The paper focuses on knowledge generation, a topic frequently overlooked in the traditional debates in epistemology and philosophy of science. We focus on investigation as the primary process generating knowledge and its products. Investigation is taken as a generalization of the research process that includes similar knowledge-generating practices in aboriginal communities. To characterize the complexity of investigation processes and their products we go beyond traditional epistemological characterization of knowledge in terms of mental states and turn to (...) the concept of routine. Investigation processes share a common symbolic representation form which we call here a knowledge thread. The dynamics of the knowledge thread may be characterized by two intertwined tiers: cognitive and institutional. Using examples from our previous studies, especially on the recent discovery of microRNAs in molecular biology, we illustrate the dynamics of threads and claim that it is susceptible to the social network analysis which, however, requires insightful applications and sound interpretation of the results. Such an interpretation, as we suggest, may further be elaborated on the grounds of anthropological theories of distributed agency and distributed cognition. (shrink)

IntroductionBisphenol A is highly debated and studied in relation to a variety of health outcomes. This large variation in the literature makes BPA a topic that is prone to selective use of literature, in order to underpin one’s own findings and opinion. Over time, selective use of literature, by means of citations, can lead to a skewed knowledge development and a biased scientific consensus. In this study, we assess which factors drive citation and whether this results in the (...) overrepresentation of harmful health effects of BPA.MethodsA citation network analysis was performed to test various determinants of citation. A systematic search identified all relevant publications on the human health effect of BPA. Data were extracted on potential determinants of selective citation, such as study outcome, study design, sample size, journal impact factor, authority of the author, self-citation, and funding source. We applied random effect logistic regression to assess whether these determinants influence the likelihood of citation.ResultsOne hundred sixty-nine publications on BPA were identified, with 12,432 potential citation pathways of which 808 citations occurred. The network consisted of 63 cross-sectional studies, 34 cohort studies, 29 case-control studies, 35 narrative reviews, and 8 systematic reviews. Positive studies have a 1.5 times greater chance of being cited compared to negative studies. Additionally, the authority of the author and self-citation are consistently found to be positively associated with the likelihood of being cited. Overall, the network seems to be highly influenced by two highly cited publications, whereas 60 out of 169 publications received no citations.ConclusionIn the literature on BPA, citation is mostly driven by positive study outcome and author-related factors, such as high authority within the network. Interpreting the impact of these factors and the big influence of a few highly cited publications, it can be questioned to which extent the knowledge development in human literature on BPA is actually evidence-based. (shrink)

Low-carbon technological innovation is the main means to develop a low-carbon economy, and network knowledge sharing and collaborative innovation is an effective model for the development of low-carbon technologies. First of all, this article adopts a decision-making experiment and evaluation laboratory method and interpretation structure model, combines the two methods, extracts the advantages of the two, and discards the shortcomings of the two, thus constructing a new optimized and upgraded interpretation structure model. We give methods to explore the main (...) influencing factors of collaborative innovation of low-carbon technologies for online knowledge sharing. Based on the industrial network knowledge sharing and cooperation network environment, the network evolution game model of network knowledge sharing knowledge collaboration is constructed to study the rewards and punishments, the profit distribution rate, the knowledge potential difference, and the parameter pairing of the network knowledge sharing cooperation network structure in the process of network knowledge sharing and collaborative knowledge innovation. The influence of the network knowledge sharing cooperation strategy is obtained through simulation to change the size of the relevant parameters so that the network knowledge sharing cooperation agent chooses the network evolution game of the sharing strategy to realize the optimal evolutionary stable strategy. According to the simulation results, this article proposes suggestions from the following aspects, aiming to improve the overall knowledge synergy effect of the network knowledge sharing and cooperation network. (shrink)

Discovering the influences between paintings and artists is very important for automatic art analysis. Lately, this problem has gained more importance since research studies are looking into explanations about the origin and evolution of artistic styles, which is a related problem. This paper proposes to build a multiplex artwork representation based on artistic formal concepts to gain more understanding about the aforementioned problem. We complement and built our approach on the previous notion of Creativity Implication Network. We used the (...) recently proposed MultiRank algorithm to suggest possible explanations of the dynamic of some artistic styles. Our results corroborate some well-known facts about the artists analyzed and give qualitative and quantitative information that show the possibilities and strengths of the proposed framework. We plan to expand our analysis to include more abstract artworks. Ideally, we are going to be able to validate more our results and test how our methodology could be used to generate visual artifacts too. (shrink)

The aim of this article is to map the intellectual structure of scholarship on economic and social value in the sport industry. Given that bibliometric techniques are specially appropriate for identifying the intellectual structures of a field of knowledge and complement traditional literature reviews, a co-citation bibliometric analysis has been applied. This kind of analysis identifies networks of interconnections. Therefore, we aim to detect both the most and the least active research areas in this field, as well as (...) their sub-disciplinary composition. There is an abundance of literature on sport efficiency and economic efficiency in the sport industry, our main conclusion is the identification of a literature gap in regard to social value in sport organisations, which is expected to be a research opportunity for scholars. This is in line with the lack of standardisation in the measurement for social value in sport organisations. In fact, similar to analysis undertaken in the past few decades of other industries with contributions to stakeholders and the multi-fiduciary theory of stakeholders, both the creation of social value indicators for sport entities and the empirical analysis of social efficiency in sport institutions, are identified and outlined as future areas of research. Therefore, this bibliometric analysis will contribute to determine the future challenges that this area of research will face in the following years so as to fill the literature gap identified. (shrink)

Although the connectionist approach has lead to elegant solutions to a number of problems in cognitive science and artificial intelligence, its suitability for dealing with problems in knowledge representation and inference has often been questioned. This paper partly answers this criticism by demonstrating that effective solutions to certain problems in knowledge representation and limited inference can be found by adopting a connectionist approach. The paper presents a connectionist realization of semantic networks, that is, it describes how (...) knowledge about concepts, their properties, and the hierarchical relationship between them may be encoded as an interpreter‐free massively parallel network of simple processing elements that can solve an interesting class of inheritance and recognition problems extremely fast—in time proportional to the depth of the conceptual hierarchy. The connectionist realization is based on an evidential formulation that leads to principled solutions to the problems of exceptions and conflicting multiple inheritance situations during inheritance, and the best‐match or partial‐match computation during recognition. The paper also identifies constraints that must be satisfied by the conceptual structure in order to arrive at an efficient parallel realization. (shrink)

