Higher-order Concepts Research Articles

현대 사회에서 헌법상 근로자 개념의 재구성

This study explores the necessity and direction for the reconstruction of the constitutional concept of workers in light of changes in the contemporary labour environment. The emergence of diverse forms of labour that transcend the traditional “blue-collar” worker calls for a reassessment of the concept of workers as defined by labour law. However, the Korean Constitutional Court bases its definition of constitutional workers on labour law, while the legislature has been reluctant to amend the provisions defining workers for decades. In this context, courts attempt to include various forms of labour by expanding the interpretation of existing legal definitions. However, such judicial interpretations seem insufficient to keep pace with changes in the labour environment, complicating the law’s consistency, thereby increasing the complexity and placing an undue political burden on the judiciary. Based on this analysis, this study emphasizes that the primary responsibility for encompassing new labour realities through legal amendments lies with the legislature, advocating the necessity to reset the constitutional concept of labour as a basis for legislation and a standard for constitutional review in the post-remedial process. To this end, this research reinterprets Hugo Sinzheimer’s concept of labour constitution in a contemporary context and derives indicators for a new concept of workers that surpass dependency theory, aiming to provide a legal foundation that can flexibly and resiliently respond to the complexities of the labour environment. This study proposes setting the concept of workers as a higher-order concept and, based on this, suggests ways to diversify the concept of labourers and labour laws at the legal level. Traditional labour relations will be covered by the regulation of existing labour laws, while emerging grey areas will be encompassed through individual labour laws. Such an approach to diversified individual labour laws ensures that the constitutionally granted labour rights and the diversity and specificity of labour relations are harmoniously reflected, ultimately guaranteeing an equal level of protection for all workers.

Characteristics differentiating problem representation synthesis between novices and experts.

Formulating a thoughtful problem representation (PR) is fundamental to sound clinical reasoning and an essential component of medical education. Aside from basic structural recommendations, little consensus exists on what characterizes high-quality PRs. To elucidate characteristics that distinguish PRs created by experts and novices. Early internal medicine residents (novices) and inpatient teaching faculty (experts) from two academic medical centers were given two written clinical vignettes and were instructed to write a PR and three-item differential diagnosis for each. Deductive content analysis described the characteristics comprising PRs. An initial codebook of characteristics was refined iteratively. The primary outcome was differences in characteristic frequencies between groups. The secondary outcome was characteristics correlating with diagnostic accuracy. Mixed-effects regression with random effects modeling compared case-level outcomes by group. Overall, 167 PRs were analyzed from 30 novices and 54 experts. Experts included 0.8 fewer comorbidities (p < .01) and 0.6 more examination findings (p = .01) than novices on average. Experts were less likely to include irrelevant comorbidities (odds ratio [OR] = 0.4, 95% confidence interval [CI] = 0.2-0.8) or a diagnosis (OR = 0.3, 95%CI = 0.1-0.8) compared with novices. Experts encapsulated clinical data into higher-order terms (e.g., sepsis) than novices (p < .01) while including similar numbers of semantic qualifiers (SQs). Regardless of expertise level, PRs following a three-part structure (e.g., demographics, temporal course, and clinical syndrome) and including temporal SQs were associated with diagnostic accuracy (p < .01). Compared with novices, expert PRs include less irrelevant data and synthesize information into higher-order concepts. Future studies should determine whether targeted educational interventions for PRs improve diagnostic accuracy.

Understanding operon architecture using LEGO bricks.

Many undergraduates struggle to interpret abstract concepts in molecular biology. Modeling can facilitate learning by making these abstract concepts tangible. Here, we present an exercise based on the lac operon designed for undergraduate students using LEGO bricks. The lac operon is a classic example of transcriptional regulation taught in a variety of undergraduate biology courses and is fundamental to understanding the regulation of gene expression. This easy-to-implement active learning exercise demonstrates how the various components of the lac operon are oriented under a variety of nutritional conditions to control gene expression. In addition, higher-order concepts, such as the effect of mutation on lac operon expression, can be readily modeled. Overall, students not only found this exercise to be enjoyable but also helpful as a tool to engage with this course material.

