The goal of the Department of Defense Net-Centric Data Strategy is to improve data sharing throughout the DoD. Data sharing is a critical element of interoperability in the emerging system-of-systems. Achieving interoperability requires the elimination of two types of data heterogeneity: differences of syntax and differences of semantics. This paper builds a path toward semantic uniformity through application of a disciplined approach to ontology. An ontology is a consensus framework representing the types of entities (...) within a given domain and the relations between them. The construction of an ontology begins when a Community of Interest (COI) identifies its authoritative data sources (ADS), which are usually manifest in relevant doctrinal publications, glossaries, data dictionaries, and logical data models. The identified terms are then defined in relation to a common logical framework that has been designed to ensure interoperability with other ontologies created on the basis of the same strategy. As will be described, the Command and Control (C2) Ontology will include representations of a substantial number of entities within the Command and Control (C2) domain. If domain ontologies (e.g. Strike and Counterinsurgency) semantically align with the C2 Ontology, then a substantial barrier to systems interoperability is thereby crossed. (shrink)

Leonelli (2016) suggested a relational view of data against a representational view by emphasizing data-centric biology rather than the theory-centric tradition in the philosophy of science. This is because the first view allows for data journeys across laboratories using public database resources, whereas the second does not. This paper examines Leonelli’s strategies to defend the relational view of data. Contrary to Leonelli’s intention, it indicates that her strategies led to unnecessary misunderstandings of the relationships (...) among data, representation, and evidential values. It will be argued that evidential values of data are inevitably based on a representational feature and that it is better to reconcile both views of data as complementary rather than contrasting. (shrink)

This paper addresses a relatively new mode of ecological research: data synthesis studies. Data synthesis studies involve reusing data to create a general model as well as a reusable, aggregated dataset. Using a case from movement ecology, I analyse the trade-offs and strategies involved in data synthesis. Like theoretical ecological modelling, I find that synthesis studies involve a modelling trade-off between generality, precision and realism; they deal with this trade-off by adopting a pragmatic kludging strategy. (...) I also identify an additional trade-off, the synthesis trade-off, between making data easy to synthesise for a particular project, on the one hand, and facilitating data reuse for other projects, on the other. In response to this synthesis trade-off, researchers create flexible datasets that are relatively easy to use for particular projects and can be adjusted to suit some other purposes. The flexibility compromise is also found in broader open data efforts, making it a significant element in the future of data-intensive ecology. (shrink)

In Bulgaria, integrating technology and innovation is crucial for advancing sustainable healthcare disaster management, enhancing disaster response and recovery, and minimizing long-term environmental and social impacts. The purpose of the study is to assess the impact of modern technological innovations on the effectiveness of disaster management in health care in Bulgaria with a focus on Health Information Systems (HIS), Telemedicine, Telehealth, e-Health, Electronic Health Records, Artificial Intelligence (AI), Public Communication Platforms, and Data Security and Privacy. These innovations, when integrated (...) effectively, can significantly strengthen Bulgaria's preparedness and response capabilities, improving efficiency and reducing the environmental footprint of disaster interventions. Collaboration with technology experts, research institutions, and international organizations is essential for successful implementation. The research aims to assess how these technologies can enhance disaster management efficacy, adopting a methodical approach using Systematic Literature Reviews (SLRs). Systematic Literature Reviews (SLRs) utilize precise criteria for research selection and evaluation to reduce bias, systematically compiling and analyzing data from various studies to offer evidence-based insights. They are crucial for uncovering research gaps, indicating areas needing further exploration. Findings highlight the transformative potential of technology integration in streamlining communication, data management, and operational efficiency. The study underscores the urgent need for an integrated approach and a culture of innovation within the healthcare sector, emphasizing ongoing assessment and adaptation of technology-based strategies. While acknowledging limitations and calling for further research, the study provides valuable insights into Bulgaria's healthcare disaster management strategies and sets the stage for future investigations to refine and expand upon these strategies. It advocates for a strategic framework guiding the efficient integration of technology into disaster management, aiming for resilient and patient-centric healthcare systems. (shrink)

In times of crises, public health leaders may claim that trials of public health interventions are unethical. One reason for this claim can be that equipoise—i.e. a situation of uncertainty and/or disagreement among experts about the evidence regarding an intervention—has been disturbed by a change of collective expert views. Some might claim that equipoise is disturbed if the majority of experts believe that emergency public health interventions are likely to be more beneficial than harmful. However, such beliefs are not always (...) justified: where high quality research has not been conducted, there is often considerable residual uncertainty about whether interventions offer net benefits. In this essay we argue that high-quality research, namely by means of well-designed randomized trials, is ethically obligatory before, during, and after implementing policies in public health emergencies (PHEs). We contend that this standard applies to both pharmaceutical and non-pharmaceutical interventions, and we elaborate an account of equipoise that captures key features of debates in the recent pandemic. We build our case by analyzing research strategies employed during the COVID-19 pandemic regarding drugs, vaccines, and non-pharmaceutical interventions; and by providing responses to possible objections. Finally, we propose a public health policy reform: whenever a policy implemented during a PHE is not grounded in high-quality evidence that expected benefits outweigh harms, there should be a planned approach to generate high-quality evidence, with review of emerging data at preset time points. These preset timepoints guarantee that policymakers pause to review emerging evidence and consider ceasing ineffective or even harmful policies, thereby improving transparency and accountability, as well as permitting the redirection of resources to more effective or beneficial interventions. (shrink)

