Information-sharing Mechanisms Research Articles

COVID-19: An exploration of consecutive systemic barriers to pathogen-related data sharing during a pandemic

Abstract In 2020, the COVID-19 pandemic resulted in a rapid response from governments and researchers worldwide, but information-sharing mechanisms were variable, and many early efforts were insufficient for the purpose. We interviewed fifteen data professionals located around the world, working with COVID-19-relevant data types in semi-structured interviews. Interviews covered both challenges and positive experiences with data in multiple domains and formats, including medical records, social deprivation, hospital bed capacity, and mobility data. We analyze this qualitative corpus of experiences for content and themes and identify four sequential barriers a researcher may encounter. These are: (1) Knowing data exists, (2) being able to access that data, (3) data quality, and (4) ability to share data onwards. A fifth barrier, (5) human throughput capacity, is present throughout all four stages. Examples of these barriers range from challenges faced by single individuals to non-existent records of historic mingling/social distance laws, and up to systemic geopolitical data suppression. Finally, we recommend that governments and local authorities explicitly create machine-readable temporal “law as code” for changes in laws such as mobility/mingling laws and changes in geographical regions.

Healthcare Management Strategies for Enhancing Patient Engagement

Introduction: The healthcare industry is transforming due to the growing emphasis on patient-oriented care and better results. One critical element for accomplishing these goals is patient empowerment, that is, the active participation of the individual in their health journey. This abstract outlines the identified strategies from a paper related to improving patients' engagement in their own healthcare.Methods: We carried out a systematic literature review focused on identifying strategies to improve patient engagement. Studies published between 2010 and 2020 considered interventions focusing on patient engagement in the management aspect of healthcare. We selected and reviewed 20 articles to identify key themes and strategies.Results: Our study identified four strategies healthcare practitioners used to develop patient self-management strategies. Such strategies may involve enhancing communication and information-sharing mechanisms, promoting education and empowerment of the patient and family, utilizing technology and digital tools, and nurturing collaboration between patients and healthcare providers. Game example strategies were used to identify and code each type.Conclusions: onclusively, these are the ways by which healthcare organizations can enhance patient engagement and drive better patient outcomes. However, such strategies need to be implemented in a focused and patient-centered manner based on the variety of patients' needs and preferences. Future research should assess the effectiveness of these mechanisms and identify other strategies for engaging patients in managing their healthcare.

Dare to share: information and intelligence sharing within the UK’s anti-money laundering regime

ABSTRACT The UK's approach to combating money laundering extends beyond traditional enforcement authorities, encompassing diverse regulated entities mandated to monitor and share intelligence on suspected laundering activities. This study examines the UK's Anti-Money Laundering (AML) nodal institutional architecture, focusing on the significance of information-sharing mechanisms and structures among law enforcement, public institutions, and private entities. Different types of information – ranging from raw data to strategic, tactical, and operational intelligence, as well as evidence – dictate the appropriate structures and mechanisms for their sharing. This study introduces a nuanced framework for analysing these structures, assessing the spectrum from highly structured to organic approaches in state intervention, alongside varying levels of formality, incorporating mandatory or voluntary elements. The analysis identifies four main factors shaping the dynamics of information sharing in the UK's AML efforts: strategic resource allocation involving technology and human resources, the establishment of formal rules and standardised interpretations, cultural shifts towards trust and reciprocity, and state coordination and leadership. The findings reveal the central role of the state not only in setting legal frameworks but also in steering coordination, managing resources, and fostering reciprocal relationships among public and private nodes to enhance information sharing, reflecting a ´state-anchored´ approach to AML governance.