Identifying policy alternatives to enable the virtual establishment of a veterinarian-client-patient relationship.

This research seeks to identify an existing policy stream around the establishment of a veterinarian-client-patient relationship (VCPR) through telemedicine to provide evidence of, and advance policy alternatives for, states and countries looking to allow this practice responsibly. This is seen as an important step for access to veterinary care, particularly for cats. The multiple streams policy framework requires identification of a centering event, problem stream, policy stream and politics stream in order to have the necessary conditions for policy change to occur. This research identifies that policy stream through thematic content analysis. State-level policies from across the entire USA that address the virtual establishment of a physician-patient relationship were analyzed to provide themes that could be applied to similar policies in veterinary medicine. Ten key themes were identified and further organized into four high-order concepts through the thematic content analysis. Detailed accounting of the specific policy alternatives is provided in the supplementary materials. The themes and concepts presented provide evidence of a robust policy stream. This content analysis, and the supporting supplementary details, provide many options to guide states in the development of sound policies for the virtual establishment of a VCPR by drawing from the more matured field of human medicine.

Learning Relationship-Enhanced Semantic Graph for Fine-Grained Image-Text Matching.

Image-text matching of natural scenes has been a popular research topic in both computer vision and natural language processing communities. Recently, fine-grained image-text matching has shown its significant advance in inferring the high-level semantic correspondence by aggregating pairwise region-word similarity, but it remains challenging mainly due to insufficient representation of high-order semantic concepts and their explicit connections in one modality as its matched in another modality. To tackle this issue, we propose a relationship-enhanced semantic graph (ReSG) model, which can improve the image-text representations by learning their locally discriminative semantic concepts and then organizing their relationships in a contextual order. To be specific, two tailored graph encoders, visual relationship-enhanced graph (VReG) and textual relationship-enhanced graph (TReG), are respectively exploited to encode the high-level semantic concepts of corresponding instances and their semantic relationships. Meanwhile, the representations of each graph node are optimized by aggregating semantically contextual information to enhance the node-level semantic correspondence. Further, the hard-negative triplet ranking loss, center hinge loss, and positive-negative margin loss are jointly leveraged to learn the fine-grained correspondence between the ReSG representations of image and text, whereby the discriminative cross-modal embeddings can be explicitly obtained to benefit various image-text matching tasks in a more interpretable way. Extensive experiments verify the advantages of the proposed fine-grained graph matching approach, by achieving the state-of-the-art image-text matching results on public benchmark datasets.

Business model innovation through the adoption of service logic: evolving to servification

PurposeIn servitization research, there has been a call to move further toward the development of business models based on a service approach. This article aims to answer this call by adopting service logic (SL) and developing strategies and organizational resources and processes to create a service-centric business model called servification, defined as the process of identifying and developing strategies and organizational resources and processes to create a business model based on SL.Design/methodology/approachThis article is conceptual and extends servitization in the direction of service-centric business model innovation by drawing on and extending SL.FindingsThe article defines service as a higher-order concept according to SL and develops the concept of a helping strategy as the foundation for a service-based business model. Further, it develops a typology of organizational resources and processes that must be developed for the emergence of such a business model.Research limitations/implicationsSince this article is the first to conceptually develop servification, more both theoretical and empirical research is naturally required. The development of servification takes servitization in the direction of service-based business model innovation and also contributes to the research on SL.Practical implicationsServification enables the development of service-centric strategies and organizational resources and processes and service-based business models.Originality/valueThis article is the first to adopt SL in studies of business model innovation.