The term “Complex Systems Biology” was introduced a few years ago [Kaneko, 2006] and, although not yet of widespread use, it seems particularly well suited to indicate an approach to biology which is well rooted in complex systems science. Although broad generalizations are always dangerous, it is safe to state that mainstream biology has been largely dominated by a gene-centric view in the last decades, due to the success of molecular biology. So the one gene - one trait approch, (...) which has often proved to be effective, has been extended to cover even complex traits. This simplifying view has been appropriately criticized, and the movement called systems biology has taken off. Systems biology [Noble, 2006] emphasizes the presence of several feedback loops in biological systems, which severely limit the range of validity of explanations based upon linear causal chains (e.g. gene → behaviour). Mathematical modelling is one the favourite tools of systems biologists to analyze the possible effects of competing negative and positive feedback loops which can be observed at several levels (from molecules to organelles, cells, tissues, organs, organisms, ecosystems). Systems biology is by now a well-established field, as it can be inferred by the rapid growth in number of conferences and journals devoted to it, as well as by the existence of several grants and funded projects.Systems biology is mainly focused upon the description of specific biological items, like for example specific organisms, or specific organs in a class of animals, or specific genetic-metabolic circuits. It therefore leaves open the issue of the search for general principles of biological organization, which apply to all living beings or to at least to broad classes. We know indeed that there are some principles of this kind, biological evolution being the most famous one. The theory of cellular organization also qualifies as a general principle. But the main focus of biological research has been that of studying specific cases, with some reluctance to accept (and perhaps a limited interest for) broad generalizations. This may however change, and this is indeed the challenge of complex systems biology: looking for general principles in biological systems, in the spirit of complex systems science which searches for similar features and behaviours in various kinds of systems. The hope to find such general principles appears well founded, and I will show in Section 2 that there are indeed data which provide support to this claim. Besides data, there are also general ideas and models concerning the way in which biological systems work. The strategy, in this case, is that of introducing simplified models of biological organisms or processes, and to look for their generic properties: this term, borrowed from statistical physics, is used for those properties which are shared by a wide class of systems. In order to model these properties, the most effective approach has been so far that of using ensembles of systems, where each member can be different from another one, and to look for those properties which are widespread. This approach was introduced many years ago [Kauffman, 1971] in modelling gene regulatory networks. At that time one had very few information about the way in which the expression of a given gene affects that of other genes, apart from the fact that this influence is real and can be studied in few selected cases (like e.g. the lactose metabolism in E. coli). Today, after many years of triumphs of molecular biology, much more has been discovered, however the possibility of describing a complete map of gene-gene interactions in a moderately complex organism is still out of reach. Therefore the goal of fully describing a network of interacting genes in a real organism could not be (and still cannot be) achieved. But a different approach has proven very fruitful, that of asking what are the typical properties of such a set of interacting genes. Making some plausible hypotheses and introducing some simplifying assumptions, Kauffman was able to address some important problems. In particular, he drew attention to the fact that a dynamical system of interacting genes displays selforganizing properties which explain some key aspects of life, most notably the existence of a limited number of cellular types in every multicellular organism (these numbers are of the order of a few hundreds, while the number of theoretically possible types, absent interactions, would be much much larger than the number of protons in the universe). In section 3 I will describe the ensemble based approach in the context of gene regulatory networks, and I will show that it can describe some important experimental data. Finally, in section 4 I will discuss some methodological aspects. (shrink)

This paper is aimed at analyzing the effects of banking relationship on performance of Vietnamese firms in Food and Beverage (F&B), one of the highest potential sectors. Panel data of 170 observations covers 34 F&B firms listed in the Vietnam stock exchanges in the period 2014-2018. The fixed effect model (FEM) is applied. The key findings are: First, short-term loan financing, leverage, and fixed asset ratios all negatively impacted on F&B firm performance, while firm size and net profit margin (...) had positive impacts. These findings were consistent with previous studies. Second, the opposite results with previous studies were: (i) negative corelation of ROE and number of banks firms working with, as F&B firms were inefficient in selecting bank partners; (ii) positive relation of short-term liabilities ratio and ROA/ROE, as F&B firms utilize other non-bank liabilities shortly; (iii) foreign ownership had negative relationship with ROA& ROE. Foreign investors did not have significant roles in most F&B firms. Third, long-term borrowing from banks, state ownership and ages all insignificantly correlated with firm performance. Recommendations to F&B firms include: (1) Reduce the short- term loans and fixed assets investment, while increase the cheap equity funding sources via shareholders (2) Be selective in working with banks to have better fees and interest saved with banks. (3) Utilize other short-term liabilities, including payables and advances – the low-cost funding sources. F&B firms have good bargaining powers in requesting advances from their clients. (4) Have smart buy-in strategies on foreign ownership. (shrink)

With the rapid development of information technology, the electricity consumption of Internet Data Centers (IDCs) increases drastically, resulting in considerable carbon emissions that need to be reduced urgently. In addition to the introduction of Renewable Energy Sources (RES), the joint use of the spatial migration capacity of IDC workload and the temporal flexibility of the demand of Electric Vehicle Charging Stations (EVCSs) provides an important means to change the carbon footprint of the IDC. In this paper, a sustainability improvement (...) strategy for the IDC carbon emission reduction was developed by coordinating the spatial-temporal dispatch flexibilities of the IDC workload and the EVCS demand. Based on the Minkowski sum algorithm, a generalized flexible load model of the EVCSs, considering traffic flow and Road Impedance (RI) was formulated. The case studies show that the proposed method can effectively increase the renewable energy consumption, reduce the overall carbon emissions of multi-IDCs, reduce the energy cost of the DCO, and utilize the EV dispatching potential. Discussions are also provided on the relationship between workload processing time delay and the renewable energy consumption rate. (shrink)

This research proposes a novel Smart Deduplication Framework (SDF) designed to identify and eliminate redundant data, thus optimizing storage usage and improving data retrieval speeds. The framework leverages a hybrid cloud architecture, combining the scalability of public clouds with the security of private clouds. By employing a combination of client-side hashing, metadata indexing, and machine learning-based duplicate detection, the framework achieves significant storage savings without compromising data integrity. Real-time testing on a hybrid cloud setup demonstrated a 65% (...) reduction in storage needs and a 40% improvement in data retrieval times. Additionally, the system employs blockchain for immutable logging of deduplication activities, enhancing transparency and traceability. This study concludes with an evaluation of the deduplication framework's impact on cost efficiency, system performance, and potential scalability. Future enhancements aim to integrate multi-cloud interoperability and advanced compression algorithms to further refine storage management. (shrink)

By embracing AI-driven HR analytics, organizations can anticipate market shifts, prepare their workforce for future challenges, and stay ahead of the competition. This study outlines the essential components of AI-driven HR analytics, demonstrates its impact on workforce agility, and concludes with potential future enhancements to further optimize HR functions. Key words: Predictive Workforce Analytics, Talent Optimization, Machine Learning in.

