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Research on mutual cooperation among scholars or research institutions has become more and more common. The purpose of this paper is to explore the current status of cooperation between scholars and research institutions in the field of Chinese education. In this paper, we use the method of the complex network to analyze the cooperative behavior of academic papers published by Chinese educational scholars by collecting academic papers on education leadership, education policy, quality education, and vocational education. Our conclusions show that most of the academic papers published by Chinese educational scholars are non-cooperative. In the authors of the co-authored papers, there is a significant "Matthew effect", that is, some key scholars in these fields that link the collaborators. Lastly, there is no obvious aggregation effect between the authors of the co-authored papers which indicating a widespread and extensive connection between the collaborators. The above conclusions provide valuable insights into our understanding of the cooperative behavior of Chinese education scholars.

The study presents a bibliometric network analysis of the two most recent schools reforms in Norway. Two research questions have been pursued: First, do the government-appointed expert commission use (in Green Papers) the same type of knowledge as 'evidence' for their reviews and recommendations as the Ministry of Education and Research (as reflected in the White Papers)? How has the use of 'evidence' changed over the two reform periods? Second, which body of knowledge amassed by the expert commission has the Ministry of Education and Science actually used for policy formulation? The network analysis shows (i) distinct changes in reference patterns over the two reform periods (e.g., average number of references more than doubled and references to international texts increased significantly), and (ii) an unexpectedly low usage of the 'evidence' presented by the expert commissions. The Ministry of Education and Research only draws on 9.5 percent of the references presented by the expert commissions. Strikingly, almost all of the adopted references are from a commissioned report that locally adapted and translated OECD's Definitions and Selections of Competencies project. The authors suggest 'studying up' and paying more attention to how scientific 'evidence' is actually used, translated, and edited at the political level.

Pre-evaluating scientific paper quality aids in alleviating peer review pressure and fostering scientific advancement. Although prior studies have identified numerous quality-related features, their effectiveness and representativeness of paper content remain to be comprehensively investigated. Addressing this issue, we propose a content-based interpretable method for pre-evaluating the quality of scientific papers. Firstly, we define quality attributes of computer science (CS) papers as integrity, clarity, novelty, and significance, based on peer review criteria from 11 top-tier CS conferences. We formulate the problem as two classification tasks: Accepted/Disputed/Rejected (ADR) and Accepted/Rejected (AR). Subsequently, we construct fine-grained features from metadata and knowledge entity networks, including text structure, readability, references, citations, semantic novelty, and network structure. We empirically evaluate our method using the ICLR paper dataset, achieving optimal performance with the Random Forest model, yielding F1 scores of 0.715 and 0.762 for the two tasks, respectively. Through feature analysis and case studies employing SHAP interpretable methods, we demonstrate that the proposed features enhance the performance of machine learning models in scientific paper quality evaluation, offering interpretable evidence for model decisions.

We investigate the sub-networks involved in education policy in Israel in recent years, using Mixed Methods Social Networks Analysis - drawn from combined analysis of qualitative and quantitative data. Our objective was to comprehensively explore the Israeli education policy network to deliver an understanding of its structure, actors, and relationships. Our research offers a descriptive, analytical, and interpretive account of the contemporary Israeli education policy sector, including the actors involved, central policy sub-networks and organizations, and their relationships. We analyze dependence relations within the sub-networks using Resource Dependency Theory and Policy Networks Typology. Our findings contribute to understanding the dynamics of Israeli education policy networks and their perceived influence on policy-making and enactment processes. To the international field of educational policy-related research, we introduce a novel category of policy network actors, previously unaddressed as a distinct type. We have termed this category 'Ethos networks' to characterize this group of actors and elaborate on its significance within the field. Additionally, we underline the importance of considering external societal and political factors in education policy-making.

Investigating the stories behind the makers of 3D models of crystals has proved unexpectedly unstraightforward. Drawing on actor-network theory (ANT), this article investigates the references behind a set of models of mineralogical crystals made of pasteboard held by National Museums Scotland (NMS), to uncover the history and tradition of such models and the role that pedagogy plays in their stories. The contributions of many of the main actors have been neglected, dismissed, ignored, forgotten, or otherwise rendered invisible in the historical record, either intentionally or accidentally. It became clear, however, that there was a significant tradition of modelling in paper, from the earliest years of learning, play and education. Many more people than those intending to become professional model makers were capable of making paper models of subjects from the crystals found in rocks, to buildings made of them.

Combining traditional and digital methods, this essay models a new toolbox for analyzing the knotty problem of how many letters in the State Papers were introduced to the archive through interception. Estimates by scholars vary widely. Using the State Papers Foreign metadata for the reign of Elizabeth I, we employ a method of "layered searching" to find letters involving a third party. By structuring the communications as a network, we weight edges between correspondents and the Tudor State to distinguish acts of interception from forwarded letters or spy reports. These methods suggest likely candidates for interception with a sliding scale of confidence, helping to identify two broad models of letter interception outside England, which we dub "military-diplomatic" and "catch-and-release." Overall, we estimate more than 5 percent of the collection to have been intercepted, highlighting a continuous network of intercepting officials from the Dutch Revolt to the imprisonment of Mary Stuart. [ABSTRACT FROM AUTHOR]

