the effectiveness of the proposed automatic towing control scheme.

An intelligent model for efficient load forecasting and sustainable energy management in sustainable microgrids

Microgrids have emerged as a promising solution for enhancing energy sustainability and resilience in localized energy distribution systems. Efficient energy management and accurate load forecasting are one of the critical aspects for improving the operation of microgrids. Various approaches for energy prediction and load forecasting using statistical models are discussed in the literature. In this work, a novel energy management framework that incorporates machine learning (ML) techniques is presented for an accurate prediction of solar and wind energy generation. The anticipated approach also emphasizes time series-based load forecasting in microgrids with precise estimation of State of Charge (SoC) of battery. A unique feature of the proposed framework is that utilizes historical load data and employs time series analysis coupled with different ML models to forecast the load demand in a commercial microgrids scenario. In this work, Long Short-Term Memory (LSTM) and Linear Regression (LR) models are employed for an experimental analysis to study the proposed framework under three different cases, such as (i) prediction of energy generation, (ii) load demand forecasting and, (iii) prediction of SoC of battery. The results show that the Random Forest (RF) and LSTM models performs well for energy prediction and load forecasting respectively. On the other hand, the Artificial Neural Network (ANN) model exhibited superior accuracy in terms of SoC estimation. Further, in this work, a Graphical User Interface (GUI) is developed for evaluating the efficacy of the proposed energy management framework.

Identification and Positioning Method of Bulk Cargo Terminal Unloading Hopper Based on Monocular Vision Three-Dimensional Measurement

Rapid identification and localization of dry bulk cargo hoppers are currently core issues in the automation control of gantry cranes at dry bulk terminals. The current conventional method relies on LiDAR systems for the identification and positioning of bulk unloading hoppers. However, this approach is complex and costly. In contrast, GPS-based positioning solutions for bulk unloading hoppers are prone to damage due to the vibrations generated during the operation process. Therefore, in this paper, a hopper localization system based on monocular camera vision is proposed to locate the position of the bulk unloading hopper. The hopper identification and localization process are divided into three stages. The first stage uses the improved YOLOv5 model to quickly and roughly locate the hopper target. The second stage uses morphological geometrical features to locate the corner points of the hopper target. The third stage determines the three-dimensional coordinates of the hopper target by solving the position of the corner points in the world coordinate system through the PnP (Perspective-n-Point) algorithm. The experimental results show that the average positioning accuracy of the coordinates of the method is above 93%, demonstrating the accuracy and effectiveness of the method.

NUS so fast: the social and ecological implications of a rapidly developing indigenous food economy in the Cape Town area

AbstractThe modern global food system is highly unsustainable, shaped by industrialisation and corporate consolidation, with negative repercussions on the environment and biodiversity as well as human health. This paper looks at the burgeoning economy in neglected and underutilised species (NUS) in the Western Cape, South Africa, as a potential innovation that could make the local food system more socially and ecologically resilient. Although, at present, NUS are only marginally included in the local food system and policy discussions, NUS increasingly appear in the high-end food industry, driven by international gastronomic trends. These species hold potential as climate resilient, nutritionally dense, and socially and culturally significant foods in the region, but they also carry ecological and social risks. We critically examine the fledgling NUS economy in the Cape Town area to unpack the motivations and challenges associated with the potentially transformative inclusion of these foods into the local food system. We demonstrate that the main risks associated with NUS are negative ecological repercussions, privatisation of the NUS economy, and the reproduction and further entrenchment of unequal power and race dynamics in the region. To mitigate these risks and actualise the related benefits associated with NUS, engagement with the ecological, social, and political context of NUS needs to be significantly deepened. This is particularly true for those working in the high-end food industry, who appear to be driving the NUS economy, and will require education around sustainability and Traditional Ecological Knowledge (TEK), as well as a foregrounding awareness of power dynamics.

