Lunday

Research Journal of the Graduate School of Bulacan State University

Print ISSN 1656-3514

Online ISSN 2980-4353

https://orcid.org/0000-0001-6644-0736

Abstract

This study explores the scholarly landscape on the use of digital tools and platforms in supervising school improvement, with emphasis on the post-COVID-19 educational context. Using bibliometric analysis of Scopus-indexed publications from 2020 to 2024, the research examines trends, influential works, and thematic gaps through tools such as VOSviewer and Bibliometrix. Findings revealed an emerging yet fragmented body of literature, with increased publications after the pandemic but limited collaboration across regions. Key themes included digital leadership, learning management systems, remote supervision, and issues of equity. While much research focused broadly on educational technology, fewer studies target supervision specifically. The study provided a data-driven foundation for policymakers, researchers, and school leaders to strengthen digital supervision practices and inform future policy development.

Keywords:

Digital supervision, School Improvement and Post-COVID education.

Introduction

The COVID-19 pandemic catalyzed a rapid digital transformation across global education systems, compelling schools to adopt digital platforms not only for teaching and learning but also for administrative and supervisory functions. While scholarship has extensively examined online pedagogy and technology-mediated instruction (Hodges et al., 2020; Trust & Whalen, 2020), comparatively little research has investigated how these digital tools reshape the supervision of school improvement. Yet, effective supervision remains pivotal for ensuring accountability, guiding instructional quality, and sustaining reforms in the post-pandemic context.

Bibliometric evidence underscores both the urgency and the fragility of this field. Publication output on digital supervision increased significantly from 2020 onward, reflecting heightened scholarly attention to crisis-driven digital adoption. However, the intellectual structure of the field remains fragmented: highly cited works often emerge from finance, environmental sustainability, or computational sciences rather than education-focused supervision studies. This pattern suggests that while the technological capacities for digital supervision (e.g., artificial intelligence, blockchain, real-time dashboards) are advancing, their theorization and empirical grounding within school leadership and supervision remain limited.

To interpret these patterns and provide a foundation for future inquiry, this study draws on established theoretical perspectives from educational technology and organizational innovation. At the individual level, the Technology Acceptance Model (TAM) (Davis, 1989) emphasizes perceived usefulness and ease of use as determinants of technology uptake. In the supervisory context, these constructs help explain whether school leaders and teachers embrace digital observation tools, data dashboards, or virtual coaching platforms. The Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003) extends this view by incorporating social influence and facilitating conditions, acknowledging the organizational and infrastructural supports that enable sustained adoption. At the systemic level, Diffusion of Innovations (DOI) theory (Rogers, 2003) explains how innovations spread across schools and districts, highlighting relative advantage, compatibility, complexity, and the role of communication channels in shaping adoption trajectories.

Integrating these perspectives provides a multi-layered conceptual lens for understanding the fragmented bibliometric landscape. The limited penetration of digital supervision into mainstream educational research can be interpreted as a diffusion challenge: advanced technological solutions are available, but their adoption depends on leadership endorsement, infrastructural support, and the perceived value they add to supervision practices. By situating the bibliometric findings within TAM, UTAUT, and DOI, this study not only maps the scholarly terrain but also identifies theoretical mechanisms that can guide future empirical work and policy initiatives.

Results and Analysis

The bibliometric analysis revealed a significant research gap in the literature concerning the use of digital tools and platforms for supervising school improvement in the post-COVID-19 context. From the publications retrieved in Scopus using the keywords “digital supervision,” “school improvement,” and “post-COVID education” only a limited number directly addressed the intersection of these domains (Raptis, Psyrras, & Koutsourai, 2023).

Publication trends demonstrated a significant increase in output during 2020 and 2021, reflecting the urgent need for remote supervision during pandemic-related school closures (Al-Edwan & Al-Khader, 2022). Beyond 2022, however, the growth of studies plateaued, suggesting a decline in focused academic inquiry despite the continued integration of digital practices in educational leadership (Yuanyuan, Alias, & Mansor, 2024). This trend suggested that much of the early research attention was reactive to the immediate challenges of the COVID-19 crisis, rather than reflective of a sustained, long-term scholarly agenda on digital supervision and leadership (Kusumawati, 2023).