Archaeological data are shadowy in a number of senses. Not only are they notoriously fragmentary but the conceptual and technical scaffolding on which archaeologists rely to constitute these data as evidence can be as constraining as it is enabling. A recurrent theme in internal archaeological debate is that reliance on sedimented layers of interpretative scaffolding carries the risk that “preunderstandings” configure what archaeologists recognize and record as primary data, and how they interpret it as evidence. The selective (...) and destructive nature of data capture in archeology further suggests that there may be little scope for putting “legacy” data to work in new ways. And yet archaeologists have been strikingly successful in mining old datasets for new insights. I situate these concerns in the broader context of debate about the epistemic standing of the historical sciences, and then consider three strategies by which archaeologists address the challenges posed by legacy data. The first two – secondary retrieval and recontextualization – are a matter of reconfiguring the scaffolding that underpins evidential reasoning. The third turns on redeploying old data in the context of computational models that support the experimental simulation of the cultural systems and contexts under study. (shrink)

Non-technical summary: -/- When developing and deploying negative emissions technologies (NETs), little attention has been paid to where. On the one hand, one might develop NETs where they are likely to contribute most to global mitigation targets, contributing to a global climate solution. On the other hand, one might develop NETs where they can help support development on a regional basis, justified by regional demands. I defend these arguments and suggest that they reflect the values of efficiency and responding to (...) need, respectively. To the extent that these values conflict, they introduce what I call the Need-Efficiency Trade-off Effect (‘NET Effect’). -/- Technical summary: -/- Unlike other geoengineering methods, the effectiveness of negative emissions technologies (NETs) tends to be sensitive to regional siting. This paper argues that this point raises morally and legally important implications by identifying a trade-off between ‘efficiency’ and ‘need’. First, it introduces two arguments justifying NETs: one focused on contributions to global mitigation and the other focused on contributions to regional development. Second, reflecting the two arguments, the paper discusses the moral values of efficiency and need, respectively. For instance, if the strategy is to try to use NETs to maximize expected mitigation contributions to reflect efficiency, then deployment should occur in regions with the best prospects for success (e.g. Western countries). However, if the strategy is to try to use NETs to improve the chances of simultaneous development and mitigation to respond to need, then deployment should occur in regions with limited development and expected growth of demand for NETs (e.g. Asian countries). When these values conflict, I call that a Need-Efficiency Trade-off Effect (‘NET Effect’). The paper concludes by considering the NET Effect in the context of bioenergy with carbon capture and storage as well as direct air carbon capture and storage. [Open access]. (shrink)

The paper outlines critical aspects concerning the increasing use of big data in agriculture and farming. In particular, the aim is to shed light on the emerging dominance of the platform economy in the field of agriculture and food production. To analyze those power structures shaping this dynamic, we start with brief observations on the general relationship between digitization and agriculture and explain the platform economy, its general business model, and the proprietary forms of market power emerging from it. (...) Subsequently, we analyze the implications of the involvement of platform-economic companies in the agricultural sector. To do so, we critically examine several key examples that illuminate the strategies and ultimate objectives of those key tech players involved in this transition––particularly, two of the most dominant cloud providers, Alphabet and Amazon. Finally, we identify the main problems that can potentially emerge, and that can already be observed, from Big Tech’s involvement in agriculture and food production: (1) epistemic asymmetry (2) the erosion of privacy (3) potential harms to smaller farms and farmers, and (4) systemic dependencies on a monopolist data infrastructure. As we argue, these four dimensions are not only essential to take into account, but they also ultimately need to be responded to politically. From a policy perspective, to maintain data justice and epistemic symmetry, and to avoid the risks highlighted, we suggest––next to stressing the need for critical scholarship––to establish a democratically governed data trust, rely on open source technology, and fundamentally commit to the principle of collective data sovereignty. -/- Keywords: big tech, data sovereignty, digital farming, digital agriculture, surveillance capitalism, platform economy. (shrink)

This theme issue has the founding ambition of landscaping Data Ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing, and use), algorithms (including AI, artificial agents, machine learning, and robots), and corresponding practices (including responsible innovation, programming, hacking, and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data Ethics builds on the foundation provided by (...) Computer and Information Ethics but, at the same time, it refines the approach endorsed so far in this research field, by shifting the Level of Abstraction of ethical enquiries, from being information-centric to being data-centric. This shift brings into focus the different moral dimensions of all kinds of data, even the data that never translate directly into information but can be used to support actions or generate behaviours, for example. It highlights the need for ethical analyses to concentrate on the content and nature of computational operations — the interactions among hardware, software, and data — rather than on the variety of digital technologies that enables them. And it emphasises the complexity of the ethical challenges posed by Data Science. Because of such complexity, Data Ethics should be developed from the start as a macroethics, that is, as an overall framework that avoids narrow, ad hoc approaches and addresses the ethical impact and implications of Data Science and its applications within a consistent, holistic, and inclusive framework. Only as a macroethics Data Ethics will provide the solutions that can maximise the value of Data Science for our societies, for all of us, and for our environments. (shrink)

Atomically precise manufacturing (APM) is the assembly of materials with atomic precision. APM does not currently exist, and may not be feasible, but if it is feasible, then the societal impacts could be dramatic. This paper assesses the net societal impacts of APM across the full range of important APM sectors: general material wealth, environmental issues, military affairs, surveillance, artificial intelligence, and space travel. Positive effects were found for material wealth, the environment, military affairs (specifically nuclear disarmament), and space travel. (...) Negative effects were found for military affairs (specifically rogue actor violence and AI. The net effect for surveillance was ambiguous. The effects for the environment, military affairs, and AI appear to be the largest, with the environment perhaps being the largest of these, suggesting that APM would be net beneficial to society. However, these factors are not well quantified and no definitive conclusion can be made. One conclusion that can be reached is that if APM R&D is pursued, it should go hand-in-hand with effective governance strategies to increase the benefits and reduce the harms. (shrink)

This paper presents an ethical framework designed to support the development of critical data literacy for research methods courses and data training programmes in higher education. The framework we present draws upon our reviews of literature, course syllabi and existing frameworks on data ethics. For this research we reviewed 250 research methods syllabi from across the disciplines, as well as 80 syllabi from data science programmes to understand how or if data ethics was taught. We (...) also reviewed 12 data ethics frameworks drawn from different sectors. Finally, we reviewed an extensive and diverse body of literature about data practices, research ethics, data ethics and critical data literacy, in order to develop a transversal model that can be adopted across higher education. To promote and support ethical approaches to the collection and use of data, ethics training must go beyond securing informed consent to enable a critical understanding of the techno-centric environment and the intersecting hierarchies of power embedded in technology and data. By fostering ethics as a method, educators can enable research that protects vulnerable groups and empower communities. (shrink)

My belief that Socrates was wise, and your belief that Socrates was mortal can be said to have a common focus, insofar as both these thoughts are about Socrates. In Peter Geach’s terminology, the objects of our beliefs bear the feature of intentional identity, because our beliefs share the same putative target. But what if it turned out that Socrates never existed? Can a pair of thoughts share a common focus if the object both thoughts are about, does not actually, (...) really exist? Object-centric accounts of intentionality which explain the aboutness or directedness of thought in terms of the intentional object the thought in question is about, contend that thoughts which share a common focus do so in virtue of both thoughts simply being about the same intentional object. However, Alexander Sandgren contends that such theories face difficulties in explaining a puzzle of intentional identity put forward by Walter Edelberg, in which a pair of sentences seem to differ in truth value but are purportedly logically equivalent on the object-centric theory. If this is right, then it seems that any account which explains intentionality with reference to an intentional object is threatened by this result, whether this object be abstract, merely possible, Meinongian, or otherwise. In this paper, I argue that Edelberg’s Puzzle is analogous to Frege’s Puzzle and the same tools conventionally used to solve Frege’s Puzzle can be used to solve Edelberg’s Puzzle. I then propose a new object-centric solution to Edelberg’s Puzzle which takes into account modes of presentation and which is able to accommodate all the relevant linguistic data. (shrink)