The role of anthropomorphic, [formula omitted]enocentric, intentional, and social (A[formula omitted]IS) robotics in human-robot interaction

This research explores the socio-cognitive mechanisms of human intelligence through the lens of anthropomorphic, xˆenocentric, intentional, and social (AXˆIS) robotics. After delving into three pivotal AXˆIS concepts – robotic anthropomorphism, intentionality, and sociality – the study examines their impact on robot likeability and successful human-robot interaction (HRI) implementation. The research introduces the concept of robotic xˆenocentrism (represented by perceived inferiority and social aggrandizement) as a new global dimension in social robotics literature, positioning it as a higher-order concept that moderates the impact of pivotal independent variables on robot likeability. Analyzing a sample of 308 respondents in global cross-cultural teams, the study confirms that pivotal AXÍS robotics concepts foster positive robot likeability and successful HRI implementation for both industrial and social robots. Perceived inferiority negatively moderated the relationship between anthropomorphism and robot likeability, but it was a positive moderator between intentionality and robot likeability. However, social aggrandizement did not act as a significant boundary condition. Sociality remains unaffected by the moderating influence of xˆenocentrism. The study concludes by outlining future research directions for AXˆIS robotics.

Teaching Multiplicative Thinking With Virtual Representations to Children With Mathematics Difficulty

Whole number computations are a critical skill that serves as a foundation upon which higher-order concepts in mathematics are taught to children. To facilitate their instruction, educators often use multiple representations to support a child’s cognition. Representations with physical manipulatives are widely studied through a graduated instructional sequence featuring concrete, representational, and abstract stages of learning. In contrast, research on representational sequences featuring virtual manipulatives is less robust. Thus, this study evaluated an instructional strategy with virtual manipulatives, static representational drawings, and abstract algorithms to teach multiplication to three elementary students with mathematics difficulty. A functional relation was established via a single-subject multiple probe design between the treatment and students’ accuracy performance. Baseline-corrected Tau estimates confirmed a medium effect size for all three students, while student performance on measures assessing the number of errors committed and the duration of sessions also returned favorable findings.

Is the concept of personality capacious enough to incorporate virtues?

We will consider four answers to the question about whether the concept of personality is capacious enough to incorporate virtues. The simplest is that the concept of personality encompasses all individual variations in persons. It follows from this answer that virtues would, as individual differences, be incorporated into personality. Unfortunately, definitions of personality do not always invoke such capaciousness, and, in practice, most scholars limit their work to the Big Five or HEXACO models, which do not incorporate virtues. The second answer is that the concept of personality incorporates all trait or dimension level variations across persons, with some exceptions, such as intelligence, attachment style, and psychopathy. Following this definition, virtues, as traits, would be incorporated into such a broad definition of personality. Unfortunately, the boundaries for inclusion and exclusion into personality are fuzzy in this case, and there is no extant definition of personality that solves this problem. The third answer is that personality traits and virtue traits are similar, but distinct concepts. This article presents conceptual and empirical arguments for this similarity in seeing traits as a higher order concept that includes the species of personality and the species of virtue. The fourth answer is that personality and virtue are unrelated. This answer is dismissed because there are many studies that indicate that they are correlated, and few advocate such a clear differentiation. The conclusion is that, pending conceptual and empirical results indicating otherwise, the genus-species relationship seems most fitting where traits are a genus, and personality and virtue are each a species within that genus.

Using 3D molecular structure simulation to develop chemistry competence for Vietnamese students

The spatial structure of organic compounds (3D molecular structure) acts as an important tool in teaching organic chemistry. This study designed 16 3D molecular structures of hydrocarbons and chemical reaction simulations, using these simulations to design teaching plans for alkenes; guide teachers on how to use the teaching plans; and develop tests to assess students’ chemistry competency. The research aimed to evaluate the impact of using 3D molecular structure simulations on students’ development of chemistry competency. The methodology was conducted on 630 Vietnamese students divided into two groups: an experimental group and a control group. The results of this study have demonstrated the benefits of 3D molecular structure simulation, including enhancement of students’ chemistry competency, promotion of transfer and application of spatial chemistry content to higher-order concepts, and expansion of the planning of the nature and mechanism of chemical reactions. As a result, chemistry teachers can use 3D molecular structure simulation to teach topics such as atomic radius, bond length, and bond angle. This research makes an important contribution to the application of technology in teaching and developing chemistry competence for Vietnamese high school students.