BackgroundKnowledge development depends on an unbiased representation of the available evidence. Selective citation may distort this representation. Recently, some controversy emerged regarding the possible impact of swimming on childhood asthma, raising the question about the role of selective citation in this field. Our objective was to assess the occurrence and determinants of selective citation in scientific publications on the relationship between swimming in chlorinated pools and childhood asthma.MethodsWe identified scientific journal articles on this relationship via (...) a systematic literature search. The following factors were taken into account: study outcome (authors’ conclusion, data-based conclusion), other content-related article characteristics (article type, sample size, research quality, specificity), content-unrelated article characteristics (language, publication title, funding source, number of authors, number of affiliations, number of references, journal impact factor), author characteristics (gender, country, affiliation), and citation characteristics (time to citation, authority, self-citation). To assess the impact of these factors on citation, we performed a series of univariate and adjusted random-effects logistic regressions, with potential citation path as unit of analysis.ResultsThirty-six articles were identified in this network, consisting of 570 potential citation paths of which 191 (34%) were realized. There was strong evidence that articles with at least one author in common, cited each other more often than articles that had no common authors (odds ratio (OR) 5.2, 95% confidence interval (CI) 3.1–8.8). Similarly, the chance of being cited was higher for articles that were empirical rather than narrative (OR 4.2, CI 2.6–6.7), that reported a large sample size (OR 5.8, CI 2.9–11.6), and that were written by authors with a high authority within the network (OR 4.1, CI 2.1–8.0). Further, there was some evidence for citation bias: articles that confirmed the relation between swimming and asthma were cited more often (OR 1.8, CI 1.1–2.9), but this finding was not robust.ConclusionsThere is clear evidence of selective citation in this research field, but the evidence for citation bias is not very strong. (shrink)

According to the PubMed resource from the U.S. National Library of Medicine, over 750,000 scientific articles have been published in the ~5000 biomedical journals worldwide in the year 2007 alone. The vast majority of these publications include results from hypothesis-driven experimentation in overlapping biomedical research domains. Unfortunately, the sheer volume of information being generated by the biomedical research enterprise has made it virtually impossible for investigators to stay aware of the latest findings in their domain of interest, let alone to (...) be able to assimilate and mine data from related investigations for purposes of meta-analysis. While computers have the potential for assisting investigators in the extraction, management and analysis of these data, information contained in the traditional journal publication is still largely unstructured, free-text descriptions of study design, experimental application and results interpretation, making it difficult for computers to gain access to the content of what is being conveyed without significant manual intervention. In order to circumvent these roadblocks and make the most of the output from the biomedical research enterprise, a variety of related standards in knowledge representation are being developed, proposed and adopted in the biomedical community. In this chapter, we will explore the current status of efforts to develop minimum information standards for the representation of a biomedical experiment, ontologies composed of shared vocabularies assembled into subsumption hierarchical structures, and extensible relational data models that link the information components together in a machine-readable and human-useable framework for data mining purposes. (shrink)

Although for many years a sharp distinction has been made in language research between rules and words—with primary interest on rules—this distinction is now blurred in many theories. If anything, the focus of attention has shifted in recent years in favor of words. Results from many different areas of language research suggest that the lexicon is representationally rich, that it is the source of much productive behavior, and that lexically specific information plays a critical and early role in the interpretation (...) of grammatical structure. But how much information can or should be placed in the lexicon? This is the question I address here. I review a set of studies whose results indicate that event knowledge plays a significant role in early stages of sentence processing and structural analysis. This poses a conundrum for traditional views of the lexicon. Either the lexicon must be expanded to include factors that do not plausibly seem to belong there; or else virtually all information about word meaning is removed, leaving the lexicon impoverished. I suggest a third alternative, which provides a way to account for lexical knowledge without a mental lexicon. (shrink)

This article uses the methods of citation and network analysis to map the global structure of the intellectual field and its development over time. Through the case study of Mersenne's, Oldenburg's and Darwin's correspondences, we show how looking at letters as a corpus of data can provide a global representation of the evolving conversation going on in the Republic of Letters and in intellectual and scientific fields. Aggregating general correspondences in electronic format offers a global portrait of the (...) evolving composition of the intellectual and scientific scene, its changing foci of interests and the fortune of the intellectual discussions as expressed in cited persons in the letters. Such tools help replace a purely metaphoric use of the term “network” by a visible map of the intellectual relations between people on which well defined calculations of the centrality of the positions of different actors can be made as well as their evolution over time. These techniques provide welcome additions to the tool kit of scholars in an age where the computer and the web offer new ways of mapping and mining the rich store of information contained in intellectual correspondences. ☆ I would like to thank Alain Couillard for the production of the figures and Vincent Larivière and the anonymous referees of the journal for useful comments and suggestions on an earlier version of this paper. Thanks also to the many comments received over the last 10 years as I presented preliminary results of this research at the REHSEIS research center of Université of Paris VII in 1999, the Dibner Institute for the History of Science and Technology at MIT in 2000, at Pietro Corsi's seminar at Oxford University in 2007 and at the History Department of Ottawa University in 2010. (shrink)

Providing comprehensive sexuality education in schools is a work in progress in many countries throughout the world. In some countries, the journey is just beginning; in others, investments in this field have been made for many years. It is and has been difficult in Pakistan to implement and promote reproductive health, women’s empowerment, and CSE. In Pakistan, previous implementation efforts revealed the critical role of community influencers in propagating misleading information about the initiatives, inciting organized community resistance, and provoking backlash. (...) This paper looked at several aspects of community resistance, as well as approaches for overcoming the resistance for increasing community engagement in the implementation of CSE in Islamabad, Pakistan. To analyze community perceptions of CSE implementation in Islamabad, the community readiness assessment questionnaire was adapted. Questions and prompts for discussion included leadership, current initiatives, community knowledge, resource availability, community support, and implementation strategies. A total of 35 in-depth interviews were conducted. Data was analyzed and interpreted using qualitative content analysis to explore community perspectives that contribute to resistance around CSE, as well as implementation options. Using inter-code relationship data, network analysis was conducted to provide a graphical representation of the analyzed qualitative data. The study reveals community resistance to CSE being implemented in schools. Misconceptions, a lack of awareness, a lack of priority, and the lack of dedicated resources are just a few of the primary implementation challenges to consider when implementing CSE in practice. Network analysis identified, based on modularity class, five distinct clusters of highly connected nodes/codes: non-governmental organizations, misconceptions, resources and policy, strategies and community support, and personal social and health education and current efforts. In conservative environments and when confronted with resistance, innovative marketing and rebranding are critical for priority setting and community engagement, especially when developing curriculum and implementing CSE. Some of the suggested strategies for implementation include community sensitization through strategic awareness campaigns, involving already established infrastructure and NGOs, endorsement by all major stakeholders, particularly decision-makers, and the use of creative digital platforms for better dissemination. (shrink)