Design of IIOT Device Based on LoRa for Parsing Data Directly to SCADA System

As the revolution industry 4.0 was started as well as the productivity increases, the need for data analysis increases. Some industries have wide production area and they need long wire to connected between office for transferring data. A wireless system is one of solution to overcome this issue so that the technique of parsing data to expand coverage area for both local and remote systems. In this research, a device that supports IIOT (Industry on Internet of Things) will be designed by utilizing LoRa technology connected to a SCADA (Supervisory Control and Data Acquisition) system for direct parsing data. By using a SCADA system concept and incorporating wireless system as well as connecting to internet so the industrial system can be monitoring from anywhere so productivity can be increased. To test the proposed design, the two scenarios of performance test have been done, they are communicating distance test and the parsing data between two nodes LoRa as well as connecting to SCADA system. The first scenario results in the maximum communication distance that can still carried out reaching 400m. Meanwhile, the experience of second scenario on the IIOT device prototype produces accurate data so that it can be implemented in the wider industry

Achieving food security: Household perception and adoption of home gardening techniques in Ghana

As global food crises and high food prices continue to impact communities, there is a growing focus on strengthening local food systems and improving livelihoods. Home gardening techniques have gained renewed attention as a means of food production and enhancing household food security. However, there is a lack of empirical studies on the perception and adoption of home gardening techniques. This study therefore fills this gap by examining the perception and adoption of home gardening techniques among households in Ghana. A multistage sampling technique was used to select 348 households and data was collected through a structured questionnaire. Using a 5-point Likert scale, we analyzed the households' perception of home gardening techniques, and utilized a multivariate probit regression model to examine the factors influencing multiple adoption of home gardening techniques. The Kendall’s coefficient of concordance was used to test the level of agreement among ranked constraints in adopting home gardening techniques. The generalized Poisson regression was used to examine the number of adoption of home gardening techniques. The results revealed that most households perceived home gardening techniques as a way to improve household food security. Households were found to adopt multiple home gardening techniques, such as use of pots, sacks, and tires. Empirically, factors such as sex, education, occupation, income, technology cost, and social network had a significant influence on multiple adoption of home gardening techniques. Also, age, education, household size, income, technology cost, social network, inadequate space and insect and disease damages significantly influenced the number of adoptions of home gardening techniques. Furthermore, lack of time and inadequate space were the main constraints limiting the adoption of these techniques. We suggest government interventions to spur the adoption of home gardening techniques to improve household food nutrition.

Legal Culture of Coastal Lampung Indigenous People Based on Local Wisdom

This article discusses the legal culture of the Lampung Coastal Traditional Tribe Community Based on Local Wisdom, which highlights the traditional legal system of the Lampung Coastal Traditional Tribe Community and how local wisdom shapes and influences its legal practices. This research examines how cultural values, customs, and local norms play a role in resolving disputes, law enforcement, and regulating social life in these communities. Using qualitative methods, this article analyzes the structure of customary law and legal implementation mechanisms based on local wisdom principles, as well as their impact on social harmonization and cultural preservation. It is hoped that the findings from this research will provide in-depth insight into the relevance and adaptation of customary law in the modern context, as well as enrich understanding of the diversity of local wisdom-based legal systems in Indonesia.

Optimization of microgrid operations using renewable energy sources

Microgrids, comprising localized energy systems capable of operating independently or in conjunction with the main grid, are increasingly being recognized as vital components of modern energy infrastructure. The integration of renewable energy sources (RES) into microgrids offers significant potential for enhancing operational efficiency, sustainability, and resilience. This paper presents an overview of recent advancements and methodologies for optimizing microgrid operations utilizing renewable energy sources. The optimization of microgrid operations involves the strategic coordination and management of diverse energy resources, including solar photovoltaic (PV) systems, wind turbines, and energy storage systems (ESS). Key objectives include minimizing operational costs, reducing greenhouse gas emissions, ensuring reliable power supply, and maintaining system stability. Advanced optimization techniques, such as model predictive control (MPC), mixed-integer linear programming (MILP), and heuristic algorithms, play a crucial role in achieving these objectives by enabling the dynamic adjustment of energy generation and distribution in response to real-time conditions. A critical aspect of microgrid optimization is the accurate forecasting of renewable energy generation and load demand. Machine learning (ML) and artificial intelligence (AI) algorithms have been effectively employed to enhance prediction accuracy, thereby improving decision-making processes. Furthermore, the integration of ESS, such as batteries and flywheels, helps to address the intermittency of RES, providing a buffer that can store excess energy during periods of high generation and release it during peak demand. The implementation of demand response (DR) strategies within microgrids further contributes to optimization efforts. By incentivizing consumers to adjust their energy usage patterns in response to price signals or grid needs, DR programs help to balance supply and demand, reduce peak loads, and enhance overall grid reliability. Case studies and field implementations demonstrate the practical benefits of optimized microgrid operations. For instance, microgrids incorporating high shares of RES have been shown to achieve significant cost savings, improved energy security, and reduced environmental impacts. These successes underline the importance of ongoing research and development in optimization techniques and the need for supportive policy frameworks to facilitate the broader adoption of microgrids. In conclusion, optimizing microgrid operations using renewable energy sources presents a promising pathway toward a more sustainable and resilient energy future. Continued advancements in optimization algorithms, predictive analytics, and integrated system design are essential for unlocking the full potential of microgrids, ensuring they can effectively meet the evolving energy demands and environmental challenges of the 21st century. Keywords: Optimization, Microgrid, Operations, Renewable Energy, Energy Sources.