Does green mean paying? Environmental innovations and financial performance: Meta-Analytical insights/approach

Interest in the impact of environmental innovations on firms’ financial performance has surged over the past two decades, but studies show inconsistent results. This paper addresses these divergences by analyzing 74 studies from 1996 to 2022, encompassing 4,390,754 firm-year observations. We developed a probability-based meta-analysis approach to synthesize existing knowledge and found a generally positive impact of environmental innovations on financial performance, with a probability range of 0.85 to 0.97. Manufacturing firms benefit more from environmental innovations than firms in other industries, and survey-based studies report a more favorable relationship than those using secondary data. This study contributes to existing knowledge by providing a comprehensive aggregation of data, supporting the resource-based view (RBV) and the Porter hypothesis. The findings suggest significant policy implications, highlighting the need for tailored incentives and information-sharing mechanisms, and underscore the importance of diverse data sources in research to ensure robust results.

Research on Innovation of Food Logistics Supply Chain Management

In the context of globalization and constantly changing consumer demand, the management of food logistics supply chains has become increasingly complex and important. This paper mainly studies the problems and innovative methods in food logistics supply chain management, aiming to improve the efficiency and adaptability of the supply chain by optimizing management strategies. This paper adopts literature analysis and case analysis methods to analyze in detail the problems of information asymmetry, cost control, transportation efficiency, and inventory management in the food logistics supply chain. It proposes innovative supplier management models, digital management, modern supply chain management concepts, inter chain cooperation, and risk management solutions. Research has found that adopting information-sharing mechanisms and advanced information technology, as well as strengthening collaboration among various links in the supply chain, can effectively improve management efficiency and reduce operating costs. This study provides some useful references for food logistics enterprises in practical operation, helping them improve service quality and reduce operating costs in a fiercely competitive market environment, enhance market competitiveness, ensure food safety and freshness, and meet the growing needs of consumers.

Advanced parameter estimation for lithium-ion battery model using the information sharing group teaching optimization algorithm

Accurate battery modeling is crucial for optimizing the performance and safety of Lithium-ion batteries (LiBs), particularly in applications such as electric vehicles and smart grids. This paper introduces the Information Sharing Group Teaching Optimization Algorithm (ISGTOA), a novel human-based metaheuristic algorithm designed to estimate the 21 parameters of third-order Equivalent Circuit Model (ECM) for LiBs. Unlike existing methods, ISGTOA effectively manages the increased complexity of a model through advanced group teaching strategies and sophisticated information-sharing mechanisms inspired by classroom dynamics. We validated the effectiveness of ISGTOA using two distinct datasets—High Dynamic Profile (HDP) and Urban Dynamometer Driving Schedule (UDDS)—across various LiB chemistries (NCA and NMC) and temperature conditions (−5 °C, 25 °C and 45 °C). The results demonstrate that ISGTOA achieves superior parameter estimation accuracy and convergence speed compared to established and recent optimization methods such as TLBO, TLSBO, AISA, MTBO, and DTBO. Specifically, ISGTOA attained a minimum RMSE of 8.357 mV with rapid convergence and high stability in the HDP dataset and minimized RMSE to 10 mV within ten iterations at both 25 °C and 45 °C in the UDDS dataset. Additionally, ISGTOA exhibited high efficiency (up to 97.75 %) under varying thermal environments. This work not only introduces a novel algorithm for complex battery modeling but also sets the stage for future advancements in real-time battery management systems, emphasizing the importance of robust, versatile, and efficient parameter estimation techniques.

Study on the Influences of Inter-Governmental Information Flow and Interdepartmental Collaborative Supervision on Pork Quality: A Case Study in China.