A number of accounts of expert programming behavior have been advanced. These models of the programming activity have served to highlight the range of factors that are thought to underpin programming strategy. However, such accounts have tended to emphasize either the effects of the organization of the programmer's knowledge representation or the role played by features of the notation of the task language on the emergence, development, and support of particular forms of strategy. Such work has neglected to (...) (a) provide an account of the way in which these factors might interact to determine programming strategy, and (b) shed light upon the nature of the development of particular strategies as programming skill increases.This article presents the results of an empirical analysis of the strategies employed by programmers of varying skill levels using different programming languages. The development of particular forms of strategy is hypothesized to be related both to the development of systematic asymmetries in programmers' generic plan‐based representations of programming knowledge and to the way in which features of the notation of particular programming languages might differentially support particular strategies. However, the results of the study reported here suggest that these effects must be interpreted within a broad developmental context. Hence, as programming skill develops, it appears that the notation of the task language tends to take precedence as a determinant of strategy, but has less relevance at beginning stages of skill development and within the context of expert performance. This finding would not be predicted by current models of the programming activity because such models suggest that any notational effects will tend to be consistent regardless of the skill level attained by the programmer. This article endeavors to extend current models of programming by emphasizing the need to consider in detail not only the development of programming strategy, but also the way in which knowledge representation and features of the task langauge interact to give rise to particular forms of programming behavior. (shrink)

Intended to introduce readers to the use of artificial neural networks in the study of music, this volume contains numerous case studies and research findings that address problems related to identifying scales, keys, classifying musical chords, and learning jazz chord progressions. A detailed analysis of networks is provided for each case study which together demonstrate that focusing on the internal structure of trained networks could yield important contributions to the field of music cognition.

There are various approaches to ontology metamodelling, and the notion of biologically inspired modular knowledge representation systems can provide insight in the workings of such phenomena as emergent properties of network structures. What is more relevant from knowledge engineering standpoint, such approach could provide innovation and enhancement of the level of expression as well as overall functionality of modular ontologies. To do so, one needs to find biological structures that would be the basis for modularity on different (...) levels of hierarchy within the artificial system. Network analysis tools as well as systems biology and biocomputing provide a framework for research in this field. (shrink)

Scientific networks are often investigated by means of citation analyses. Yet, interpretation of such networks in terms of semantic (and often disciplinary) content heavily depends on supplementary knowledge, notably about author research specialties. Similar situations arise more generally in many types of social networks whose semantic interpretation relies on supplementary information. Here, author community net-works are inferred from a topic model which provides direct insights into the semantic specificity of the identified “hidden communities of interest” (HCoI). Using a (...) philosophy of science corpus of full-text articles (N=16,917), we investigate its underlying communities by measuring topic profile correlations be-tween authors. A diachronic perspective is built by modeling the research networks over different time-periods and mapping genealogical relationships be-tween communities. The results show a marked in-crease in philosophy of science communities over time and trace the progressive appearance of the specialization areas that structure the field today. (shrink)

Criminal intelligence data poses problems for conventional database technology. It has little structure or homogeneity and queries may involve looking for unknown associations between entities; such open-ended queries cannot be made in current systems. Finally, the data must be presented in an intuitively simple fashion for both investigative and evidential purposes. We discuss a database system which uses a labelled graph as its data model. This approach obviates the need for schema design, allows queries which look for associations between entities (...) to be implemented and provides the basis for a natural visual representation of the data. (shrink)

Network embedding aims to learn the low-dimensional representations of nodes in networks. It preserves the structure and internal attributes of the networks while representing nodes as low-dimensional dense real-valued vectors. These vectors are used as inputs of machine learning algorithms for network analysis tasks such as node clustering, classification, link prediction, and network visualization. The network embedding algorithms, which considered the community structure, impose a higher level of constraint on the similarity of nodes, and they make the learned node embedding (...) results more discriminative. However, the existing network representation learning algorithms are mostly unsupervised models; the pairwise constraint information, which represents community membership, is not effectively utilized to obtain node embedding results that are more consistent with prior knowledge. This paper proposes a semisupervised modularized nonnegative matrix factorization model, SMNMF, while preserving the community structure for network embedding; the pairwise constraints information are effectively fused with the adjacency matrix and node similarity matrix of the network so that the node representations learned by the model are more interpretable. Experimental results on eight real network datasets show that, comparing with the representative network embedding methods, the node representations learned after incorporating the pairwise constraints can obtain higher accuracy in node clustering task and the results of link prediction, and network visualization tasks indicate that the semisupervised model SMNMF is more discriminative than unsupervised ones. (shrink)

Citing of previous publications is an important factor in knowledge development. Because of the great amount of publications available, only a selection of studies gets cited, for varying reasons. If the selection of citations is associated with study outcome this is called citation bias. We will study determinants of citation in a broader sense, including e.g. study design, journal impact factor or the funding source of the publication. As a case study we assess which factors drive (...) class='Hi'>citation in the human literature on phthalates, specifically the metabolite mono phthalate. A systematic literature search identified all relevant publications on human health effect of MEHP. Data on potential determinants of citation were extracted in duplo. Specialized software was used to create a citation network, including all potential citation pathways. Random effect logistic regression was used to assess whether these determinants influence the likelihood of citation. 112 Publications on MEHP were identified, with 5684 potential citation pathways of which 551 were actual citations. Reporting of a harmful point estimate, journal impact factor, authority of the author, a male corresponding author, research performed in North America and self-citation were positively associated with the likelihood of being cited. In the literature on MEHP, citation is mostly driven by a number of factors that are not related to study outcome. Although the identified determinants do not necessarily give strong indications of bias, it shows selective use of published literature for a variety of reasons. (shrink)

Enterprise Network has increasingly gained popularity in academia. Over the past few decades, a substantial amount of EN studies have been published in China. Drawing upon a sample of 603 papers retrieved from the Chinese Social Sciences Citation Index database between 1998 and 2020, this study aims to delve into the status quo, knowledge base, research focus, and evolutionary trends of EN research in China. A multifaceted bibliometric analysis was performed using CiteSpace. The findings mainly indicate that the (...) research on EN in China has a clear development context, and the research content gradually changes from macro to micro. In addition to foreign Social Network theories, the research results of domestic scholars have become the basic knowledge in this field. The research includes these topics: the conceptualization of EN, EN as indicators of enterprise development, EN’s impact on start-ups, mechanisms of EN’s effect and governance of EN. The potential direction for future research has been identified as the integration between EN and other forms of networks, and the structure of EN. (shrink)