A thematic analysis of co-occurring keywords and citation networks revealed that most studies emphasized remote learning, teacher performance monitoring, and digital platforms for instruction (Al-Edwan & Al-Khader, 2022). In contrast, relatively few studies have examined how school leaders and supervisors have harnessed digital technologies for continuous school improvement tasks—such as instructional coaching, data-driven decision-making, and professional development in hybrid or virtual contexts—though one empirical study does highlight how principals’ instructional e-supervision and technology leadership contribute to teachers’ professional digital competence within a supportive digital culture (Rasdiana et al., 2024).

Furthermore, network visualizations indicated that studies on digital supervision were often disconnected from research clusters on educational leadership, school reform, and quality assurance, highlighting a fragmentation in the field. This fragmentation underscores the absence of theoretical integration between digital innovation and school improvement frameworks (Yuanyuan et al., 2024).

Indeed, these findings support the argument that while the pandemic spurred a temporary surge of interest in digital supervision, the field remains underdeveloped in exploring sustainable, long-term strategies. Future research should more intentionally bridge educational technology, supervisory practices, and institutional reform to strengthen the role of digital supervision in post-pandemic school improvement (Raptis et al., 2023). 

The line graph illustrates the number of English-language publications indexed in Scopus from 2020 to 2024 using the keywords digital supervision AND school improvement AND post-COVID education. The data indicate a steadily increasing trend in scholarly attention, particularly in the immediate aftermath of the COVID-19 pandemic. In 2020, publication output was relatively low, at around 330, but rose to approximately 400 in 2021, reflecting the educational sector’s initial response to the crisis. A remarkable uptrend occurred in 2022, with output reaching nearly 600, suggesting a peak in academic interest as digital supervision became central to educational recovery and reform. In 2023, publications slightly declined to just below 600, possibly reflecting a consolidation of research themes or shifting priorities. By 2024, output rose again to around 650, demonstrating renewed interest and the sustained relevance of digital supervision as schools increasingly embed digital practices into long-term improvement strategies. Thus, the trajectory affirms the growing recognition of digital supervision as a critical dimension of post-COVID educational development, particularly in supporting systemic reforms, accountability, and professional growth.

Citation analysis

Document citation analysis depicts the most influential publications within the dataset (Table 2). Cao et al. (2021) leads with 517 citations, followed by Feng et al. (2022) with 487, and Gao et al. (2021) with 254, demonstrating their substantial impact on digital and technological research domains.

Trends and Emerging Themes on how digital tools and platforms are used for supervising school improvement, especially post COVID-19

The rapid digitalization accelerated by the COVID-19 pandemic has significantly transformed educational systems worldwide, particularly in the supervision and improvement of schools. Analysis of the top 10 highest-cited publications, although primarily focused on environmental, financial, and technological systems, provides transferable insights for modern educational supervision in the post-pandemic era.

A key emerging theme is the use of digital finance and technological platforms to enhance systemic efficiency (Cao et al., 2021; Feng et al., 2022, Li et al., 2021). In school supervision, these tools can streamline resource allocation, monitor budgets, and ensure transparency in financial management. By providing school leaders with real-time financial data, digital systems enable accountable, data-driven decision-making, which is critical for monitoring and evaluating school improvement programs.

Real-time monitoring and analytics, highlighted in studies by Gao et al. (2021), Xie et al. (2021), and Yang et al. (2021), demonstrate how continuous, technology-assisted tracking can enhance supervision. In schools, such systems allow administrators to observe student learning outcomes, teacher performance, and curriculum implementation in real time. This capability facilitates timely feedback, targeted interventions, and informed decision-making, supporting dynamic and responsive school oversight.

The study by Yong et al. (2020) emphasizes the potential of blockchain technology for secure and transparent supervision. Applied to education, blockchain can ensure the integrity of student records, assessment data, and resource distribution. This supports school supervisors in maintaining accurate, tamper-proof records and strengthens accountability mechanisms in school management systems.

Artificial intelligence (AI) and machine learning, as demonstrated by Xu et al. (2021), offer predictive capabilities for supervision. AI can identify trends in student performance, detect at-risk learners, and highlight areas requiring teacher support. These insights enable proactive and personalized supervisory strategies, helping school leaders anticipate challenges and intervene effectively to support continuous improvement.