Insights from a topo-bathymetric and oceanographic dataset for coastal flooding studies: the French Flooding Prevention Action Program of Saint-Malo

Abstract. The French Flooding Prevention Action Program of Saint-Malo, France, requires the assessment of coastal flooding risks and the development of a local flood warning system. The first prerequisite is knowledge of the topography and bathymetry of the bay of Saint-Malo; the acquisition of new multibeam bathymetric data was performed in 2018 and 2019 to increase the resolution of the existing topo-bathymetric datasets and to produce two high-resolution (20 and 5 m) topo-bathymetric digital terrain models. Second, the hydrodynamics associated with coastal flooding were investigated through a dense and extensive oceanographic field experiment conducted during winter 2018–2019 using a network of 22 moorings with 37 sensors: the network included 2 directional buoys, 2 pressure tide gauges, 18 wave pressure gauges, 4 single-point current meters, 7 current profilers, and 4 acoustic wave current profilers from mid-depth (25 m) up to the upper beach and the dike system. The oceanographic dataset thus provides an extended overview of the hydrodynamics and wave processes in the bay of Saint-Malo from the coast up to over-flooding and over-topping areas. This dataset helps to identify the physical drivers of the coastal flooding and provides a quantification of their respective contributions. In particular, the wave processes at the foot of the protection structures can be observed: in this macro-tidal environment, during high spring tides, short and infragravity waves propagate up to the protection structures, while the wave set-up remains negligible, and over-topping by sea packs can occur. The combination of high-resolution topo-bathymetric and oceanographic datasets allows the construction, calibration and validation of a wave and hydrodynamic coupled model that is used to investigate flooding processes more deeply and might be integrated into a future local warning system by means of Saint-Malo inter-communality. The topo-bathymetric and oceanographic datasets are available freely at https://doi.org/10.17183/MNT_COTIER_GNB_PAPI_SM_20m_WGS84, https://doi.org/10.17183/MNT_COTIER_PORT_SM_PAPI_SM_5m_WGS84 and https://doi.org/10.17183/CAMPAGNE_OCEANO_STMALO (Shom, 2020a, b, 2021).

Quantifying Quantum Chaos through Microcanonical Distributions of Entanglement

A characteristic feature of “quantum chaotic” systems is that their eigenspectra and eigenstates display universal statistical properties described by random matrix theory (RMT). However, eigenstates of local systems also encode structure beyond RMT. To capture this feature, we introduce a framework that allows us to compare the properties of eigenstates in local systems with those of pure random states. In particular, our framework defines a notion of distance between quantum state ensembles that utilizes the Kullback-Leibler divergence to compare the microcanonical distribution of entanglement entropy (EE) of eigenstates with a reference RMT distribution generated by pure random states (with appropriate constraints). This notion gives rise to a quantitative metric for quantum chaos that not only accounts for averages of the distributions but also higher moments. The differences in moments are compared on a highly resolved scale set by the standard deviation of the RMT distribution, which is exponentially small in system size. As a result, the metric can distinguish between chaotic and integrable behaviors and, in addition, quantify and compare the of chaos (in terms of proximity to RMT behavior) between two systems that are assumed to be chaotic. We implement our framework in local, minimally structured, Floquet random circuits, as well as a canonical family of many-body Hamiltonians, the mixed-field Ising model (MFIM). Importantly, for Hamiltonian systems, we find that the reference random distribution must be appropriately constrained to incorporate the effect of energy conservation in order to describe the ensemble properties of midspectrum eigenstates. The metric captures deviations from RMT across all models and parameters, including those that have been previously identified as strongly chaotic, and for which other diagnostics of chaos such as level spacing statistics look strongly thermal. In Floquet circuits, the dominant source of deviations is the second moment of the distribution, and this persists for all system sizes. For the MFIM, we find significant variation of the KL divergence in parameter space. Notably, we find a small region where deviations from RMT are minimized, suggesting that “maximally chaotic” Hamiltonians may exist in fine-tuned pockets of parameter space. Published by the American Physical Society 2024