This study was developed around concerns about how indigenous knowledges have been represented and applied in environment and development education. The first phase of the study is a genealogical analysis after Michel Foucault. This probes representations and applications of plant-based indigenous knowledge in selected anthropological, botanical and environmental education texts in southern Africa. The emerging insights were deepened using a Social Realism vantage point after Margaret Archer to shed light on agential issues in environmental education and development contexts. Here (...) her morphogenetic/morphostatic analysis of social transformation or reproduction is used to trace changes in indigenous knowledge representations and applications over time . The second phase uses the same perspectives and tools to extend the analysis of power/knowledge relationships into the interface of indigenous communities and modern institutions in two case study settings in the Eastern Cape of South Africa. This study reveals colonially-derived hegemonic processes of modern/Western scientific institutional representations/interpretations of the knowledges of indigenous communities. It also tracks a continuing trajectory of their dominating and prescriptive mediating control over local knowledges from the pre-colonial context through into the post-colonial period in southern Africa. The analysis reveals how this hegemony is sustained through the deployment of institutional strategies of representation that transform local knowledges into the disciplinary knowledge discourses of modern scientific institutions. These representational strategies therefore generate/reproduce and validate disciplinary discourses about the other, constructing disciplinary 'regimes of truth'. In this way modern institutions appropriate and displace indigenous/local knowledges, silence the voices of local communities and regulate individual and community agency within a continuing subjugation of indigenous knowledges. This study reveals how working within modern institutions and disciplinary knowledges in participative education and development interactions can serve to implicate indigenous researchers in these institutional hegemonic processes. The study also notes evidence of a continued resistance to hegemonic Western knowledge discourses as indigenous communities have sustained many knowledge practices alongside Western knowledge discourses. There is also evidence of a recent emergence of counter-hegemonic indigenous knowledge discourses in environmental education and development practices in southern Africa. It is noted that these have been contingent upon the changing political terrain in southern Africa as this has opened the way for alternative discourses to the dominant conventional Western knowledges in formal education and development contexts. The counterhegemonic discourses invert power/knowledge relations, decentre hegemonic discourses and reposition indigenous knowledges in formal education and development contexts. This study suggests the need to foreground indigenous knowledges as a process of knowledge decolonisation that gives contextual and epistemic relevance to environmental education and development processes. This calls for a need for new strategies to transform existing institutions by creating enabling spaces for the representational inclusion of indigenous knowledges in formal/conventional knowledge discourses and their application in social contexts. This opens up possibilities for plural knowledge representations and for their integrative and reciprocal co-engagement in situated contexts of environmental education and development in southern Africa. (shrink)

Representation of scientific knowledge in ontologies suffers so often from the lack of computational knowledge required for inference. This article aims to perform quantitative analysis on physical systems, that is, to answer questions about values of quantitative state variables of a physical system with known structure. For this objective, we incorporate procedural knowledge on two distinct levels. At the domain-specific level, we propose a representation model for scientific knowledge, i.e. variables, theories, and laws of (...) nature. At the domain-independent level, we provide an algorithm which, given a system S with known structure and a relevant scientific theory T, extracts a constraint network, whose variables are state variables of S defined by T, and whose constraints raise from relevant laws in T. The constraint network is then solved, to build a system of equations whose unknowns are the output variables of S. The proposed representation model and reasoning algorithm are evaluated by applying them to classic analysis examples. (shrink)

A scientific paper’s citation represents its influence, which is the most intuitive indicator to access the quality of papers. This paper mainly adopts the social network analysis method, using the authors and the keywords of sports industry papers in China to constitute the networks of collaboration and knowledge, to explore effects of the degree centrality of authors and keywords and the structural hole of authors and keywords on the citation of papers in the collaboration and knowledge (...) networks and draw the following conclusions: as for collaboration networks, the degree centrality at the paper level is positively correlated with citations; in the collaboration network, the positive correlation between the structural hole at the paper level and citations does not exist; within knowledge networks, an inverted- U shape was found between degree centrality and paper’s citation; and within knowledge networks, a positive correlation is in existence between the structural hole of papers and their citation. This study synthesizes the already widely used collaboration network with the knowledge network constructed through keywords, distinguishes from the previous network features focusing at the author level, and explores research projects of Chinese Sports Industry from the paper level, providing a new perspective for the research of sports industry in China, complementing the methods and ideas of sports industry research, as well as providing a reference for the research in other disciplinary fields. (shrink)

In this thought-provoking work, Tony D. Sampson presents a contagion theory fit for the age of networks. Unlike memes and microbial contagions, _Virality_ does not restrict itself to biological analogies and medical metaphors. It instead points toward a theory of contagious assemblages, events, and affects. For Sampson, contagion is not necessarily a positive or negative force of encounter; it is how society comes together and relates. Sampson argues that a biological knowledge of contagion has been universally distributed by way (...) of the rhetoric of fear used in the antivirus industry and other popular discourses surrounding network culture. This awareness is also detectable in concerns over _too much connectivity_, such as problems of global financial crisis and terrorism. Sampson’s “virality” is as established as that of the biological meme and microbe but is not understood through representational thinking expressed in metaphors and analogies. Rather, Sampson interprets contagion theory through the social relationalities first established in Gabriel Tarde’s microsociology and subsequently recognized in Gilles Deleuze’s ontological worldview. According to Sampson, the reliance on representational thinking to explain the social behavior of networking—including that engaged in by nonhumans such as computers—allows language to overcategorize and limit analysis by imposing identities, oppositions, and resemblances on contagious phenomena. It is the power of these categories that impinges on social and cultural domains. Assemblage theory, on the other hand, is all about relationality and encounter, helping us to understand the viral as a positively sociological event, building from the molecular outward, long before it becomes biological. (shrink)

In anticipation of the journal’s centenary in 2027 this paper provides a citation network analysis of all available citation and publication data of the Australasian Journal of Philosophy (1923–2017). A total of 2,353 academic articles containing 21,772 references were collated and analyzed. This includes 175 articles that contained author-submitted keywords, 415 publisher-tagged keywords and 519 articles that had abstracts. Results initially focused on finding the most published authors, most cited articles and most cited authors within the journal, followed (...) by most discussed topics and emerging patterns using keywords and abstracts. The analysis then proceeded to apply social network analysis using Kumu© – a visualization platform for mapping systems and relationships using large datasets. Analysis reveals topic clusters both unique to the journal, and inclusive of the journal’s history. Results from this analysis reaffirm the journal’s continuing focus on topics in traditional analytic philosophy such as morality, epistemology and knowledge, whilst also featuring topics associated with logic and paradox. This paper presents a new approach to analysing and understanding the historic and emerging topics of interest to the journal, and its readership. This has never previously been done for single philosophy journal. This is historically important given the journal’s forthcoming centenary. (shrink)

Works out the implications of the claims of Ch. 5. Concepts used to explain actions of thinking creatures are irreducibly causal: the explanatory causal vocabulary that we call upon to interpret the semantics of a thinking object or creature is normative, relying on the interpreter's own standards of rationality. Sciences like physics, on the other hand, seek explanations and laws in which causal concepts no longer figure. Neither knowledge of the syntactical program of a computer nor knowledge of (...) the neurophysiology of an organism warrant our attributing to the object or creature a holistic normative network of concepts, acquired through its interactions with the surrounding world. Consequently, information, ends, or strategies can be represented in such a system, but the system cannot be interpreted as having the information, ends, or strategies. Generally, then, the difference between mind and body is not an ontological difference between types of entities, but a difference between schemes of classificatory concepts. (shrink)