Finally, IoT and UAV technologies (Islam et al., 2021) present opportunities for automated supervision of school facilities and environments. Sensors can monitor classroom conditions, track attendance, and optimize facility management. Such technologies extend the supervisory reach of administrators, allowing them to maintain both instructional quality and safety standards remotely and efficiently.

Collectively, these trends reflect a convergence of digital tools that directly enhance school supervision. Post-COVID-19, effective oversight requires real-time, secure, and intelligent systems that integrate financial management, data analytics, AI insights, blockchain security, and IoT-enabled monitoring. By leveraging these tools, school leaders can implement transparent, proactive, and evidence-based supervisory practices, ensuring sustained school improvement, equitable educational opportunities, and accountability in the digital era.

Citation Distribution and Implications for the limited research on how digital tools and platforms are used for supervising school improvement, especially post COVID-19

Analysis of the top 10 highest-cited publications reveals a notable thematic concentration that diverges from educational supervision. Most of these studies focus on digital finance, green technological innovation, and environmental sustainability rather than school supervision. For instance, Cao et al. (2021) and Feng et al. (2022), the most cited works with 517 and 487 citations respectively, examine the effects of digital finance and technological innovation on environmental and energy efficiency in China’s regional economies. Similarly, Gao et al. (2021) and Xie et al. (2021) focus on carbon emission efficiency and technological progress, reflecting the predominance of environmental and industrial applications in digitalization research.

This concentration indicates that while digital platforms are extensively studied in financial and industrial contexts, their application in educational supervision remains critically underrepresented. Notably, only Yong et al. (2020), who developed a blockchain-based system for vaccine supply and supervision, conceptually aligns with digital supervision. However, this work is situated in the public health domain, leaving a substantial gap in research on digital tools for school improvement.

Post-COVID-19, schools faced unprecedented challenges necessitating rapid digital transformation in teaching, learning, and administrative supervision. Despite these pressures, bibliometric evidence shows that scholarly attention has largely remained on industrial and environmental applications of digital technologies, rather than educational leadership, instructional oversight, and school-based decision-making. This gap represents a missed opportunity to explore how digital platforms could have supported monitoring instructional quality, tracking student outcomes, and facilitating data-driven supervision in virtual or hybrid learning environments.

The citation distribution further reflects a disproportionate academic focus. The top two documents alone account for nearly 1,000 citations, while studies potentially relevant to educational digitalization remain less visible. Although technological frameworks such as machine learning (Xu et al., 2021) and IoT applications (Islam et al., 2021) are gaining traction in other fields, their direct integration into school supervision and improvement strategies is still limited.

This pattern underscores a significant opportunity for educational researchers to adapt technological innovations from other sectors to school supervision. For example, blockchain approaches used in vaccine supervision could be reimagined for secure management of student records and transparent tracking of teacher performance, while AI and machine learning methods from construction and industrial systems could inform predictive analytics for school improvement planning.

In conclusion, the current citation landscape reveals a substantial research gap in the application of digital tools for supervising school improvement. The post-pandemic educational environment necessitates targeted research investigating how digital platforms can support school leaders in instructional supervision, resource management, and student outcome monitoring. Bridging this gap would not only expand educational scholarship but also provide practical frameworks for administrators navigating the complexities of digital transformation in the 21st century.

Co-citation analysis 

Co-citation analysis provides insights into the intellectual structure and thematic foundations of the limited research on digital tools and platforms for supervising school improvement, particularly post-COVID-19. Co-citation strength reflects the frequency with which two documents are cited together, highlighting conceptual or methodological connections, while total link strength (TLS) indicates a document’s connectivity and influence within the scholarly network.

The most highly co-cited document is the “EU Digital Finance Strategy” (TLS = 684; 38 citations), underscoring the centrality of European financial digitalization policies in studies examining digital transformation. Although the primary focus of these studies is not educational supervision, their influence suggests that digital tools in schools are often conceptualized through frameworks derived from financial regulation and policy-driven digital strategies. Similarly, the “Commission 2030 Digital Compass” (TLS = 588; 14 citations) reinforces the impact of international and regional digital policy, indicating that school digitalization is largely aligned with broader governmental visions, yet direct applications to school leadership and supervision remain sparse.