Biodiversity science is in a pivotal period when diverse groups of actors—including researchers, businesses, national governments, and Indigenous Peoples—are negotiating wide-ranging norms for governing and managing biodiversity data in digital repositories. These repositories, often called biodiversity data portals, are a type of organization for which governance can address or perpetuate the colonial history of biodiversity science and current inequities. Researchers and Indigenous Peoples are developing and implementing new strategies to examine and change assumptions about which agents should count (...) as salient participants in scientific projects, especially in projects that build and manage large digital data portals. Two notable efforts are the FAIR (Findable, Accessible, Interoperable, Reusable) and CARE (Collective benefit, Authority, Responsibility, Ethics) Principles for scientific data management and governance. To characterize how these principles influence the governance of biodiversity data portals, we develop an account of fit-for-use data that makes explicit its social as well as technical conditions in relation to agents and purposes. The FAIR Principles, already widely adopted by biodiversity researchers, prioritize machine agents and efficient computation, while the CARE Principles prioritize Indigenous Peoples and their data sovereignty. Both illustrate the potency of an emerging general strategy by which groups of actors craft and implement governance principles for data fitness-of-use to change assumptions about who are salient participants in data science. (shrink)

Grounded theory methodology is perceived as challenging due to its systematic and rigorous process. However, this is because most people do not realize that the strategies used in the grounded theory data analysis process are used by laypeople and professionals regularly, if not daily. This article aims to help others interested in grounded theory with a background in qualitative data analysis feel comfortable engaging in the methodology and constructing multiple theories in the same study. It shares my latest (...) experience incorporating various data analysis strategies with the constructivist approach: holistic and systems thinking, situational analysis, dramaturgical analysis, perspective taking, and abstraction. The examples remove the mystery from abstraction and abductive reasoning. (shrink)

Utilizarea Big Data prezintă probleme juridice semnificative, în special din punctul de vedere al protecției datelor. Cadrul juridic existent al Uniunii Europene, bazat în special pe Directiva nr. 46/95/CE și Regulamentul general privind protecția datelor cu caracter personal, oferă o protecție corespunzătoare. Dar, pentru Big Data este necesară o strategie cuprinzătoare și globală. Evoluția în timp a fost de la dreptul de a exclude pe alții la dreptul la controlul propriilor date și, în prezent, la regândirea dreptului la (...) identitate (digitală). DOI: 10.13140/RG.2.2.22989.38889. (shrink)

This paper explores the challenges and innovations in optimizing data science workflows within cloud computing environments. It begins by highlighting the critical role of data science in modern industries and the pivotal contribution of cloud computing in enabling scalable and efficient data processing. The primary focus lies in identifying and analyzing the key challenges encountered in current data science workflows deployed in cloud infrastructures. These challenges include scalability issues related to handling large volumes of data, (...) resource management complexities in optimizing computational resources, cost management strategies to balance performance with expenses, and ensuring robust data security and privacy measures. The manuscript then delves into innovative solutions and techniques aimed at addressing these challenges. It discusses advancements such as workflow automation tools and frameworks that streamline repetitive tasks, containerization technologies like Docker and Kubernetes for efficient application deployment and management, and the utilization of serverless architectures to enhance scalability and reduce operational costs. Additionally, it explores the benefits of parallel processing frameworks such as Apache Spark and Hadoop in optimizing data processing tasks. The integration of machine learning algorithms for dynamic workflow optimization and effective data management strategies in cloud environments are also examined. Through detailed case studies and application examples across various domains, the manuscript illustrates the practical implementation and outcomes of these optimization strategies. Furthermore, it discusses emerging trends in cloud technologies, the role of AI-driven automation in enhancing workflow efficiencies, and ethical considerations surrounding data science operations in cloud computing. The manuscript concludes with a summary of findings, practical recommendations for organizations seeking to enhance their data science workflows in the cloud, and insights into future research directions to address evolving challenges. (shrink)

Effective stress management strategies correlate with improved academic performance in college students, yet inconsistent findings in existing research warrant further investigation. This study explored the intricate interplay between stress levels, coping strategies, and academic achievement in HyFlex learningenvironments. A stratified random sample of 111 students from five specializations within the Bachelor of Secondary Education program participated. Utilizing a descriptive-correlational design, data were collected through validated self-report questionnaires and a weighted general average. Subsequent descriptive statistics and bivariate correlation analysis revealed (...) moderate stress levels among participants who preferred task-oriented coping strategies. Interestingly, a significant positive association was observed between stress levels and academic achievement and emotion-oriented coping strategies, while a negative correlation emerged between stress and task-oriented coping strategies. Avoidance-oriented coping strategies, conversely, displayed a significant negative association with academic success. These findings underscore the crucial role of educational institutions in providing robust support mechanisms for stress management and cultivating a task-focused learning environment to optimize student well-being and academic performance within the HyFlex model. (shrink)

Ontological realism aims at the development of high quality ontologies that faithfully represent what is general in reality and to use these ontologies to render heterogeneous data collections comparable. To achieve this second goal for clinical research datasets presupposes not merely (1) that the requisite ontologies already exist, but also (2) that the datasets in question are faithful to reality in the dual sense that (a) they denote only particulars and relationships between particulars that do in fact exist and (...) (b) they do this in terms of the types and type-level relationships described in these ontologies. While much attention has been devoted to (1), work on (2), which is the topic of this paper, is comparatively rare. Using Referent Tracking as basis, we describe a technical data wrangling strategy which consists in creating for each dataset a template that, when applied to each particular record in the dataset, leads to the generation of a collection of Referent Tracking Tuples (RTT) built out of unique identifiers for the entities described by means of the data items in the record. The proposed strategy is based on (i) the distinction between data and what data are about, and (ii) the explicit descriptions of portions of reality which RTTs provide and which range not only over the particulars described by data items in a dataset, but also over these data items themselves. This last feature allows us to describe particulars that are only implicitly referred to by the dataset; to provide information about correspondences between data items in a dataset; and to assert which data items are unjustifiably or redundantly present in or absent from the dataset. The approach has been tested on a dataset collected from patients seeking treatment for orofacial pain at two German universities and made available for the NIDCR-funded OPMQoL project. (shrink)