This paper is concerned with the representation in academic journal articles and textbooks of an organisation theory. In the case of Burns’ and Stalker’s book The Management of Innovation (1961,1966), summaries of the text by other scholars have arguably differed from the original authors and among themselves in their emphases. Similar points have been made about representations of other theorists such as Kurt Lewin and, perhaps most famously, Adam Smith. They all raise issues about the meanings of texts and (...) where such meanings lie: with the author, the reader, the text itself or perhaps some combination of these. They also raise questions about whether texts can be shown to have definitive meanings; and if not, whether there are any criteria for adjudicating on the validity of varied interpretations. Representations by textbook writers are analysed and questions about the meaning of texts raised by ‘structuralist’ and ‘deconstructionist’ writers examined. Their writings beg certain questions about textual representations. Perhaps the most extreme of these views is Barthes’ concept of the ‘death of the author’. Like Barthes, Derrida argues, for the reasons mentioned above, that there is no underlying, final decipherable meaning in a text, but gives more credence to the role of the author, accepting the validity of the author’s consciousness and intentions as one of the sources of meaning in texts. There are also other sources: the situatedness and historical context of the text and the text itself. Derrida’s concept of ‘différance’ requires the reader to engage in an analysis of the text which offers limitless possibilities for interpretation and a renunciation of the certainty of truth, because the meaning of a text may extend beyond the limits of our knowledge at any one time. His notion of the ‘logic of supplementarity’ is a further means to analyse texts, as it also disprivileges obvious or overt meanings in texts by overturning hierarchy in oppositions and questioning univocal definitions of meaning. Questions inspired by these and other writers give rise to an exploration of who is speaking in the text; which subject matter is represented as central and which as marginal; binary oppositions within the text and intertextual connections. The paper then begins the more ambitious task of answering the broader question as to whether it can be shown that there are more and less ‘representative’ or ‘stronger’ interpretations of a text. (shrink)

The description of named entities in terminological knowledge bases has never been addressed in any depth in terminology. Firm preconceptions, rooted in philosophy, about the only referential function of proper names have presumably led to disparage their inclusion in terminology resources, despite the relevance of named entities having been highlighted by prominent figures in the discipline of terminology. Scholars from different branches of linguistics depart from the conservative stance on proper names and have foregrounded the need for a novel (...) approach, more linguistic than philosophical, to describing proper names. Therefore, this paper proposed a linguistic and terminological approach to the study of named entities when used in scientific discourse, with the purpose of representing them in EcoLexicon, an environmental knowledge base designed according to the premises of Frame-based Terminology. We focused more specifically on named rivers mentioned in a coastal engineering corpus. Inclusion of named entities in terminological knowledge bases requires analyzing the context that surrounds them in specialized texts because these contexts convey specialized knowledge about named entities. For the semantic representation of context, this paper thus analyzed the local syntactic and semantic contexts that surrounded potamonyms in coastal engineering texts and described the semantic annotation of the predicate-argument structure of sentences where a potamonym was mentioned. The semantic variables annotated were the following: semantic category of the arguments; semantic role of the arguments; semantic relation between the arguments; and lexical domain of the verbs. This method yielded valuable insight into the different semantic roles that named rivers played, the entities and processes that participated in the events educed by potamonyms through verbs, and how they all interacted. Furthermore, since arguments are specialized terms and verbs are relational constructs, the analysis of argument structure led to the construction of semantic networks that depicted specialized knowledge about named rivers. These conceptual networks were then used to craft the thematic description of potamonyms. Accordingly, the semantic network and the thematic description not only constituted the representation of a potamonym in EcoLexicon, but also allowed the geographic contextualization of specialized concepts in the terminological resource. (shrink)

Science maps are visual representations of the structure and dynamics of scholarly knowl­edge. They aim to show how fields, disciplines, journals, scientists, publications, and scientific terms relate to each other. Science mapping is the body of methods and techniques that have been developed for generating science maps. This entry is an introduction to science maps and science mapping. It focuses on the conceptual, theoretical, and methodological issues of science mapping, rather than on the mathematical formulation of science mapping techniques. After (...) a brief history of science mapping, we describe the general procedure for building a science map, presenting the data sources and the methods to select, clean, and pre-process the data. Next, we examine in detail how the most common types of science maps, namely the citation-based and the term-based, are generated. Both are based on networks: the former on the network of publications connected by citations, the latter on the network of terms co-occurring in publications. We review the rationale behind these mapping approaches, as well as the techniques and methods to build the maps. We also present less-common types of science maps, including co-authorship networks, interlocking editorship networks, maps based on patents’ data, and geographic maps of science. Moreover, we consider how time can be represented in science maps to investigate the dynamics of science. We also discuss some epistemological and sociological topics that can help in the interpretation, contextualization, and assessment of science maps. Then, we present some possible applications of science maps in science policy. In the conclusion, we point out why science mapping may be interesting for all the branches of meta-science, from knowl­edge organization to epistemology. (shrink)

In this study, secondary school DKAB (Religious Culture and Moral Knowledge) lesson’s belief learning domain has been examined structurally. In this context, the basic principles of belief have been discussed according to Māturīdīsm, Ash'arism, Mutazilite and in places according to Shia. The common points and different aspects of the ideas in the domain of belief of these schools have been examined in a comparative way. Subjects such as the attribute of taqwin/creation, which is the main discussion between Māturīdīsm and (...) Ashʿarism, whether Allah can be known by reason, whether the good and the evil are determined by reason or nass/verses are the examples. Additionally existance of the immutable attributes and that whether they are eternal or not, that whether ru’yatullah/seeing God is possible or not and the conditions of the afterlife which have been points of discussion between Mutazilite and Ahl es-Sunnah have been handled in the article. Surely these are matters of extensive discussion; this study evaluated these topics in the pedagogical context of the belief learning domain of the DKAB lesson. Firstly the theological background of the belief learning domain of DKAB lesson has been handled. Then learning outcomes which are the first elements of the curriculum have been classified. And thirdly the text books which are the second dimension of the curriculum have been analyzed. The method of the study is document analysis. Belief is the first of the learning domains designated as worship, morality, Prophet Muhammad and culture, and it is also of great importance because it is the basis of other learning domains. Belief learning domain is in the interest of curriculum designers in terms of having some pedagogical features but it must also be in harmony with theological acceptances as it is one of the basic components of religiosity. The theological background is also directly related to the political and legal context of the lesson, such as doctriner and non-confessional status. Because when various interpretations of religion do not have common points or when the common points are weak, the non-confessional feature will always be a controversial matter. In theological texts God has been described as essential, the almighty, the omniscient and one who intervenes in the history. Discussions between Kalam schools and philosophical schools about God's attributes, or the discussions within the Kalam schools are very important in terms of reflecting God-universe-human relationship. One of the most important problems in this issue is that the conception of God is not decisive, and that the conception of matter and human must be compatible with the conception of God. Developing a theology in the context of God's attributes, excluding matter and human conceptions leads to an over-abstraction of the theological background. Moreover, changes in the conception of matter and human will harm the conception of God, and the contribution of religious education to those who searching for meaning will decrease. The fact that the faith principles of Islamic religion do not vary depending on the sects strengthens the status of non-confessional religous education. In addition, an essential God conceptualization facilitates the management of people their lives. For believers, life has a purpose and it is a preparation for the afterlife. Furthermore in the context of cultural knowledge, gaining in-depth knowledge is a remarkable support for social life. On the other hand, the achievements in the lesson curriculum are at the first levels in terms of taxonomy and this shows that the lesson does not support high level learning and identity formation. Considering the speed and severity of the transformation in social life, it is necessary to provide some qualities that will support the construction of self and personality of those who take religious education. However, the low level of objectives of the curriculum and the one-dimensionality of Bloom's taxonomy used in the curriculum have been an unsolved problem for a long time. This points out the importance of developing a curriculum of religious education, taking into account the theological background and the individual and social dimensions of human beings. On the other hand, it can be thought that there are some problems in the establishment of the relationship between God-universe-human in the textbooks. Although the content is suitable for personal God representation and gives prominence to causality tought, when it comes to the idea of order of the universe, it contradicts with personal God representation and moral development. When the idea of order is over-objectivized in the textbooks, it becomes unclear how God intervenes in the universe. So, it remains suspended that the learners how make sense of events and their actions. (shrink)