To study the influences of the degree of interdepartmental collaborative supervision on the behavioral strategy selection of pig farmers, pig slaughterers, and pork processing manufacturers in the pork supply chain system, this study established a three-party evolutionary game model involving pig farmers, pig slaughterers, and pork processing manufacturers based on the social co-governance framework by focusing on the interdepartmental information sharing mechanism and cooperative governance. Here, we examined how the degree of collaborative supervision among government departments influences the behavioral strategy selection of these parties by focusing on key mechanisms such as information sharing and interdepartmental collaborative governance. Our findings revealed that within a social co-governance system, the strategic choices of the three entities in the pork supply chain closely correlate with the coordination level of collaborative supervision among government departments, particularly through information-sharing mechanisms. Additionally, the strategies are influenced by market-based contract supervision among entities, consumer reporting intensity, and the collaborative governance capabilities of the government, market actors, and consumers. Higher levels of social co-governance are associated with fewer risky links in the pork supply chain and reduced overall risk. Key factors affecting the behavioral strategy selection of the subjects in the pork supply chain include interdepartmental collaborative governance among government departments (e.g., optimizing random inspection frequencies, adjusting economic penalties, and disclosing enterprise market credit information via information sharing mechanisms), consumer complaint probabilities, and the intensity of mutual supervision among enterprises. Therefore, to enhance pork supply chain quality and mitigate risks, it is crucial to enhance the coordination of collaborative supervision among government departments, encourage consumer reporting, and improve market-based mutual supervision mechanisms among upstream and downstream subjects in the supply chain.

International Legal Dynamics in Combating Cybercrime: Challenges and Opportunities for Developing Countries

The surge of cybercrime in the contemporary digital landscape presents complex challenges, requiring an international legal framework to combat the evolving threats. This article delves into the international legal dynamics surrounding the fight against cybercrime, with a specific focus on the challenges and opportunities faced by developing countries. The research employs a comprehensive analysis of existing international legal instruments, treaties, and collaborative initiatives aimed at addressing cyber threats. The study identifies the multifaceted challenges encountered by developing nations in effectively combating cybercrime. These challenges include the lack of harmonization in legal definitions, jurisdictional complexities, and the rapid evolution of cyber threats outpacing legal responses. Additionally, resource constraints, limited technological capabilities, and varying legal frameworks across borders further complicate the enforcement of cyber laws. Amidst these challenges, the research highlights opportunities for developing countries to enhance their capacities in the global fight against cybercrime. Collaboration and information-sharing mechanisms, capacity-building initiatives, and the alignment of domestic laws with international standards emerge as key opportunities. The article emphasizes the importance of fostering international cooperation to facilitate the exchange of expertise and resources, ultimately fortifying the collective response to cyber threats. In conclusion, the article underscores the urgent need for developing countries to navigate the intricate international legal landscape in combating cybercrime. By seizing opportunities for collaboration and capacity-building, these nations can play a proactive role in shaping a more resilient global cybersecurity framework.

Trust Environment for Cyber-Physical Systems: The DYNAMO Approach

This paper explores the evolving landscape of cybersecurity within cyber-physical systems, emphasizing the critical need for resilience and trust-building mechanisms. Grounded in the foundational perspectives of Cybersecurity Science, the study addresses the challenges posed by the complex interdependencies among physical, information, cognitive, and social domains. It introduces the DYNAMO platform, a novel approach that integrates Cyber Threat Intelligence (CTI) with Business Continuity Management (BCM) to enhance situational awareness and recovery planning. The platform's comprehensive methodology spans existing tool incorporation, detailed assessments, identification of gaps, simulations, and knowledge generation. Furthermore, the paper delves into the intricacies of cybersecurity information sharing, advocating for a unified approach to combat hybrid threats. The establishment of a common operational picture and shared situational awareness emerges as pivotal, underlining the indispensable role of technology, social trust, and resilience in securing critical information-sharing mechanisms in cyber-physical systems.