Education is a necessary tool for national development and for development to take place, it is important that teachers who are the driving force of passing instructions to students in the school must be properly mentored for them to carry out their assignments. It is on the basis of this background that this study was conducted. Descriptive survey research design was found suitable for the study. A multistage sampling technique was employed in this research and 100 respondents were selected for (...) the study. Four research questions and hypotheses were raised and formulated and a questionnaire titled mentoring strategies and school effectiveness was developed for data gathering. The instument was validated and the reliability co-efficient of .84 was achieved. The finding revealed that there was significant relationship between mentoring strategies and secondary school effectiveness in Ilorin East, Kwara State. It was recommended among other things that teachers should be trained using mentoring strategies and that school administrators should ensure activities which will involve pairing new with experienced teachers so that they will gain new experience from the models. (shrink)

The increasing complexity and scale of modern computing needs have led to the development and adoption of cloud computing as a ubiquitous paradigm for data storage and processing. The hybrid cloud model, which combines both public and private cloud infrastructures, has been particularly appealing to organizations that require both the scalability offered by public clouds and the security features of private clouds. Various strategies for configuring and managing resources have been developed to optimize the hybrid cloud environment. These strategies (...) aim to balance conflicting objectives such as cost-efficiency, performance optimization, security, and compliance with regulatory standards. This exploratory research focused on evaluating the efficiency and limitations of different configuration strategies in hybrid cloud environments. Findings indicate that each approach presents distinct advantages. Improving resource utilization and automating governance processes are significant advantages of Policy-based Resource Management, which leads to costeffectiveness. Intelligent routing of traffic is a feature of Cross-cloud Load Balancing, resulting in optimized performance and higher service availability. By centralizing control, the Hybrid Cloud Service Mesh allows for secure and streamlined cross-service communication. A notable feature of Cross-cloud Container Orchestration is its ability to simplify the migration of applications across diverse cloud environments. For immediate threat detection and regulatory compliance, real-time monitoring is facilitated by Log Management and Analytics. However, Policy-based Resource Management can be complex and inflexible. Extra costs for data transfer between different cloud providers are a drawback of Crosscloud Load Balancing. Additional network hops create latency issues in Hybrid Cloud Service Mesh configurations. If configured incorrectly, Cross-cloud Container Orchestration could expose the system to security risks. Finally, Log Management and Analytics require both ample storage and advanced analytical capabilities. (shrink)

We describe a strategy for integration of data that is based on the idea of semantic enhancement. The strategy promises a number of benefits: it can be applied incrementally; it creates minimal barriers to the incorporation of new data into the semantically enhanced system; it preserves the existing data (including any existing data-semantics) in their original form (thus all provenance information is retained, and no heavy preprocessing is required); and it embraces the full spectrum (...) of data sources, types, models, and modalities (including text, images, audio, and signals). The result of applying this strategy to a given body of data is an evolving Dataspace that allows the application of a variety of integration and analytic processes to diverse data contents. We conceive semantic enhancement (SE) as a lightweight and flexible process that leverages the richness of the structured contents of the Dataspace without adding storage and processing burdens to what, in the intelligence domain, will be an already storage- and processing-heavy starting point. SE works not by changing the data to which it is applied, but rather by adding an extra semantic layer to this data. We sketch how the semantic enhancement approach can be applied consistently and in cumulative fashion to new data and data-models that enter the Dataspace. (shrink)

Metacognition-related studies do often give focus on the regulation or experience components but little on the knowledge component. In particular and especially within the Philippine context, not much focus is given with regards to a clear and coherent academic framework that fortifies the metacognitive strategy knowledge in mathematical problem solving amongst students. Using an evolved grounded theory, the purpose of this study is to look closely into the metacognitive strategy knowledge of preservice teacher education students. Twenty-three students participated (...) and initial data were collected using the prepared problem solving test. Subsequently, interviews were conducted to supplement the initial data. Pandit’s grounded theory methodology and the constant comparison method were used to analyze the data collected. Findings revealed an emerging three-phased categorization of metacognitive strategy knowledge thru problem solving: preparatory, production, and evaluation. The multi-distinct yet related categorization were neither linear nor just cyclic in nature but is experienced and underwent by problem solvers with varying degree of creativity and flexibility depending on the problem at hand, beliefs, attitudes, and learning style. The findings shed some light on the distinct role of metacognitive strategy knowledge and some ensuing factors during authentic problem solving. (shrink)

In light of Taiwan's extensive exposure to the Chinese Communist Party's "cognitive domain infiltration warfare," this paper proposes new response mechanisms and strategies for cybersecurity and national defense. The focus is primarily on assessing the CCP's cognitive infiltration tactics to develop policy recommendations in cybersecurity linguistics. These recommendations are intended to serve as a reference for future national defense and information security policies. Within the constraints of limited resources, this study attempts to provide an integrated analysis method combining qualitative and (...) quantitative tools. This method involves text mining in cybersecurity linguistics, focusing on "textual content" and incorporating discourse deconstruction. The aim is to enhance the success rate in identifying and defining contentious information in cognitive warfare, thereby offering policy suggestions. -/- Keywords: Cognitive Infiltration, Big Data Corpus, Cybersecurity Linguistics, Text Mining Analysis, Narrative Language Deconstruction. (shrink)

Moral circles help define the boundaries of one’s moral consideration. One’s moral circle may provide insight into how one perceives or treats other entities. A data-driven model exploration was conducted to explore predictors and prediction models. Candidate predictors were built upon past research using moral foundations and political orientation. Moreover, we also employed additional moral psychological indicators, i.e., moral reasoning, moral identity, and empathy, based on prior research in moral development and education. We used model exploration methods, i.e., Bayesian (...) model exploration, Bayesian model averaging, and elastic-net regression. The study successfully replicated past research supporting the relationship between moral foundations, political orientation, and the moral circle. Additional moral psychological constructs, such as post-conventional moral reasoning and moral identity, significantly predicted the moral circle width. The identified components of the moral circle were conceptually related to phronesis, i.e., practical wisdom. We discussed the educational implications of the findings, particularly those related to moral education focusing on phronesis cultivation, multiculturalism and global citizenship, and climate justice. (shrink)