은닉 마르코프 모델을 이용한 적응형 학습경로 생성에 관한 연구

Due to the global impact of COVID-19, the use of non-face-to-face learning is increasing. For non-face-to-face learning, it is important to create a learning path based on efficiency. This study introduces the hidden Markov model (HMM) as a method of creating a learning path known as a network in which knowledge concepts are arranged in order, that is, the path of experience that students may encounter in class. and it aims to improve the accuracy of path prediction by using a variable selection technique that includes least absolute shrinkage and selection operator (LASSO), and random forest (RF) before performing HMM. In addition, this study aims to show that the learning path based on higher-order concepts made of precedence relationships from HMM is more accurate than other candidate paths. As a result of using data shared by AI-hub (https://aihub.or.kr/), the performance of HMM when selecting relational pairs using LASSO, and RF was improved significantly, and the case of using HMM when evaluating the learning path consisting of higher concepts was excellent in terms of model goodness of fit compared to other models.

Understanding higher education students’ sense of belonging: a qualitative meta-ethnographic analysis

ABSTRACT The current literature on ‘sense of belonging’ spans a number of disciplines, with no apparent consensus on definition between these, complicated by the fact that sense of belonging is temporal and context-sensitive (such as during COVID-19). In particular, a closer look at how students define sense of belonging is needed from an up-to-date perspective to help them feel more connected to the faculty/campus and improve their wellbeing and mental health in the ‘new normal’ and ‘next normal’ post-pandemic eras. Therefore, this study explores higher education students’ sense of belonging, a concept that has not been adequately conceptualised, from their perspectives. As these perspectives are subjective, an interpretive approach is required to generate rich meanings. This study has adopted a meta-ethnographic approach to synthesise qualitative studies, which allows for comparison and synthesis of studies into a new interpretation through translations. Interpretive qualitative synthesis resulted in one higher-order concept, four main concepts, and nineteen sub-concepts that conceptualise higher education students’ understanding of sense of belonging to their universities.

The invisible work of transfer centre nurses: A qualitative study of strategies to overcome communication challenges.

To explore the role of transfer centre nurses and how they facilitate communication between referring and accepting providers during calls about interhospital transfers, including their strategies to overcome communication challenges. A qualitative interview study. We conducted semi-structured interviews with 17 transfer centre nurses at one tertiary medical centre from March to August 2019, asking participants to describe their work. We performed content analysis, applying codes based on the Relational Coordination Framework and generating emergent codes, then organized codes in higher-order concepts. We followed the COREQ checklist. Transfer centre nurses employed multiple strategies to mitigate communication challenges. When referring providers had misconceptions about the transfer centre nurse's role and theaccepting hospital's processes, the nurses informed referring providers why sharing information with them was necessary. If providers expressed frustrations or lacked understanding about their counterpart's caseload, the nurses managed providers' emotions by letting them "vent," explaining the other provider's situational context and describing the hospital's capabilities. Some nurses also mediated conflict and sought to break the tension if providers debated about the best course of action. When providers struggled to share complete and accurate information, the nurses hunted down details and 'filled in the blanks'. Transfer centre nurses perform invisible work throughout the lifespan of interhospital transfers. Nurses' expert knowledge of the transfer process and hospitals' capabilities can enhance provider communication. Meanwhile, providers' lack of knowledge of the nurse's role can impede respectful and efficient transfer conversations. Interventions to support and optimize the transfer centre nurses' critical work are needed. This study describes how transfer centre nurses facilitate communication and overcome challenges during calls about interhospital transfers. An intervention that supports this critical work has the potential to benefit nurses, providers and patients by ensuring accurate and complete information exchange in an effective, efficient manner that respects all parties. This study was designed to capture the perspectives and experiences of transfer centre nurses themselves through interviews. Therefore, it was not conducted using input or suggestions from the public or the patient population served by the organization.