The crowding out effect of local government debt expansion: Insights from commercial credit financing

Understanding the impact of local government debt expansion on microeconomic entities is crucial in evaluating local government debt policies. This study explored the crowding-out effect of local government debt on firms' commercial credit financing. We found that local government debt plays a crucial role in enhancing corporate commercial credit financing by exacerbating the financing constraints faced by firms. Second, the impact of local government debt on commercial credit financing is more pronounced for firms with lower leverage and a more stable capital chain. Third, state-owned enterprises (SOEs) are more susceptible to the impact of local government debt on commercial credit financing compared to private enterprises. And the crowding-out effect of local government debt on firms' commercial credit financing is more pronounced in the regions where the credit market regulation is relatively weaker. Our findings provide valuable insights that can contribute to the reform of the local government debt management system.

Theoretical and experimental investigation into detection of early-stage propagation of double cracks with distributed fiber optic sensor

A strain transfer model is developed to describe the transfer of crack opening displacement (COD) of double cracks in a structural substrate to the distributed fiber optic sensor (DFOS). Global and local coordinate systems are set up to aid in the deduction of the transfer of CODs of the double cracks to the DFOS. The analytical model of strain transfer is first derived in the local coordinate system and then is transformed into the global coordinate system. Analytical results show that the DFOS fiber strain induced by CODs of the double cracks in the structural substrate is affected by both the spacing and the CODs of the double cracks, and the strain peak is suppressed as the crack spacing is less than the characteristic length which is defined as the range of influence of the COD of the individual crack. The influences of the material properties of the DFOS, the fiber coating, the bonding adhesive, and the DFOS-fiber coating interfacial stiffness are discussed. The developed model is also experimentally validated by monitoring CODs of double cracks in aluminum alloy plates with optical frequency domain reflectometer (OFDR) DFOSs. Experimental results show that the strain distribution measured by the OFDR DFOSs agree well with the analytical results of the developed model. The limitations of the developed model and future work anticipated are then discussed.

Weaving scientific and local knowledge on climate change impacts in coastal Kenya, Western Indian Ocean

Climate change poses severe threats to coastal social-ecological systems (SES) worldwide. Recent calls recognize the importance of including Indigenous and local knowledge (ILK) in research on climate change impacts. Yet studies that have attempted to weave ILK and scientific knowledge have seldom considered the gendered nature of climate change impacts. Building on the literature on gender and climate change and knowledge pluralism, this study contributes to addressing this research gap by exploring local knowledge on climate change impacts and its relation to scientific knowledge through a gendered approach and focusing on the Western Indian Ocean region, and more specifically on Kenya. We adopted a mixed methodology combining qualitative and quantitative approaches. We found evidence of pronounced climate change impacts on coastal SES both in the scientific literature and in local reports. Our findings highlight that there is an extensive overlap between information derived from scientific and local knowledge systems. Importantly, our study revealed reports of change that were only provided by SSF communities, namely changes in coastal dynamics, a decrease in rainfall, and a decrease in the abundance of green algae. Although we found gendered variations in changes reported by SSF communities, gendered differences of climate change impacts on SSF were not detected in the reviewed literature. Overall, our results suggest that knowledge cross-fertilization generates a holistic, relational, and place-based view of climate change impacts, which may support sound and gender-inclusive adaptive policies. We conclude by suggesting key policy recommendations for climate adaptation and risk management

Deploying deep Solanaceae domestication and virus biotechnology knowledge to enhance food system performance and diversity

Abstract Our knowledge of crop domestication, genomics, and of the plant virosphere unevenly represents the taxonomic distribution of the global biodiversity, and, as we show here, is significantly enriched for the Solanaceae. Within the family, potato, tomato, eggplant, pepper, and over 100 lesser-known edible species play important nutrition and cultural roles in global and local food systems. Technologies using engineered viruses are transitioning from proof-of-concept applications in model plants to the precise trait breeding of Solanaceae crops. Leveraging this accumulated knowledge, we highlight the potential of virus-based biotechnologies for fast-track improvement of Solanaceae crop production systems, contributing to enhanced global and local human nutrition and food security.