THE IMPORTANCE OF FORENSIC LABS IN MINIMIZING CRIME PREVENTION: A STUDY WITH REFERENCE TO KARACHI CITY

The role of forensic labs in crime prevention and investigation cannot be overstated. These specialized facilities provide law enforcement agencies with the scientific tools and expertise necessary to analyze evidence and solve crimes. In Karachi City, where crime remains a persistent challenge, the role of forensic labs is particularly critical. However, a recent research paper highlights the significant challenges faced by forensic labs in Karachi City, including inadequate infrastructure, limited resources, and heavy workloads. The paper, which assesses the current state of forensic labs in Karachi City and analyzes their impact on crime rates, emphasizes the crucial role of well-equipped forensic labs in facilitating effective criminal investigations. The authors argue that timely and accurate forensic analysis is essential for solving crimes and deterring potential offenders. They note that forensic labs with advanced technologies and skilled personnel significantly increase the chances of solving crimes and contributing to public safety. However, the research also reveals that forensic labs in Karachi City face significant challenges in their efforts to combat crime. Insufficient funding and outdated equipment hinder the timely processing and analysis of forensic evidence, leading to delays in criminal investigations and diminished crime prevention efforts. The authors argue that addressing these challenges is crucial for the effective functioning of forensic labs and their contribution to crime prevention. To enhance the capabilities of forensic labs in Karachi City, the authors recommend further investment in infrastructure and resources. They suggest that adequate funding should be allocated to upgrade equipment and facilities, enabling timely and accurate analysis of forensic evidence. Additionally, specialized training programs should be developed to ensure that forensic professionals are equipped with the latest methodologies and technologies. The paper also emphasizes the importance of collaboration between forensic labs and law enforcement agencies in maximizing their impact on crime prevention. The authors argue that strengthening partnerships and information-sharing mechanisms between these entities will improve coordination, streamline investigations, and enhance the overall crime prevention landscape in Karachi City. The study's findings are particularly relevant in the context of Karachi City's ongoing struggle with crime. The city has experienced a significant increase in criminal activity in recent years, with many cases going unsolved due to a lack of evidence and inadequate resources. The research paper highlights the need for increased investment in forensic labs and collaboration between law enforcement agencies to address these challenges and enhance public safety.The research paper provides valuable insights into the critical role of forensic labs in crime prevention and investigation in Karachi City. The authors emphasize the need for additional investment in infrastructure and resources, as well as collaboration between forensic labs and law enforcement agencies, to enhance their contribution to crime prevention efforts. By addressing these challenges, forensic labs in Karachi City can play a more effective role in combating crime and ensuring public safety.

Research on paths of opportunistic behavior avoidance and performance improvement in food supply chain from the perspective of social control.

It is essential to avoid opportunistic behaviors of food supply chain members to guarantee food safety and sustainable supply. This research adopted the perspective of supply chain membership governance to discuss the critical mechanisms of opportunistic behavior avoidance and performance improvement in the food supply chain. Two information-sharing mechanisms (information sharing with customers and information sharing with suppliers) were used as mediating variables to explore the mechanisms of how social control, information sharing, and opportunistic behavior worked on supply chain performance. Furthermore, an online questionnaire survey was conducted to collect 210 data samples from the food manufacturing industry in China, and the structural equation model method was applied to test the research hypotheses. According to the empirical research findings, social control can directly reduce opportunistic behaviors of supply chain members and reduce such behaviors indirectly via the mediating factor of information sharing; social control affects the supply chain performance via the mediating factors of information sharing and opportunistic behavior, instead of directly improving supply chain performance. Two information sharing mechanisms vary in their mechanism of influence. Information sharing with customers reduces opportunistic behaviors, but does not directly improve supply chain performance. Information sharing with suppliers enhances supply chain performance and reduces opportunistic behaviors. This research offers theoretical and practical suggestions for performance improvement and opportunistic behavior avoidance to promote food supply chain management.

Rethinking journalism protection: looking beyond copyright

ABSTRACT Journalism plays a crucial role in providing reliable information and holding those in power accountable. However, newspapers have experienced a significant drop in profitability, with digital platforms controlling the industry's main revenue sources being one contributing factor. To tackle this problem, the EU has granted press publishers the right to demand payment for copyright licenses from digital platforms. This article examines the nature and history of the new neighbouring right introduced by the EU Directive 790/2019 (DCSM) and considers the relationship between copyright and competition law in this area. While this move aims to enhance the bargaining power of publishers, it alone might not be sufficient to safeguard the public's right to information, freedom of speech, and a diverse news media landscape. Consequently, the effectiveness of the EU Directive will require additional regulatory measures, including bargaining codes, information-sharing mechanisms, and the implementation of specific ‘choice architectures’.