Grounding the Vector Space of an Octopus: Word Meaning from Raw Text

Most, if not all, philosophers agree that computers cannot learn what words refers to from raw text alone. While many attacked Searle’s Chinese Room thought experiment, no one seemed to question this most basic assumption. For how can computers learn something that is not in the data? Emily Bender and Alexander Koller (2020) recently presented a related thought experiment—the so-called Octopus thought experiment, which replaces the rule-based interlocutor of Searle’s thought experiment with a neural language model. The Octopus thought experiment was awarded a best paper prize and was widely debated in the AI community. Again, however, even its fiercest opponents accepted the premise that what a word refers to cannot be induced in the absence of direct supervision. I will argue that what a word refers to is probably learnable from raw text alone. Here’s why: higher-order concept co-occurrence statistics are stable across languages and across modalities, because language use (universally) reflects the world we live in (which is relatively stable). Such statistics are sufficient to establish what words refer to. My conjecture is supported by a literature survey, a thought experiment, and an actual experiment.

Higher-order concepts for the potential infinite

The lambda calculus can be seen as a language that connects mathematics with computer science. However, the models used in both disciplines have different basic properties. In computer science these models are mainly based on domain theory with its partial functions and its fixed point property. In mathematics the models use total functions and relations and allow the integration of logic. Typically, mathematical models are based on set theory with its actual infinite sets, which are incongruous with computer science.We will present a dynamic model that is based consequently on the potential infinite. It uses total functions, whereby functions and the function spaces are seen as interdependent, increasing finite entities. It moreover allows the integration of higher-order logic (to be demonstrated in a separate paper), provided the universal quantifier is interpreted in a specific, dynamic way. Such a model can serve as a common denotational semantics of the lambda calculus for both, mathematics and computer science.

The Role of Perceived Injustice and Need for Esteem on Incel Membership Online

ABSTRACT Incels – a term that stands for “involuntary celibates”—is a subculture of men connected by their inability to obtain romantic and sexual relationships. As a group known for real-world violent attacks, understanding the drivers of online membership offers valuable insight into these vulnerable men. The current study used inductive qualitative analysis of over 8,000 posts made by 703 unique posters in two online incel communities to explore common themes within the process of incel membership online. Qualitative analyses uncovered two higher-order concepts: perceptions of injustice and searching for esteem. Within these concepts several underlying themes emerged: victimization, perceived barriers to manhood, psychological responses, and black pill as liberation. The results posit that one avenue to incel membership comes from heightened perceptions of injustice among these users. In addition, the incel forum offers a strategy to increase self-esteem through online membership, which may be a vital draw for disenfranchised young people. Unfortunately, it seems that online incel membership, while a source of self-esteem, shapes incel perceptions, leading members to re-interpret instances in their lives through the lens of extremist ideology.

The Neuroimaging Data Model Linear Regression Tool (nidm_linreg): PyNIDM Project.

The Neuroimaging Data Model (NIDM) is a series of specifications for describing all aspects of the neuroimaging data lifecycle from raw data to analyses and provenance. NIDM uses community-driven terminologies along with unambiguous data dictionaries within a Resource Description Framework (RDF) document to describe data and metadata for integration and query. Data from different studies, using locally defined variable names, can be retrieved by linking them to higher-order concepts from established ontologies and terminologies. Through these capabilities, NIDM documents are expected to improve reproducibility and facilitate data discovery and reuse. PyNIDM is a Python toolbox supporting the creation, manipulation, and querying of NIDM documents. Using the query tools available in PyNIDM, users are able interrogate datasets to find studies that have collected variables measuring similar phenotypic properties. This, in turn, facilitates the transformation and combination of data across multiple studies. The focus of this manuscript is the linear regression tool which is a part of the PyNIDM toolbox and works directly on NIDM documents. It provides a high-level statistical analysis that aids researchers in gaining more insight into the data that they are considering combining across studies. This saves researchers valuable time and effort while showing potential relationships between variables. The linear regression tool operates through a command-line interface integrated with the other tools (pynidm linear-regression) and provides the user with the opportunity to specify variables of interest using the rich query techniques available for NIDM documents and then conduct a linear regression with optional contrast and regularization.