Semantic Network Analysis in Social Sciences introduces the fundamentals of semantic network analysis and its applications in the social sciences. Readers learn how to easily transform any given text into a visual network of words co-occurring together, a process that allows mapping the main themes appearing in the text and revealing its main narratives and biases. Semantic network analysis is particularly useful today with the increasing volumes of text-based information available. It is one of the developing, cutting-edge methods to organize, (...) identify patterns and structures, and understand the meanings of our information society. The first chapters in this book offer step-by-step guidelines for conducting semantic network analysis, including choosing and preparing the text, selecting desired words, constructing the networks, and interpreting their meanings. Free software tools and code are also presented. The rest of the book displays state-of-the-art studies from around the world that apply this method to explore news, political speeches, social media content, and even to organize interview transcripts and literature reviews. Aimed at scholars with no previous knowledge in the field, this book can be used as a main or a supplementary textbook for general courses on research methods or network analysis courses, as well as a starting point to conduct your own content analysis of large texts. (shrink)

We present a computational analysis of de re, de dicto, and de se belief and knowledge reports. Our analysis solves a problem first observed by Hector-Neri Castañeda, namely, that the simple rule -/- `(A knows that P) implies P' -/- apparently does not hold if P contains a quasi-indexical. We present a single rule, in the context of a knowledge-representation and reasoning system, that holds for all P, including those containing quasi-indexicals. In so doing, we explore the (...) difference between reasoning in a public communication language and in a knowledge-representation language, we demonstrate the importance of representing proper names explicitly, and we provide support for the necessity of considering sentences in the context of extended discourse (for example, written narrative) in order to fully capture certain features of their semantics. (shrink)

Purpose: This research examines postmodernism's influence in social and political change and its relationship to popular culture. It examines how postmodernism changed media studies, cultural anthropology, gender studies, and youth culture. This study seeks to address gaps in our knowledge by analyzing how postmodern notions promote a more flexible cultural analysis and challenge traditional identity and representation theories. Materials and Methods: Gayatri Chakravorty Spivak, Walter Benjamin, Susan Sontag, and Angela McRobbie are among the postmodernists and cultural theorists explored (...) in the book. Ethnographic, empirical, political, feminist, and cultural studies are used to study popular culture's evolution. This multidisciplinary research examines fashion, media, and moral panics in current youth culture to analyse cultural shifts. Findings: Postmodernism makes individuals doubt their beliefs, which fractures and changes their identities, according to the research. It concludes that cultural studies must remain flexible and unrigorous to address current social and political issues. The study shows that postmodernism has changed youth culture, media consumption, and gender relations. Additionally, it examines how famous cultural theorists have affected postmodernism and mainstream media discourse. Implications to Theory, Practice and Policy: Cultural studies must evolve to keep up with postmodern society's changing dynamics, according to study. It claims that empirical and interdisciplinary research are needed to understand cultural changes. It also invites cultural experts to investigate popular culture more openly and flexibly and reevaluate feminist theory in postmodern contexts. (shrink)

This study provides a general overview of contemporary business ethics research of the last 10 years (1997-2006) and discusses potential future research directions in business ethics based on the overview. Using citation and co-citation analysis, this study examined the citation data of journal articles, books, and other publications collected in the Social Sciences Citation Index (SSCI), wherein key research themes in business ethics studies in 1997—2006 and correlations between these themes were explored. The results show that (...) major research themes in business ethics have shifted in the last decade from research on ethical decision making and on the relationship between corporate social responsibility and corporate performance to research on stakeholder theory in business ethics and on the relationship between consumer behavior and corporate social responsibility. The results of this study help map the invisible network of knowledge production in business ethics research and provide important insights on future business ethics research. (shrink)

The uncertainty associated with paradigmatic families has been shown to correlate with their phonetic characteristics in speech, suggesting that representations of complex sublexical relations between words are part of speaker knowledge. To better understand this, recent studies have used two-layer neural network models to examine the way paradigmatic uncertainty emerges in learning. However, to date this work has largely ignored the way choices about the representation of inflectional and grammatical functions (IFS) in models strongly influence what they subsequently (...) learn. To explore the consequences of this, we investigate how representations of IFS in the input-output structures of learning models affect the capacity of uncertainty estimates derived from them to account for phonetic variability in speech. Specifically, we examine whether IFS are best represented as outputs to neural networks (as in previous studies) or as inputs by building models that embody both choices and examining their capacity to account for uncertainty effects in the formant trajectories of word final [ɐ], which in German discriminates around sixty different IFS. Overall, we find that formants are enhanced as the uncertainty associated with IFS decreases. This result dovetails with a growing number of studies of morphological and inflectional families that have shown that enhancement is associated with lower uncertainty in context. Importantly, we also find that in models where IFS serve as inputs—as our theoretical analysis suggests they ought to—its uncertainty measures provide better fits to the empirical variance observed in [ɐ] formants than models where IFS serve as outputs. This supports our suggestion that IFS serve as cognitive cues during speech production, and should be treated as such in modeling. It is also consistent with the idea that when IFS serve as inputs to a learning network. This maintains the distinction between those parts of the network that represent message and those that represent signal. We conclude by describing how maintaining a “signal-message-uncertainty distinction” can allow us to reconcile a range of apparently contradictory findings about the relationship between articulation and uncertainty in context. (shrink)