How do people reason about their opponent in turn-taking games? Often, people do not make the decisions that game theory would prescribe. We present a logic that can play a key role in understanding how people make their decisions, by delineating all plausible reasoning strategies in a systematic manner. This in turn makes it possible to construct a corresponding set of computational models in a cognitive architecture. These models can be run and fitted to the participants’ data in terms (...) of decisions, response times, and answers to questions. We validate these claims on the basis of an earlier game-theoretic experiment about the turn-taking game “Marble Drop with Surprising Opponent”, in which the opponent often starts with a seemingly irrational move. We explore two ways of segregating the participants into reasonable “player types”. The first way is based on latent class analysis, which divides the players into three classes according to their first decisions in the game: Random players, Learners, and Expected players, who make decisions consistent with forward induction. The second way is based on participants’ answers to a question about their opponent, classified according to levels of theory of mind: zero-order, first-order and second-order. It turns out that increasing levels of decisions and theory of mind both correspond to increasing success as measured by monetary awards and increasing decision times. Next, we use the logical language to express different kinds of strategies that people apply when reasoning about their opponent and making decisions in turn-taking games, as well as the ‘reasoning types’ reflected in their behavior. Then, we translate the logical formulas into computational cognitive models in the PRIMs architecture. Finally, we run two of the resulting models, corresponding to the strategy of only being interested in one’s own payoff and to the myopic strategy, in which one can only look ahead to a limited number of nodes. It turns out that the participant data fit to the own-payoff strategy, not the myopic one. The article closes the circle from experiments via logic and cognitive modelling back to predictions about new experiments. (shrink)

The study outlines the technical challenges encountered during migration, including data compatibility issues, schema conversion, and security compliance, as well as strategies to mitigate these obstacles. Testing and validation techniques are applied throughout the migration, highlighting essential checkpoints to confirm data accuracy and optimal performance in the Snowflake environment. Postmigration performance metrics are evaluated to illustrate improvements in query execution, scalability, and overall system efficiency compared to the legacy system. The results underscore the advantages of Snowflake’s architecture in (...) handling high-volume, concurrent queries without compromising speed or accuracy. (shrink)

Brains, unlike artificial neural nets, use symbols to summarise and reason about perceptual input. But unlike symbolic AI, they “ground” the symbols in the data: the symbols have meaning in terms of data, not just meaning imposed by the outside user. If neural nets could be made to grow their own symbols in the way that brains do, there would be a good prospect of combining neural networks and symbolic AI, in such a way as to combine the (...) good features of each. The article argues the cluster analysis provides algorithms to perform the task, and that any solution to the task must be a form of cluster analysis. (shrink)

The goal of referent tracking is to create an ever-growing pool of data relating to the entities existing in concrete spatiotemporal reality. In the context of Electronic Healthcare Records (EHRs) the relevant concrete entities are not only particular patients but also their parts, diseases, therapies, lesions, and so forth, insofar as these are salient to diagnosis and treatment. Within a referent tracking system, all such entities are referred to directly and explicitly, something which cannot be achieved when familiar concept-based (...) systems are used in what is called “clinical coding”. In this paper we describe the components of a referent tracking system in an informal way and we outline the procedures that would have to be followed by healthcare personnel in using such a system. We argue that the referent tracking paradigm can be introduced with only minor – though nevertheless ontologically important – technical changes to existing EHR infrastructures, but that it will require a radically different mindset on the part of those involved in clinical coding and terminology development from that which has prevailed hitherto. (shrink)

Teachers' pedagogical strategy in teaching reading comprehension cannot be neglected because when learners fail to comprehend text and give meaning to it, they experience difficulties understanding other subjects taught. This study, therefore, examined reading comprehension strategies adopted by teachers to enhance reading comprehension among primary school learners. This study adopted a qualitative research method with an interpret visit paradigm. Ten (10) teachers were purposively selected for the study one each from ten (10) primary schools. Data was collected the (...) selected participants using semi-structured interview. The researchers ensured the trustworthiness of the interview through disclosure and corroboration. The data collected were transcribed for the purpose of analysis using the atlasti software and the thematic data analysis technique. Findings indicate that some teachers did not understand the various strategies to optimise reading comprehension. Teachers also lacked knowledge of the different learners learning preferences to plan their reading comprehension lessons. Furthermore, the lack of appropriate reading material and differentiated reading exercises for slow learners were highlighted among the challenges that hampered reading comprehension. The study recommends capacity-building programmes to provide strategies for differentiated teaching, to learn to accommodate slow learners and to provide appropriate resources by the education department. (shrink)

Manufacturing and industry practices are undergoing an unprecedented revolution as a consequence of the convergence of emerging technologies such as artificial intelligence, robotics, cloud computing, virtual and augmented reality, among others. This fourth industrial revolution is similarly changing the practices and capabilities of operators in their industrial environments. This paper introduces and explores the notion of the Operator 4.0 as well as how this novel way of conceptualizing the human operator necessarily implicates human values in the technologies that constitute it. (...) The design approach known as value sensitive design (VSD) is used to explore how these Operator 4.0 technologies can be designed for human values. Expert elicitation surveys were used to determine the values of industry stakeholders and examples of how the VSD methodology can be adopted by engineers in order to design for these values is illustrated. The results provide preliminary adoption strategies that industrial teams can take to Operator 4.0 technology for human values. (shrink)

Despite widespread recognition of an emergent politics of data in our midst, we strikingly lack a political theory of data. We readily acknowledge the presence of data across our political lives, but we often do not know how to conceptualize the politics of all those data points—the forms of power they constitute and the kinds of political subjects they implicate. Recent work in numerous academic disciplines is evidence of the first steps toward a political theory of (...) data. This article maps some limits of this emergent literature with an eye to enriching its theoretical range. The literature on data politics, both within political theory and elsewhere, has thus far focused almost exclusively on the algorithm. This article locates a further dimension of data politics in the work of formatting technology or, more simply, formats. Formats are simultaneously conceptual and technical in the ways they define what can even count as data, and by extension who can count as data and how they can count. A focus on formats is of theoretical value because it provides a bridge between work on the conceptual contours of categories and the technology-centric literature on algorithms that tends to ignore the more conceptual dimensions of data technology. The political insight enabled by format theory is shown in the context of an extended interrogation of the politics of racialized redlining. (shrink)

The main purpose of the study is to understand the mathematical problem-solving strategies among student teachers. This study used both quantitative and qualitative type of research. Aside from the semi-structured interviews, data were gathered through participant's actual mathematical problem-solving outputs and the videotaped interviews. Findings revealed that the problem-solving strategies among student teachers in the Problem-Solving subject are cognitive, metacognitive and other strategies. The cognitive strategies used by the student teachers are rehearsal, elaboration, and organization. The metacognitive strategies are (...) critical thinking and self-regulation. Other strategies are overlapping the cognitive and metacognitive strategies. These are prediction/orientation, planning, monitoring, and evaluating. The findings also suggest a significant influence of the strategies to the academic performance of the student teachers. (shrink)