Investigating Language Relationships in Multilingual Sentence Encoders Through the Lens of Linguistic Typology

Abstract Multilingual sentence encoders have seen much success in cross-lingual model transfer for downstream NLP tasks. The success of this transfer is, however, dependent on the model’s ability to encode the patterns of cross-lingual similarity and variation. Yet, we know relatively little about the properties of individual languages or the general patterns of linguistic variation that the models encode. In this article, we investigate these questions by leveraging knowledge from the field of linguistic typology, which studies and documents structural and semantic variation across languages. We propose methods for separating language-specific subspaces within state-of-the-art multilingual sentence encoders (LASER, M-BERT, XLM, and XLM-R) with respect to a range of typological properties pertaining to lexical, morphological, and syntactic structure. Moreover, we investigate how typological information about languages is distributed across all layers of the models. Our results show interesting differences in encoding linguistic variation associated with different pretraining strategies. In addition, we propose a simple method to study how shared typological properties of languages are encoded in two state-of-the-art multilingual models—M-BERT and XLM-R. The results provide insight into their information-sharing mechanisms and suggest that these linguistic properties are encoded jointly across typologically similar languages in these models.

Multitask learning for emotion and personality traits detection

In recent years, deep learning-based automated personality traits detection has received a lot of attention, especially now, due to the massive digital footprints of an individual. Moreover, many researchers have demonstrated that there is a strong link between personality traits and emotions. In this paper, we build on the known correlation between personality traits and emotional behaviors and propose a novel transferring based multitask learning framework that simultaneously predicts both of them. We also empirically evaluate and discuss different information-sharing mechanisms between the two tasks. To ensure the high quality of the learning process, we adopt a model-agnostic meta-learning-like framework for model optimization. Our computationally efficient multitask learning model achieves the state-of-the-art performance across multiple famous personality and emotion datasets, even outperforming language model-based models.

Implementing environmental protection tax in China: an alternative framework

PurposeThe purpose of this study is to better understand the nexus between environmental taxes and other environmental management systems (EMSs) and to propose an alternative framework for implementing environmental protection tax (EPT) in China.Design/methodology/approachThe study uses a multimethod approach encompassing document analysis and comparative analysis. The archival data covers laws, reports, regulations, guidelines and standards related to the EPT and EMS sub-systems in China.FindingsThe study identifies several institutional features of environmental taxes that have not been fully explored in past tax research. In addition, the study reveals that information-sharing mechanisms are key to addressing the risks and uncertainties associated with the implementation of an environmental tax and that the mechanisms are grounded in the nexus among EPT and two EMS sub-systems.Research limitations/implicationsThe findings of this study have implications for the understanding of China’s environmental tax system, the Environmental Impact Assessment system and the pollutants discharge permit (PDP) system. The construction of an alternative framework provides insights for approaches to environmental taxation. A limitation of this study is that the application of the framework might be undermined by the inaccurate manual sampling, as some pollutants may be non-replicable.Practical implicationsThe findings of this study are relevant to policymakers who are designing, improving or abandoning environmental taxes for alternate solutions to environmental issues.Social implicationsThe insights gained from this study may be of assistance to lower the risks and uncertainties associated with the implementation of an environmental tax.Originality/valueThe study contributes to approaches to environmental taxes by constructing an alternative framework that connects an environmental tax system with two EMSs. The framework lays the groundwork for some promising research opportunities. Additionally, the study extends the tax accounting literature (Hanlon and Heitzman, 2010) by connecting accounting and environmental knowledge and developing a transdisciplinary approach. The study also contributes to the emerging body of literature that addresses the challenges in implementing environmental taxes in China.