Bandpass leapfrog hybrid implicit–explicit procedure with promoted absorption for obtaining fine geometry in a single direction

For an accurate and efficient calculation of fine geometry along a single direction in open regions, a bandpass one-step hybrid implicit–explicit (HIE) procedure with promoted absorption is implemented in this study. More precisely, the proposed scheme is modified by integrating complex envelope (CE) method, higher order concept, perfectly matched layer (PML) formulation, and one-step leapfrog HIE procedure. Furthermore, by introducing property variables, efficiency can be improved significantly. In addition, the proposed scheme not only overcomes the Courant–Friedrich–Levy stability condition but also solves the efficiency decrement problem of implicit algorithms. The effectiveness of the proposed algorithm is validated and demonstrated both numerically and experimentally. According to the results, we can conclude that the proposed scheme is advantageous in terms of enhanced accuracy, promoted absorption, improved efficiency for fine geometry along a single direction in bandpass open region problems.

The Neuroimaging Data Model Linear Regression Tool (nidm_linreg): PyNIDM Project

The Neuroimaging Data Model (NIDM) is a series of specifications for describing all aspects of the neuroimaging data lifecycle from raw data to analyses and provenance. NIDM uses community-driven terminologies along with unambiguous data dictionaries within a Resource Description Framework (RDF) document to describe data and metadata for integration and query. Data from different studies, using locally defined variable names, can be retrieved by linking them to higher-order concepts from established ontologies and terminologies. Through these capabilities, NIDM documents are expected to improve reproducibility and facilitate data discovery and reuse. PyNIDM is a Python toolbox supporting the creation, manipulation, and querying of NIDM documents. Using the query tools available in PyNIDM, users are able interrogate datasets to find studies that have collected variables measuring similar phenotypic properties. This, in turn, facilitates the transformation and combination of data across multiple studies. The focus of this manuscript is the linear regression tool which is a part of the PyNIDM toolbox and works directly on NIDM documents. It provides a high-level statistical analysis that aids researchers in gaining more insight into the data that they are considering combining across studies. This saves researchers valuable time and effort while showing potential relationships between variables. The linear regression tool operates through a command-line interface integrated with the other tools (pynidm linear-regression) and provides the user with the opportunity to specify variables of interest using the rich query techniques available for NIDM documents and then conduct a linear regression with optional contrast and regularization.

Designing for inclusion in public playgrounds: a scoping review of definitions, and utilization of universal design

Purpose Public playgrounds afford children and families important opportunities for outdoor play, social participation, and inclusion. Unfortunately, many children and families experience barriers to accessing, using, and being included in public playgrounds. Consequently, Universal Design (UD) is promoted for providing conceptual guidance for designing for inclusion in public playgrounds. However, a lack of research evidence means researchers have engaged in the ongoing interpretation of the UD concept and related non-discriminatory planning and design concepts. Therefore, the aim of this study was to examine how UD, and related concepts, are used in peer-reviewed articles concerning public playgrounds. Materials and methods A scoping review was conducted in November 2019, which identified 15 peer-reviewed articles that met the inclusion criteria. Results Analysis revealed that the terms UD, inclusive design, accessibility, and usability are all being used to describe non-discriminatory planning and design concepts arbitrarily and without regard for higher or lower order concepts. Two broad interpretations were evident: (a) UD is synonymous with accessibility for some, and (b) UD is a higher-order concept that goes beyond accessibility for others. Nevertheless, findings highlight the utility of UD in underpinning the design of public playgrounds in many developed countries; however, the concept requires further clarity and specificity as it pertains to playground design and more pertinently inclusion in outdoor play. Conclusions We argue for further conceptual refinement to consolidate the importance and future application of UD for Play (UDP) in the design of public playgrounds that promote outdoor play, social participation, and inclusion. IMPLICATIONS FOR REHABILITATION Most peer-reviewed journal articles reviewed fail to define what is meant by the term Universal Design. Of those that do provide a definition, the outcome of inclusion in play, or the application of Universal Design to enable play in public playgrounds was unclear. Research to date has mostly focused on related concepts, including accessibility and usability, with less emphasis on Universal Design. Recommend a tailored perspective of Universal Design for Play (UDP).