Several highly co-cited technical documents highlight the technological foundations of digital supervision tools. For example, Simonyan and Zisserman (2014) on convolutional networks (TLS = 35), He et al. (2016) on deep residual learning (TLS = 65 and 18), and Redmon and Farhadi (2018) on YOLOv3 (TLS = 0) demonstrate that many tools are inspired by advanced AI and computer vision technologies. These technologies have potential applications in education, such as automated classroom observation, AI-assisted performance monitoring, and digital assessment systems, although their integration into school supervision remains largely unexplored.

The inclusion of Braun and Clarke (2006) on thematic analysis (TLS = 5 and 16) emphasizes the ongoing relevance of qualitative research. This methodological anchor supports the exploration of experiential and interpretive dimensions of digital tool adoption, offering insight into how school leaders and teachers perceive and implement supervision platforms.

Blockchain technology, represented by Nakamoto (2008) (TLS = 8), is emerging as a potential foundation for secure, transparent, and decentralized school supervision systems. Although its co-citation strength is lower, it signals a growing interest in adapting blockchain for educational accountability and data integrity.

Overall, the co-citation network reflects a landscape dominated by policy-driven and technical studies, with qualitative and theoretical works occupying smaller but essential roles. High TLS values are concentrated in policy and AI-focused documents, while education-specific applications of digital platforms remain underdeveloped. The low influence of some technical documents suggests that while recognized, their relevance to school improvement research is currently limited. 

Summary of Key Patterns:

1. Policy Influence: European and international digital strategies strongly shape the discourse, indicating that digital transformation in schools is largely policy-driven.

2. Technological Foundations in AI: Deep learning and computer vision methods form the technical backbone of digital supervision tools, with potential applications in classroom monitoring and instructional oversight.

3. Emerging Role of Blockchain: Blockchain appears as an avenue for secure and transparent management of educational records and performance data.

4. Relevance of Qualitative Methods: Thematic analysis remains critical for understanding the human, organizational, and experiential aspects of adopting digital supervision tools.

Implications for School Supervision:

This analysis demonstrates that while digital infrastructure and policy support are growing, their direct application to school supervision is limited. There is an urgent need for research that translates these technological advances and policy frameworks into practical strategies for instructional oversight, performance monitoring, and school improvement. Bridging this gap will enable educational leaders to leverage AI, blockchain, and IoT technologies to enhance supervision, ensure accountability, and support evidence-based decision-making in the post-COVID-19 educational landscape.

The network visualization from the co-citation analysis revealed four distinct clusters, as illustrated in Figure 2. Each cluster was identified and described based on representative publications, with labels assigned through the author’s inductive interpretation and understanding of the thematic focus within the four clusters.

The co-citation network in Figure 2 reveals distinct clusters of literature but no unified body of work directly addressing digital supervision in schools. The left side of the map contains highly cited studies in artificial intelligence, deep learning, and blockchain technologies (e.g., He, Zhang; Simonyan & Zisserman; LeCun & Bengio; Nakamoto), while the right-side features methodological contributions (e.g., Braun & Clarke on thematic analysis; Davis on technology acceptance). These groups are only weakly connected, underscoring that research on digital supervision remains fragmented and indirectly informed by broader technological and methodological advances rather than education-specific scholarship.

This dispersion shows two main findings. First, technological innovations with potential relevance to remote supervision, performance monitoring, or digital record-keeping are being studied extensively—but mostly outside of education. Second, foundational works in research methodology are widely cited, indicating that rigorous approaches are valued, yet they are not systematically applied to the supervisory use of digital platforms.

The absence of a central, cohesive cluster focused specifically on digital tools for school supervision suggests that this area of inquiry is still emerging. The COVID-19 pandemic spurred rapid adoption of digital platforms, but scholarly work has largely lagged practice. Future research should build on these foundational technological and methodological studies to develop targeted frameworks for integrating digital tools into supervisory roles, supporting real-time data use, virtual coaching, and continuous school improvement in hybrid learning environments.

Overall, the co-citation patterns confirm that the research on using digital platforms to support school supervision is still fragmented, limited, and lacking a cohesive theoretical or empirical base. While some foundational methodological and technological studies are frequently cited, there is a clear absence of sustained, targeted scholarship that specifically addresses the supervisory dimension of digital school management.