Similarities in Recognition Cues Lead to the Infiltration of Non-Nestmates in an Ant Species.

Chemical cues are among the most important information-sharing mechanisms in insect societies, in which cuticular hydrocarbons play a central role, e.g., from nestmate recognition to queen signaling. The nestmate recognition mechanism usually prevents intruders from taking advantage of the resources stored in the nest. However, nestmate recognition is not unconditionally effective, and foreign individuals can sometimes infiltrate unrelated nests and take advantage of the colony resources. In this study, we investigated the role of overall colony odor profiles on the ability of conspecific workers to drift into unrelated colonies. We hypothesized that drifters would have higher chances of success by infiltrating colonies with the odor profiles most similar to their own nest, avoiding being detected as non-nestmates. By performing a drifting bioassay, we found that workers of the ant Formica fusca infiltrated unrelated conspecific colonies at a rate of 2.4%, significantly infiltrating colonies displaying CHC profiles most similar to their natal nests. Notably, methyl branched hydrocarbons seem to play a role as recognition cues in this species. In addition, we show that environmental rather than genetic factors are responsible for most contributions on the CHC phenotype, presenting ca. of 50% and 27.5% of explained variation respectively, and playing a major role in how worker ants detect and prevent the infiltration of non-nestmates in the colony. Hence, relying on cuticular hydrocarbons similarities could be a profitably evolutionary strategy by which workers can identify conspecific colonies, evade detection by guards, and avoid competition with genetic relatives.

International evidence on state ownership and trade credit: Opportunities and motivations.

Recent events, most notably the Global Financial Crisis and the COVID-19 pandemic, have made it increasingly apparent that liquidity is synonymous with corporate survival. In this paper, we explore how governments can fulfill an important need as suppliers of liquidity. Building on the financing advantage view of state ownership, we theorize how state-owned enterprises (SOEs) may provide capital by offering trade credit to customer firms. The data indicate a positive relation between the level of state ownership and the provision of trade credit. Using an institution-focused framework, we further determine that the nation’s institutional environment systematically affects the opportunities and motivations for SOEs to grant trade credit. Specifically, we find that SOEs grant more trade credit in countries with less developed financial markets, weaker legal protection of creditors, less comprehensive information-sharing mechanisms, more collectivist societies, left-wing governments, and higher levels of unemployment. Firm-level factors also influence the credit-granting decisions of SOEs, with SOEs with lower levels of state ownership and higher extents of internationalization offering lower amounts of trade credit. Overall, our study offers novel insights regarding the important role of state-owned firms as providers of liquidity.Electronic supplementary materialThe online version of this article (10.1057/s41267-021-00406-5) contains supplementary material, which is available to authorized users.

Securing Data in Life Sciences—A Plant Food (Edamame) Systems Case Study

Efforts to identify specialty crop genetics and agronomics, such as for edamame (vegetable soybean), that improve crop yields, resilience, and sustainability often fail to account for data on nutritional content, sensory profile, and/or consumer acceptability. Limited exchange of data across agricultural and food sectors challenges the design of specialty crops that meet consumer needs and expectations and the value chain, and can increase cyberbiosecurity risks. Communication and collaboration within the multi-sector system are essential to address cyberbiosecurity issues related to privacy of data producers, ownership of original data, risks of data sharing, security protection for data transfer and storage, and public perceptions of the food supply chain. This paper introduces a new exploration to design domestic (U.S.) edamame, which is based on both our domain knowledge of life science and our information-sharing mechanisms across the agriculture and food sectors. A case study, involving a multidisciplinary team of breeders and non-breeder researchers with expertise in crop/food production, processing, quality, and economics, serves as a model. We introduce the value chain attributed to combining and linking data from different sectors in the research and development phase, and explain why we believe such data-sharing mechanisms can facilitate better analyses that resonate throughout the full system, from seed to consumer. Our perspective illustrates that, by securely sharing and interpreting data across sectors and identifying cyberbiosecurity risks, we can design promising agricultural and food systems to better meet consumers' need and protection of life science data.