Egocentric networks represent a popular research design for network research. However, to what extent and under what conditions egocentric network centrality can serve as reasonable substitutes for their sociocentric counterparts are important questions to study. The answers to these questions are uncertain simply because of the large variety of networks. Hence, this paper aims to provide exploratory answers to these questions by analyzing both empirical and simulated data. Through analyses of various empirical networks (including some classic albeit small ones), this paper shows that egocentric betweenness approximates sociocentric betweenness quite well (the correlation is high across almost all the networks being examined) while egocentric closeness approximates sociocentric closeness only reasonably well (the correlation is a bit lower on average with a larger variance across networks). Simulations also confirm this finding. Analyses further show that egocentric approximations of betweenness and closeness seem to work well in different types of networks (as featured by network size, density, centralization, reciprocity, transitivity, and geodistance). Lastly, the paper briefly presents three ideas to help improve egocentric approximations of centrality measures.

Background: Learner profiles detected from digital trace data are typically triangulated with survey data to explain those profiles based on learners' internal conditions (e.g., motivation). However, survey data are often analysed with limited consideration of the interconnected nature of learners' internal conditions. Objectives: Aiming to enable a thorough understanding of trace-based learner profiles, this paper presents and evaluates a comprehensive approach to analysis of learners' self-reports, which extends conventional statistical methods with psychological networks analysis. Methods: The study context is a massive open online course (MOOC) aimed at promoting physical activity (PA) for health. Learners' (N = 497) perceptions related to PA, as well as their self-efficacy and intentions to increase the level of PA were collected before and after the MOOC, while their interactions with the course were logged as digital traces. Learner profiles derived from trace data were further examined and interpreted through a combined use of conventional statistical methods and psychological networks analysis. Results and Conclusions: The inclusion of psychological networks in the analysis of learners' self-reports collected before the start of the MOOC offers better understanding of trace-based learner profiles, compared to the conventional statistical analysis only. Likewise, the combined use of conventional statistical methods and psychological networks in the analysis of learners' self-reports before and after the MOOC provided more comprehensive insights about changes in the constructs measured in each learner profile. Major Takeaways: The combined use of conventional statistical methods and psychological networks presented in this paper sets a path for a comprehensive analysis of survey data. The insights it offers complement the information about learner profiles derived from trace data, thus allowing for a more thorough understanding of learners' course engagement than any individual method or data source would allow.

Nationally and internationally equity in education has become a key goal. In Norway, a White Paper has been tabled to address how equity can be improved through education. In this paper the pedagogic and knowledge orientation of the initiatives are analyzed and discussed in relation to two models of equity: "equity through equality" and "equity through diversity." The paper finds that although contradictions are present, the Norwegian ministry clearly favors the equality model. The author claims that the presented policies can be understood as a response to the global educational trend that Apple refers to as "conservative modernization." This can further be related to Bernstein's "Totally Pedagogised Society," where the adaptable, trainable individual is a key notion. The paper concludes that the lack of attention given to the diversity of citizens may be a major shortcoming, as lack of recognition is in many ways what causes educational failure in the first place. (Contains 3 tables and 7 footnotes.)

The present study analyzes the offshoring network constructed from the information contained in the Panama Papers, characterizing worldwide regions and countries as well as their intra- and inter-relationships. The Panama Papers 2016 divulgence is the largest leak of offshoring and tax avoidance documentation. The document leak, with a volume content of approximately 2.6 terabytes, involves more than two hundred thousand enterprises in more than two hundred countries. From this information, the offshore connections of individuals and companies are constructed and aggregated using their countries of origin. The top offshore financial regions and countries of the network are identified, and their intra- and inter-relationship are mapped and described. We are able to identify the top countries in the offshoring network and characterize their connectivity structure, discovering the more prominent actors in the worldwide offshoring scenario and their range of influence.

Pre-evaluating scientific paper quality aids in alleviating peer review pressure and fostering scientific advancement. Although prior studies have identified numerous quality-related features, their effectiveness and representativeness of paper content remain to be comprehensively investigated. Addressing this issue, we propose a content-based interpretable method for pre-evaluating the quality of scientific papers. Firstly, we define quality attributes of computer science (CS) papers as integrity , clarity , novelty , and significance , based on peer review criteria from 11 top-tier CS conferences. We formulate the problem as two classification tasks: Accepted/Disputed/Rejected (ADR) and Accepted/Rejected (AR). Subsequently, we construct fine-grained features from metadata and knowledge entity networks, including text structure, readability, references, citations, semantic novelty, and network structure. We empirically evaluate our method using the ICLR paper dataset, achieving optimal performance with the Random Forest model, yielding F1 scores of 0.715 and 0.762 for the two tasks, respectively. Through feature analysis and case studies employing SHAP interpretable methods, we demonstrate that the proposed features enhance the performance of machine learning models in scientific paper quality evaluation, offering interpretable evidence for model decisions. • Define four criteria for quality evaluation of scientific papers: integrity, clarity, novelty, and significance. • Propose a framework for quality evaluation of scientific papers based on coarse features and knowledge entity network. • An effective algorithm for measuring the novelty and significance of scientific papers based on knowledge entity networks. • Create and release a rigorous dataset, which could serve as the gold standard for quality evaluation of scientific papers. • Conduct extensive experiments to validate the effectiveness of the proposed framework. [ABSTRACT FROM AUTHOR]