This analysis reveals an important opportunity for future research: to build a structured body of knowledge that systematically investigates the design, implementation, and effectiveness of digital tools for supervising school improvement. There is a pressing need to examine how these platforms can support real-time data tracking, virtual coaching, collaborative evaluation, and distributed leadership in increasingly complex, hybrid educational environments.

In conclusion, the co-citation analysis not only points out the limited research volume in this critical area but also emphasizes the need for interdisciplinary, practice-based studies that can inform educational leaders on how to effectively integrate digital supervision tools in the post-COVID-19 educational landscape.

The co-word analysis map generated from the Scopus database offers a comprehensive view of the thematic structure surrounding current research on the use of digital tools and platforms for supervising school improvement, particularly in the post-COVID-19 context. The visualization reveals four major thematic clusters, each representing distinct but interconnected research directions.

CLUSTER 1 (red cluster) is heavily anchored in technological innovation, with key terms including "artificial intelligence," "machine learning," "deep learning," and "blockchain." This cluster reflects a growing body of research dedicated to exploring how cutting-edge digital technologies are being integrated into educational supervision processes. AI-based systems are increasingly being utilized for predictive analytics, performance monitoring, and personalized feedback mechanisms in schools. Blockchain, on the other hand, offers potential for secure, transparent data management and credential verification. The presence of terms such as "decision-making" and "clinical decision-making" suggests a cross-pollination of concepts from healthcare and data science into education, indicating a trend toward automated or semi-automated supervisory mechanisms supported by intelligent systems.

CLUSTER 2 (green cluster) centered around the term "human", which serves as the most dominant node, indicating the high frequency and centrality of human-related concerns in the literature. This cluster also includes terms such as "technology," "education," "COVID-19," and "questionnaire," suggesting that much of the research focuses on how digital supervision practices affect human participants in educational settings, particularly during and after the pandemic. The pandemic context has catalyzed rapid adoption of digital tools for instructional monitoring, curriculum evaluation, and remote learning oversight. The green cluster illustrates the emphasis on the humanization of technology—how educators, students, and school leaders interact with digital systems under crisis-driven educational reforms.

CLUSTER 3 (blue cluster) features terms such as "China," "green technology," and "information management," pointing to geopolitical and policy-oriented research. This cluster underscores the influence of national policy environments, particularly in countries like China, on the implementation of digital education reforms. It may also reflect international comparisons or country-specific case studies examining how different education systems adopted or regulated digital tools for school improvement during and after the COVID-19 crisis. The presence of "green technology" suggests that sustainability and digital infrastructure policies are also part of the broader discourse.

CLUSTER 4 (yellow cluster) which reflects methodological considerations such as "controlled study," "retrospective study," "middle aged," and "female." Although these terms are more commonly associated with health and psychological studies, their presence in this map implies an increasing application of empirical, evidence-based research designs to assess the effectiveness of digital supervisory tools in education. The inclusion of demographic terms suggests that researchers are accounting for varied user experiences and outcomes, potentially comparing effectiveness across different age groups and gender identities. This movement toward scientific rigor reflects an attempt to evaluate educational technologies not just by their availability or novelty, but by their measurable impact on teaching, learning, and school improvement outcomes.

Overall, the co-word map reveals a richly interconnected research landscape. The intersection of the human-centered themes (green), technological innovation (red), rigorous methodology (yellow), and policy/geographic specificity (blue) indicates that post-pandemic research on school improvement supervision via digital tools is inherently interdisciplinary. It merges insights from education, data science, public health, and policy studies. The co-occurrence of these terms reveals the field's progression toward more complex, systemic understandings of how digital platforms can be harnessed not just for instruction, but for strategic educational leadership and accountability.

This bibliometric evidence supports the conclusion that while the COVID-19 pandemic accelerated the adoption of digital platforms, it also initiated a broader, ongoing transformation in how educational quality and improvement are conceptualized and managed.

1.   Implications of the Study

4.1 Theoretical Implications

The theoretical implications of this study illustrates a significant gap in the existing body of knowledge concerning the integration of digital tools and platforms in school supervision processes, particularly in the context of post-COVID-19 education. Despite the rapid digital transformation in educational settings during and after the pandemic, there is limited theoretical development explaining how these technologies reshape supervisory practices, leadership models, and decision-making processes in school improvement initiatives. This gap suggests the need to expand existing educational management theories to account for the role of digital mediation in supervision, including frameworks that address remote monitoring, data-driven decision-making, and the dynamics of virtual collaboration. With this deficiency, the study advances the theoretical discourse by advocating the transformation of conventional supervisory frameworks to encompass digital competencies, technology integration approaches, and their broader implications for school improvement.