We describe a strategy that is being used for the horizontal integration of warfighter intelligence data within the framework of the US Army’s Distributed Common Ground System Standard Cloud (DSC) initiative. The strategy rests on the development of a set of ontologies that are being incrementally applied to bring about what we call the ‘semantic enhancement’ of data models used within each intelligence discipline. We show how the strategy can help to overcome familiar tendencies to (...) stovepiping of intelligence data, and describe how it can be applied in an agile fashion to new data resources in ways that address immediate needs of intelligence analysts. (shrink)

This study aimed to explore the teachers' experiences in addressing the learning gaps during the resumption of in-person classes post-pandemic. Specifically, it sought to determine the learning recovery strategies implemented and the challenges encountered by the teachers. Six (6) teachers from DepEd Zamboanga City Division were involved in this study employing a qualitative-phenomenological research design. The participants were purposively selected based on the criteria defined in this paper. The data were collected through in-depth interviews with semi-structured interview questions. The (...) findings revealed that the teachers employed a multifaceted approach to bridge the learning gaps. These include conducting remedial reading and pull-out sessions, integrating basic reading activities in all subject areas, and using differentiated instructions and materials. However, teachers also encountered challenges related to the limited availability of resources, the need for professional development to address pedagogical changes, the lack of parental support, and absenteeism among learners. The research finding suggests intervention at the individual and system levels to mitigate the learning gaps. Policy recommendations include upskilling and plans of teachers, particularly in teaching beginning reading, increasing funding allocation for basic education resources, reviewing implementation of the learning recovery plans, and improving collaboration with parents and community stakeholders to support learners’ education. (shrink)

As the world grapples with the urgent need for sustainable development, the transition towards green energy stands as a critical imperative. Financing this transition poses significant challenges, requiring innovative approaches that align financial objectives with environmental sustainability goals. This review presents a conceptual framework for leveraging data-driven techniques in sustainable finance to facilitate the transition towards green energy. The proposed framework integrates principles of sustainable finance with advanced data analytics to enhance decision-making processes across the financial ecosystem. At (...) its core, the framework emphasizes the importance of harnessing vast datasets related to energy production, consumption, environmental impact, and financial performance. By leveraging machine learning algorithms and predictive modeling techniques, financial stakeholders can gain deeper insights into the risks and opportunities associated with green energy investments. Key components of the framework include data collection and aggregation, risk assessment, impact measurement, and investment optimization. Data sources range from traditional financial indicators to environmental metrics, social impact assessments, and geopolitical factors. Through comprehensive data analysis, financial institutions can assess the long-term viability and sustainability of green energy projects, while also evaluating potential social and environmental impacts. Risk assessment methodologies within the framework consider both financial risks, such as market volatility and regulatory uncertainty, and non-financial risks, such as climate change impacts and community resilience. By integrating these factors into risk models, investors can make more informed decisions that mitigate potential losses and maximize returns. Furthermore, impact measurement tools enable stakeholders to quantify the environmental and social benefits of green energy investments. By tracking metrics such as carbon emissions reduction, energy efficiency improvements, and job creation, investors can assess the contribution of their portfolios towards broader sustainability objectives. Finally, the framework incorporates investment optimization strategies that align financial goals with environmental objectives. Through portfolio diversification, asset allocation, and innovative financial instruments such as green bonds and impact investing funds, financial institutions can allocate capital more efficiently towards green energy projects. The conceptual framework presented herein offers a systematic approach to integrating data-driven methodologies into sustainable finance practices. By leveraging advanced analytics and comprehensive datasets, financial stakeholders can drive the transition towards green energy while simultaneously achieving financial returns and positive environmental outcomes. (shrink)

Criticism of big data has focused on showing that more is not necessarily better, in the sense that data may lose their value when taken out of context and aggregated together. The next step is to incorporate an awareness of pitfalls for aggregation into the design of data infrastructure and institutions. A common strategy minimizes aggregation errors by increasing the precision of our conventions for identifying and classifying data. As a counterpoint, we argue that there (...) are pragmatic trade-offs between precision and ambiguity that are key to designing effective solutions for generating big data about biodiversity. We focus on the importance of theory-dependence as a source of ambiguity in taxonomic nomenclature and hence a persistent challenge for implementing a single, long-term solution to storing and accessing meaningful sets of biological specimens. We argue that ambiguity does have a positive role to play in scientific progress as a tool for efficiently symbolizing multiple aspects of taxa and mediating between conflicting hypotheses about their nature. Pursuing a deeper understanding of the trade-offs and synthesis of precision and ambiguity as virtues of scientific language and communication systems then offers a productive next step for realizing sound, big biodiversity data services. (shrink)

Abstract – This study aimed primarily to determine the effectiveness of crime prevention strategies implemented by the Salug Valley Philippine National Police (PNP) in terms of Police Integrated Patrol System, Barangay Peacekeeping Operation, Anti-Criminality Operation, Integrated Area Community Public Safety services, Bantay Turista and School Safety Project as evaluated by 120 inhabitants and 138 PNP officers from four Municipalities of Salug Valley Zamboanga del Sur. Stratified random sampling was utilized in determining the respondents. Index crime rate were correlated with the (...) crime prevention strategies of the PNP in town of Salug Valley. A descriptive method of research was applied in this study utilizing self-made questionnaire. The data collected were analyzed using the main statistical tools like frequency count, percentage, mean computation, Kruskal Wallis Analysis of Variance and simple correlation. Findings of the study revealed that the crime prevention strategies in four (4) municipalities were “much effective” to include Integrated Patrol System, Barangay Peace Keeping Operations, Anti-Criminality Operations, Integrated Area Community Public Safety Services, Bantay Turista and School Safety Project in connection to the responses of 158 participants. There is a significant relationship between crime prevention strategies employed and index crime rate. (shrink)

In this paper we will examine how experts from certain epistemic networks behave in the circumstances of a crisis. Our main goal is to show rhetorical strategies experts use to strengthen their own epistemic authority. We will do that by analysing experts’ strategies used in two pandemics: the one caused by A h1n1 virus in 2009 and the current pandemic caused by SARS-CoV-2. There are four different, but interrelated, rhetorical strategies, that epistemic experts use to consolidate their epistemic authority. Two (...) are internally oriented and consist of 1) experts providing additional reasons for why the measures they propose in the time of crises are rational and (2) experts emphasising their own responsibilities in the crises. Experts also use two externally oriented rhetorical strategies by which they (3) challenge the expertise of other experts and (4) raise doubts about the motives of other epistemic experts. (shrink)