The Role of Human–Machine Interactive Devices for Post-COVID-19 Innovative Sustainable Tourism in Ho Chi Minh City, Vietnam

In this research article, we aim to study the proposed role of human–machine interactive (HMI) technologies, including both artificial intelligence (AI) and virtual reality (VR)-enabled applications, for the post-COVID-19 revival of the already depleted tourism industry in Vietnam’s major tourist destination and business hub of Ho Chi Minh City. The researchers aim to gather practical knowledge regarding tourists’ intentions for such service enhancements, which may drive the sector to adopt a better conclusive growth pattern in post-COVID-19 times. In this study, we attempt to focus on travelers who look for paramount safety with the assurance of empathetic, personalized care in post-COVID-19 times. In the current study, the authors employ structural equation modeling to evaluate the intentions of tourists both structurally and empirically for destination tourism with data collected from tourists with previous exposure to various kinds of these devices. The study shows that human–machine interactive devices are integrating AI and VR and have a significant effect on overall service quality, leading to tourist satisfaction and loyalty. The use of such social interactive gadgets within tourism and mostly in hospitality services requires an organization to make a commitment to futuristic technologies, along with building value by enriching service quality expectations among fearful tourists. This research shows that tourists mainly focus on the use of such HMI devices from the perspective of technology acceptance factors, qualitative value-enhancing service and trustworthy information-sharing mechanisms. The concept of the tour bubble framework is also discussed in detail. The analysis of this discussion gives us a more profound understanding of the novel opportunities which various administrative agencies may benefit from to position these devices better in smart, sustainable destination tourism strategies for the future so that, collectively, service 5.0 with HMI devices can possibly bring back tourism from being disintegrated. Such service applications are the new social innovations leading to sustainable service and a sophisticated experience for all tourists.

Early Warning Indicator Systems in Action: Considerations from Identification to Supports

Background/Context School transitions pose a variety of social-emotional and academic challenges to students, especially those who are more vulnerable due to home, health, or academic challenges. With this awareness, a growing number of school districts have developed and implemented early warning indicator systems (EWISs) aimed at early identification of and support to vulnerable students. Purpose/Objective/Research Question/Focus of Study While a growing body of research has documented EWISs use objective criteria to identify vulnerable students, there is scant scholarship about student identification using subjective tools, the processes that facilitate information sharing and collaboration between sending and receiving schools, and effective student supports. Our study aimed to narrow the gaps in the literature by providing insight about EWI identification, between-school communication, and student supports through the case study of one school district that implemented both objective and subjective EWISs. Our research questions were as follows: (1) Which students have been identified through the district's objective and subjective EWISs?; (2) How have school staff shared information stemming from the EWISs?; and (3) What supports do school staff offer students identified by the objective compared to the subjective EWISs? Research Design We used a mixed-methods approach, including statistical analysis of student-level administrative records, interviews with district staff, a survey of school staff, and multiple interviews with site staff at a sampling of schools. Conclusions/Recommendations: Identification Our study found that subjective criteria may be more effective in identifying students who are more likely to be missed by automated identification systems, such as “internalizers.” Moreover, stakeholder perception of specific indicators may have an impact on the selection of indicators in use. Sharing of information The practices that schools use to share information about transitioning students is an area ripe for future research. Our study revealed the importance of designing information-sharing mechanisms with the end user in mind. Developing a standardized rubric and incorporating a scale measure for relative urgency could increase the effectiveness and efficiency of the process. We also identified a tension between the need to share information and the will to protect students’ privacy. We see value in localized efforts to mitigate the unintended effects of such tension. Supports A primary consideration in an EWIS is its alignment to the district's model for the distribution of resources to support students. EWIS design considerations We identified the existence of tradeoffs between site-level autonomy and system-level coherence in the design of EWISs.