A defining characteristic of Alzheimer’s disease is difficulty in retrieving semantic memories, or memories encoding facts and knowledge. While it has been suggested that this impairment is caused by a degradation of the semantic store, the precise ways in which the semantic store is degraded are not well understood. Using a longitudinal corpus of semantic fluency data, we derive semantic network representations of patients with Alzheimer’s disease and of healthy controls. We contrast our network-based approach with analyzing fluency data (...) with the standard method of counting the total number of items and perseverations in fluency data. We find that the networks of Alzheimer’s patients are more connected and that those connections are more randomly distributed than the connections in networks of healthy individuals. These results suggest that the semantic memory impairment of Alzheimer’s patients can be modeled through the inclusion of spurious associations between unrelated concepts in the semantic store. We also find that information from our network analysis of fluency data improves prediction of patient diagnosis compared to traditional measures of the semantic fluency task. (shrink)

A mechanism for planning ahead would appear to be essential to any creature with more than insect level intelligence. In this paper it is shown how planning, using full means-ends analysis, can be had while avoiding the so called symbol grounding problem. The key role of knowledge representation in intelligence has been acknowledged since at least the enlightenment, but the advent of the computer has made it possible to explore the limits of alternate schemes, and to explore the (...) nature of our everyday understanding of the world around us. In particular, artificial intelligence (AI) and robotics has forced a close examination, by people other than philosophers, of what it means to say for instance that "snow is white." One interpretation of the "new AI" is that it is questioning the need for representation altogether. Brooks and others have shown how a range of intelligent behaviors can be had without representation, and this paper goes one step further showing how intending to do things can be achieved without symbolic representation. The paper gives a concrete example of a mechanism in terms of robots that play soccer. It describes a belief, desire and intention (BDI) architecture that plans in terms of activities. The result is a situated agent that plans to do things with no more ontological commitment than the reactive systems Brooks described in his seminal paper, "Intelligence without Representation.". (shrink)

Commonsense epistemology regards perceptual experience as a distinctive source of knowledge of the world around us, unavailable in ‘blindsight’. This is often interpreted in terms of the idea that perceptual experience, through its representational content, provides us with justifying reasons for beliefs about the world around us. I argue that this analysis distorts the explanatory link between perceptual experience and knowledge, as we ordinarily conceive it. I propose an alternative analysis, on which representational content plays no explanatory role: (...) we make perceptual knowledge intelligible by appeal to experienced objects and features. I also present an account of how the commonsense scheme, thus interpreted, is to be defended: not by tracing the role of experience to its contribution in meeting some general condition on propositional knowledge (such as justification), but by subverting the assumption that it has to be possible to make the role of experience intelligible in terms of some such contribution. (shrink)

In this paper we present a dynamic assignment language which extends the dynamic predicate logic of Groenendijk and Stokhof [1991: 39–100] with assignment and with generalized quantifiers. The use of this dynamic assignment language for natural language analysis, along the lines of o.c. and [Barwise, 1987: 1–29], is demonstrated by examples. We show that our representation language permits us to treat a wide variety of donkey sentences: conditionals with a donkey pronoun in their consequent and quantified sentences with donkey (...) pronouns anywhere in the scope of the quantifier. It is also demonstrated that our account does not suffer from the so-called proportion problem.Discussions about the correctness or incorrectness of proposals for dynamic interpretation of language have been hampered in the past by the difficulty of seeing through the ramifications of the dynamic semantic clauses (phrased in terms of input-output behaviour) in non-trivial cases. To remedy this, we supplement the dynamic semantics of our representation language with an axiom system in the style of Hoare. While the representation languages of barwise and Groenendijk and Stokhof were not axiomatized, the rules we propose form a deduction system for the dynamic assignment language which is proved correct and complete with respect to the semantics. (shrink)

In this chapter, we discuss social network analysis as a method for the history of economics. We argue that social network analysis is not primarily a method of data representation but foremost a method of discovery and confirmation. It is as such a promising method that should be added to the toolbox of the historian of economics. We furthermore argue that, to be meaningfully applied in history, social network analysis must be complemented with historical knowledge gained by other (...) means and often by more traditional, mostly qualitative, methods. It should therefore be viewed as a method that complements rather than replaces more established approaches in the history of economics. (shrink)

The concept of knowledge is the topic of this monograph, the purpose of which is to study how it has been represented in educational research literature since 1939. Six texts have been selected, which use the Malmö Longitudinal Study data. These texts span the time period of 1939-1995 and have different foci, such as intelligence, social adjustment, benefits of education, recurrent education and quality of life. Discourse analysis has been used to study the texts. The assumption, guiding the analysis, (...) is that representations of knowledge are found in the texts. In this study the representations that are sought are ideas with reference to knowledge. It was found that different concepts of knowledge have been constucted by diverse activities of choosing, judging and interpreting. The purposes and sources, for whcih these activities have been undertaken, are quite dissimilar, so much so, as to constitute differing conceptualizations of knowledge, underlying these six educational research texts.
The theoretical framework is based on the work of two philosophers, Ernst Cassirer and Michael Lyncg. Cassirer's work from the 1930s and 1940s, in which precision in scientific concepts is advanced, is contrasted to Lynch's work from 1995, in which he proposes the use of fluid concepts. One such fluid concept has been used in the title of this monograph. Over the years, conceptualizations of knowledge have changed in this educational discourse. These results are presented, using social cartography to map the texts as intertextual fields. Visualizing complex pheonomena in this manner provides the reader with an interpretation of the discourse, in which the change is seen. Thus, mapping opens up the discourse for us to see, showing us the concepts of knowledge embedded in the texts, and allows us to see how the ways of seeing have changed over time in this discourse. The monograph ends with a discussion on the construction of knowledge, its consequences for the nature of knowledge and Cassirer's "unity of essence". (shrink)

The vigorous development of online education has produced massive amounts of education data. How to mine and analyze education big data has become an urgent problem in the field of education and big data knowledge engineering. As for the dynamic learning data, knowledge tracing aims to track learners’ knowledge status over time by analyzing the learners’ exercise data, so as to predict their performance in the next time step. Deep learning knowledge tracking performs well, but they (...) mainly model the knowledge components while ignoring the personalized information of questions and learners, and provide limited interpretability in the interaction between learners’ knowledge status and questions. A context-aware attentive knowledge query network model is proposed in this paper, which combines flexible neural network models with interpretable model components inspired by psychometric theory. We use the Rasch model to regularize the embedding of questions and learners’ interaction tuples, and obtain personalized representations from them. In addition, the long-term short-term memory network and monotonic attention mechanism are used to mine the contextual information of learner interaction sequences and question sequences. It can not only retain the ability to model sequences, but also use the monotonic attention mechanism with exponential decay term to extract the hidden forgetting behavior and other characteristics of learners in the learning process. Finally, the vector dot product is used to simulate the interaction between the learners’ knowledge state and questions to improve the interpretability. A series of experimental results on 4 real-world online learning datasets show that CAKQN has the best performance, and its AUC value is improved by an average of 2.945% compared with the existing optimal model. Furthermore, the CAKQN proposed in this paper can not only track learners’ knowledge status like other models but also model learners’ forgetting behavior. In the future, our research will have high application value in the realization of personalized learning strategies, teaching interventions, and resource recommendations for intelligent online education platforms. (shrink)