4.2 Practical Implications

The findings from this bibliometric analysis reveals a significant gap in research on the use of digital tools for supervising school improvement in the post-COVID-19 context. Policymakers and school leaders should prioritize investments in digital infrastructure and capacity-building to enhance accountability and data-driven decision-making (Alam et al., 2025; UNESCO IIEP, 2025). For instance, Philippine schools have begun piloting AI-powered analytics within learning management systems to monitor student performance and provide targeted feedback to teachers (Villaver & Cabigas, 2025; Co, 2025). Internationally, Finland has adopted digital platforms for school self-evaluation, resource tracking, and instructional quality assurance, reflecting a trust-based model of supervision supported by technology (Education Finland, 2025).

These cases illustrate how digital supervision mechanisms can promote transparency, responsiveness, and evidence-informed leadership. However, the absence of established frameworks and comprehensive research calls for the development of best practices and interdisciplinary studies tailored to post-pandemic educational needs. Addressing this gap can enhance the effectiveness, efficiency, and adaptability of school supervision in an increasingly digital educational landscape.

Conclusion, Limitations, and Future Recommendations

Conclusion

In conclusion, this bibliometric analysis demonstrates a significant research gap concerning the use of digital tools and platforms in supervising school improvement, particularly in the post-COVID-19 educational landscape. Despite the rapid digital transformation triggered by the pandemic, scholarly attention remains limited in exploring how these technologies are integrated into supervision practices to enhance educational outcomes. The findings reveal a fragmented and relatively sparse body of literature, suggesting that this critical area has not kept pace with the broader digitalization of education. As schools increasingly rely on digital systems for administrative and instructional support, the lack of comprehensive studies on their supervisory applications underscores an urgent need for focused research to inform policy, training, and implementation strategies in the new normal of education.

Limitations

One key limitation of this bibliometric study is the scarcity of existing literature specifically addressing the use of digital tools and platforms for supervising school improvement in the post-COVID-19 context. This research gap limits the depth of analysis that can be conducted, as there is a lack of comprehensive and focused scholarly work that explicitly connects digital supervision practices with school improvement outcomes in the aftermath of the pandemic. Consequently, the bibliometric mapping may not fully capture the complexity or evolving nature of digital supervision trends, and there is a risk of overlooking emerging but underrepresented contributions. Additionally, the relatively recent emergence of this topic means that many innovative practices may not yet be documented in peer-reviewed publications, thereby restricting the scope and generalizability of the findings. In addition to that, this study relied exclusively on the Scopus database. While Scopus offers extensive coverage of peer-reviewed literature, the use of a single database may have excluded relevant education-specific studies indexed elsewhere, such as in ERIC or Web of Science. This limitation should be addressed in future research by integrating multiple databases to strengthen the comprehensiveness and generalizability of bibliometric findings.

Future Research Recommendations

Future research should take a comprehensive and forward-looking approach. One key recommendation is to investigate effective digital supervision models across diverse educational contexts, such as urban and rural settings or public and private institutions, to identify adaptable and context-sensitive practices. Longitudinal studies are also needed to examine the sustained impact of digital supervision strategies that emerged during the pandemic, shedding light on their long-term influence on school improvement outcomes. Additionally, research should delve into the integration of advanced technologies, including artificial intelligence and learning analytics, to enhance supervisory processes and support data-driven decision-making. Exploring the perceptions and readiness of stakeholders—school leaders, supervisors, teachers, and students—can provide valuable insights into the human factors that affect the adoption and effectiveness of digital supervision tools. Evaluative studies on specific platforms (e.g., Google Workspace, Zoom, Microsoft Teams, or LMS tools) can further determine their utility, usability, and effectiveness in supporting supervisory functions. Moreover, policy-focused research is necessary to uncover gaps in infrastructure, training, and funding that hinder the implementation of digital supervision systems. Finally, the development and validation of hybrid supervision frameworks that blend digital and face-to-face modalities could offer sustainable models for continuous school improvement in a rapidly evolving educational landscape.

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