The study aimed to identify E- Learning strategies and their relation to the efficiency of research performance in foreign and Palestinian universities (University of Ottawa, Munster, Suez Canal, Al-Azhar, Islamic, Al-Aqsa). The analytical descriptive approach was used for this purpose, and relying on the questionnaire as a main tool for data collection. The study society is from the senior management, where the number of senior management in the universities in question is 206. The random stratified sample was selected and (...) (SPSS) was used for statistical data analysis. The study found a significant relationship between E- Learning strategies and the efficiency of research performance in universities. It also reached the participation of senior management in the research that develops the university performance in the Palestinian universities. The senior management indicated that they do not care to follow the policies of implementing the development of scientific research. While the senior management in foreign universities indicated that they are interested in following up the policies of implementing the development of scientific research. The study also showed that senior management in Palestinian universities does not care about providing the appropriate budget for E- Learning. The study recommended that the senior management of Palestinian universities should provide an E- Learning budget and encourage employees to continue using E- Learning strategies. The administration in the Palestinian universities should adopt and support outstanding research, and the need to encourage interest in the implementation of policies for the development of scientific research. (shrink)

In spite of all the industrious efforts Peirce scholars have made so far, Peirce’s biography still retains a number of gaps, among which the problem of identity of Peirce’s second wife, Juliette Froissy, stands out most significantly. It is all the more important that, as some scholars suggest, the discovery of any reliable facts about Juliette could provide an explanation to some of the decisions Peirce had made, which irrevocably changed the course of his life, as well as his semiotic (...) theory. By courtesy of Professor Dr. Nathan Houser and the Peirce Edition Project, the writer of the present paper was granted access to the archive materials containing the Max H. Fisch — Maurice Auger correspondence and Victor Lenzen’s notes on Juliette. The paper aims at arranging the dispersed data obtained from these and other sources into a set of several distinct versions, which curiously refer to each other and collectively impose a certain order on some major abductions concerning Juliette’s identity. (shrink)

Research in second language learning has identified the absence of metacognition among learners as one of the major problems contributing to students’ inability to comprehend listening texts. Moreover, the shift to remote teaching due to COVID-19 has made it more crucial for teachers and learners to adapt to new modes of teaching and learning. This accentuates the need for effective listening strategy instruction. This study conducted at a university in Oman, is unique in two ways: first, it seeks out (...) teachers’ perceptions of metacognitive strategy instruction in remote teaching; and second, the intervention in the form of explicit metacognitive strategy instruction is offered online. This paper presents the findings of the study, which focused on the following: teachers’ perception of students’ listening difficulties; teachers’ perceptions of metacognitive strategies and their explicit instruction; the role of metacognitive strategy awareness and instruction in improving student participation and skills in listening; challenges encountered in teaching listening during remote teaching; and overcoming challenges of teaching metacognitive strategies in remote teaching. This mixed-method study collected data through questionnaires and interviews with 10 faculty members and 75 students. The findings show that teachers face several challenges, such as time limitations, shortened semesters, unfamiliar coursebook contexts, and assessment practices. For strategy instruction, teachers utilized collaborative lesson planning and resources and virtual flipped classrooms, among others. We conclude that metacognitive strategy instruction can provide better scaffolding during listening instruction and recommends further exploration of students’ use of metacognitive strategies in other academic contexts. (shrink)

This study aims to describe the cultural strategy of the Buginese people of Pagatan (one of ethnic group in Indonesia) in preserving their local wisdom living in a multicultural society. This research was conducted using qualitative descriptive method through three methods of data collection i.e. in-depth interview, observation and literature involving community leaders and ordinary people as informants. The historical-interpretative method was used to analyze the Data. The findings from this study indicate that the people of Buginese-Pagatan (...) use two strategies to preserve their Buginese identity in a pluralistic society i.e. the strategy of interaction patterns and the use of ethnic symbols. In the strategy of interaction patterns, they implement adaptive and inclusive interaction patterns. This strategy is represented by the mastery and the use of regional languages in addition to the Buginese language, cross-ethnic marriages, and participation in social activities. While in the strategy of using ethnic symbols, they form a distinct identity from the one existing in Sulawesi. This strategy is represented by the use of ethnic symbols such as wearing Bodo clothes, bone cap in the rituals of marriage and moving in new houses, preserving the ancient model of Buginese house for settlement, and forming a new cultural identity called Maccera Tasi. This research has identified local values preserved and held by its people as cultural strategies in building a harmonious society. We believe that the cultural strategies are useful not only to form a united, dignified and civilized local community of Indonesia, but also to serve as a model for other cultures to preserve their local wisdom. (shrink)

This descriptive correlational study anchored on Lazarus and Folkman’s Coping Theory identified the pedagogical problems met and the coping strategies adapted by elementary school teachers during the pandemic in one school district in the Division of Aklan during the height of the pandemic in 2021. This also tried to find out the extent of pedagogical problems experienced by the teacher respondents related to curriculum, fellow teachers, learners, school, and parents, and the coping strategies applied to manage the problems they encountered. (...) Forty-six grade school teachers purposively selected in the identified elementary schools in the district participated in the study. A researcher-made survey questionnaire validated by experts was used in the gathering of data. Findings revealed that teacher respondents were between 31-40 years old, mostly female and single, with average monthly income from 10,000 to 20, 000, travel less than 6 km from their homes to the work station, and are proficient in terms of ICT competence. The extent of pedagogical problems experienced by the respondents related to curriculum and fellow teachers was slightly a challenge; and to learners, school-related aspects, and parents as not at all considered as challenges. To cope with these challenges, the respondents’ top three activities were attending webinars for professional growth, enjoying quality time with their families, and going to and praying in the church. These imply that grade school teachers are more particular about improving themselves professionally and strengthening their faith in God than doing other things that affect their physical and mental health. (shrink)

Scholarship on the politics of new media widely assumes that communication functions as a sufficient conceptual paradigm for critically assessing new media politics. This article argues that communication-centric analyses fail to engage the politics of information itself, limiting information only to its consequences for communication, and neglecting information as it reaches into our selves, lives, and actions beyond the confines of communication. Furthering recent new media historiography on the “information theory” of Shannon and Wiener, the article reveals both the (...) primacy of communication in midcentury information theory, and also a striking resonance between these postwar communication theories and Habermas’s more recent communicative theory of democracy. To achieve a critical perspective beyond communication, the article proposes a media genealogy of the politics of subjects as a methodology for developing an analysis of how information formats us as subjects of data. (shrink)