Towards sustainable landscapes: Implementing participatory approaches in contract design for biodiversity preservation and ecosystem services in Europe

Agricultural landscapes are the result of the long-term, complex, and intermingled interfaces between nature and culture. Among the stakeholders involved in the production of agri-environmental and climate services, farmers play a crucial role, and their contribution should be duly acknowledged to promote sustainable land management. Therefore, this research aims to contribute to the participatory design of agri-environmental contracts to incentivize landscape and biodiversity practices. To achieve this goal, 13 innovation labs with multi-actor perspective were established across nine different European countries. These groups envisioned a future sustainable landscape characterized by diversity and balance of economic, socio-cultural, and environmental components. Trust-based networks and effective communication channels emerge as vital components for the success of sustainable local production systems. Practitioners emphasize the significance of European-level policies in effecting transformative change and influencing farmers'willingness to contribute to both food production and environmental public goods. They defined concrete contract features such as public funding, hybrid payments, and the presence of intermediaries for the potential of agri-environmental measures. Notably, practitioners perceive a wide range of benefits associated with the implementation of agri-environmental measures, extending beyond economic compensation. Gaining a deeper understanding of practitioners' perceptions of their territories and agri-environmental measures is crucial for policymakers to design tailored and appealing programs that resonate with practitioners'needs.

Designing a model of emergency medical services preparedness in response to mass casualty incidents: a mixed-method study

BackgroundEmergency medical services preparedness in mass casualty incidents is one of the most important concerns in emergency systems. A mass casualty incident is a sudden event with several injured individuals that overwhelms the local health care system. This study aimed to identify and validate the components of emergency medical services readiness in mass casualty incidents which ultimately led to designing a conceptual model.MethodsThis research was an explanatory mixed-method study conducted in five consecutive stages in Iran between November 2021 and September 2023. First, a systematic review was carried out to extract the components of emergency medical services preparedness in mass casualty incidents based on the PRISMA guideline. Second, a qualitative study was designed to explore the preparedness components through in-depth semi-structured interviews and analyzed using the content analysis approach. Third, the integration of the components extracted from the two stages of the systematic review and qualitative study was done by an expert panel. Fourth, the obtained components were validated using the Delphi technique. Two rounds were done in the Delphi phase. Finally, the conceptual model of emergency medical services preparedness in mass casualty incidents was designed by a panel of experts.Results10 articles were included in the systematic review stage and sixteen main components were extracted and classified into four categories. In the second stage, thirteen components were extracted from the qualitative study and classified into five categories. Then, the components of the previous two phases were integrated into the panel of experts and 23 components were identified. After validation with the Delphi technique, 22 components were extracted. Lastly, the final components were examined by the panel of experts, and the conceptual schematic of the model was drawn.ConclusionsIt is necessary to have an integrated framework and model of emergency medical service readiness in the planning and management of mass casualty incidents. The components and the final model of this research were obtained after the systematic scientific steps, which can be used as a scheme to improve emergency medical service preparedness in response to mass casualty incidents.

Cookin’ the Books: How Waitlist Management Biases Data Production in Built for Zero Communities

Built for Zero (BFZ) is a new data-driven approach to allocating housing assistance to homeless households. BFZ implementation includes the production/maintenance of a “by-name list” (BNL). The BNL is a regularly updated spreadsheet with personalised data about everyone who enters and exits a local homeless system (i.e., flow). Local administrators use the BNL to produce “by-name data” (BND). BND lets administrators monitor and manipulate system flow in “real time.” Scholars have not analysed how administrators manage their BNL and produce BND. This paper starts that conservation by answering three questions with interview data that was collected from administrators at 28 “BFZ communities” (i.e., homeless systems implementing BFZ): How do administrators manage their BNL? What factors influence BNL management? How does BNL management affect BND accuracy? Using thematic analysis, the author provides evidence that administrators manage the length of their BNL by removing “inactive” clients who have disengaged from service providers. Administrators try to verify housing status before deeming someone inactive. The verification process is shaped by social policies, network ties, virtual interactions, and administrative discretion. Because those things vary across homeless systems, administrators face different constraints and enablers whilst verifying someone’s housing status. The intersection of contextual factors and subjective processes biases the BND administrators produce from their BNL.