Traditional historical scholarship struggles to keep up with the rapid pace of modern scientific publication trends. Even focusing on a particular scientific field, the rate of new publications far outpaces even the most studious historian’s research capacity. This essay summarizes an approach to this problem that uses computational techniques of network analysis. As a complement to close analysis of particular documents, network analysis can give a large-scale perspective on the history of science, identifying relational patterns across a vast number of (...) documents that might otherwise require an entire career to digest. To demonstrate the power of the approach, the essay applies network theory to a corpus of publications in evolutionary medicine. Four distinct networks, including those focused on authors, keywords, and citations, quickly unearth a range of relevant historical information. The essay illustrates how interpretable historical conclusions are drawn from a variety of quantitative metrics. The aim is to provide an overview of network techniques for historians looking to add robust network analysis to their research repertoire. (shrink)

Ontologies, as the term is used in informatics, are structured vocabularies comprised of human- and computer-interpretable terms and relations that represent entities and relationships. Within informatics fields, ontologies play an important role in knowledge and data standardization, representation, integra- tion, sharing and analysis. They have also become a foundation of artificial intelligence (AI) research. In what follows, we outline the Coronavirus Infectious Disease Ontology (CIDO), which covers multiple areas in the domain of coronavirus diseases, including etiology, transmission, epidemiology, (...) pathogenesis, diagnosis, prevention, and treatment. We emphasize CIDO development relevant to COVID-19. (shrink)

A characteristic form of philosophical inquiry seeks to answer ‘what is x?’ questions. In this paper, we ask how philosophers do and should adjudicate debates about the correct answer to such questions. We argue that philosophers do and should rely on a distinctive type of pragmatic and meta-representational reasoning – a form of rationalizing self-interpretation – in answering ‘what is x?’ questions. We start by placing our methodological discussion within a broader theoretical framework. We posit a necessary connection between epistemic (...) methodology and metasemantics. In our view, the correct semantic assignment for a representation must be justifiable from the epistemic perspective of the subject herself, given suitable empirical information and cognitive powers. So the upshot of your own ideal, fully informed epistemic methods will determine the correct answers to ‘what is x?’ questions. The bulk of the paper is devoted to articulating and defending our rationalizing self-interpretation account of philosophical methodology. By working through a specific example, we seek to isolate the relevant inputs into deliberation and the methods for adjudicating between competing answers to a ‘what is x?’ question. We suggest that the self-interpretive methods we isolate generalize across the board as a way of identifying the real nature of familiar topics. We also explain how these methods undercut the case for a priori conceptual analysis. (shrink)

Two fundamentally different perspectives on knowledge diffusion dominate debates about academic disciplines. On the one hand, critics of disciplinary research and education have argued that disciplines are isolated silos, within which specialists pursue inward-looking and increasingly narrow research agendas. On the other hand, critics of the silo argument have demonstrated that researchers constantly import and export ideas across disciplinary boundaries. These perspectives have different implications for how knowledge diffuses, how intellectuals gain and lose status within their disciplines, and (...) how intellectual reputations evolve within and across disciplines. We argue that highly general claims about the nature of disciplinary boundaries are counterproductive, and that research on the nature of specific disciplinary boundaries is more useful. To that end, this paper uses a novel publication and citation network dataset and statistical models of citation networks to test hypotheses about the boundaries between philosophy of science and 11 disciplinary clusters. Specifically, we test hypotheses about whether engaging with and being cited by scientific communities outside philosophy of science has an impact on one’s position within philosophy of science. Our results suggest that philosophers of science produce interdisciplinary scholarship, but they tend not to cite work by other philosophers when it is published in journals outside of their discipline. Furthermore, net of other factors, receiving citations from other disciplines has no meaningful impact—positive or negative—on citations within philosophy of science. We conclude by considering this evidence for simultaneous interdisciplinarity and insularity in terms of scientific trading theory and other work on disciplinary boundaries and communication. (shrink)

We explore one aspect of the structure of a codified legal system at the national level using a new type of representation to understand the strong or weak dependencies between the various fields of law. In Part I of this study, we analyze the graph associated with the network in which each French legal code is a vertex and an edge is produced between two vertices when a code cites another code at least one time. We show that this (...) network distinguishes from many other real networks from a high density, giving it a particular structure that we call concentrated world and that differentiates a national legal system (as considered with a resolution at the code level) from small-world graphs identified in many social networks. Our analysis then shows that a few communities (groups of highly wired vertices) of codes covering large domains of regulation are structuring the whole system. Indeed we mainly find a central group of influent codes, a group of codes related to social issues and a group of codes dealing with territories and natural resources. The study of this codified legal system is also of interest in the field of the analysis of real networks. In particular we examine the impact of the high density on the structural characteristics of the graph and on the ways communities are searched for. Finally we provide an original visualization of this graph on an hemicyle-like plot, this representation being based on a statistical reduction of dissimilarity measures between vertices. In Part II (a following paper) we show how the consideration of the weights attributed to each edge in the network in proportion to the number of citations between two vertices (codes) allows deepening the analysis of the French legal system. (shrink)

People undergo many idiosyncratic experiences throughout their lives that may contribute to individual differences in the size and structure of their knowledge representations. Ultimately, these can have important implications for individuals' cognitive performance. We review evidence that suggests a relationship between individual experiences, the size and structure of semantic representations, as well as individual and age differences in cognitive performance. We conclude that the extent to which experience-dependent changes in semantic representations contribute to individual differences in cognitive aging remains (...) unclear. To help fill this gap, we outline an empirical agenda that utilizes network analysis and involves the concurrent assessment of large-scale semantic networks and cognitive performance in younger and older adults. We present preliminary data to establish the feasibility and limitations of such empirical, network-analytical approaches. (shrink)

Given a controversial issue, argument mining from texts in natural language is extremely challenging: besides linguistic aspects, domain knowledge is often required together with appropriate forms of inferences to identify arguments. Via the analysis of various corpora, this contribution explores the types of knowledge that are required to develop an efficient argument mining system. We show that the Qualia structure of the Generative Lexicon with some extensions and a specific interpretation has some expressive capabilities which are appropriate for (...) this task. (shrink)