What do we know about the disruption indicator in scientometrics? An overview of the literature

The purpose of this paper is to provide a review of the literature on the original disruption indicator (DI1) and its variants in scientometrics. The DI1 has received much media attention and prompted a public debate about science policy implications, since a study published in Nature found that papers in all disciplines and patents are becoming less disruptive over time. This review explains in the first part the DI1 and its variants in detail by examining their technical and theoretical properties. The remaining parts of the review are devoted to studies that examine the validity and the limitations of the indicators. Particular focus is placed on (1) the time-sensitivity of disruption scores, (2) the convergent validity of disruption scores with expert judgments, and (3) the comparative performance of the DI1 and its variants. The review shows that, while the literature on convergent validity is not entirely conclusive, it is clear that some modified indicator variants, in particular DI5, show higher degrees of convergent validity than DI1. Limitations of the DI1 and its variants are summarized, and best practice guidelines are provided. The review encourages users of the indicator to inform about the variety of DI1 variants and to apply the most appropriate variant. More research on the convergent validity of the DI1 and its variants as well as on the time-sensitivity of disruption scores is needed before the indicators can be used in the research evaluation practice.Comment: 48 pages, 12 tables, 10 figures. Submitted to "Scientometrics

On the Mechanics Behind Academic Progress

In wissensintensiven Gesellschaften wird akademischem Fortschritt eine immer größere Bedeutung beigemessen. Sowohl die Generierung neuen Wissens als auch die Ausbildung hochqualifizierter Arbeitskräfte spielen hierbei eine Schlüsselrolle. Jüngste Studien legen allerdings nahe, dass es zunehmend schwieriger wird, neue Ideen zu finden und dass längere Bildungswege das individuelle Innovationspotenzial erheblich reduzieren. Vor diesem Hintergrund widmet sich die vorliegende Dissertation den Mechanismen, die akademischem Fortschritt zugrunde liegen. Im ersten Teil der Arbeit liegt der Fokus auf Spillover-Effekten in der Wissensproduktion. Der Ursprung dieser Effekte wird primär bei herausragenden Forscherinnen und Forschern vermutet, zu deren Ermittlung Metadaten zu 15,6 Millionen Publikationen zusammengestellt wurden. Innerhalb der Forschungselite erweist sich eine Subgruppe von 162 Personen als zentral für die Identifikation kausaler Effekte. Konstituierendes Merkmal dieser Personengruppe ist ihr unerwarteter Tod und ein damit verbundenes vorzeitiges Karriereende. Auf diese letalen Schocks folgend zeigt sich ein signifikanter Rückgang im Publikationsoutput ihres direkten Kollaborationsnetzwerks. Spillover-Effekte werden zwar aggregiert deutlich, treten über das Fächerspektrum allerdings in sehr heterogenen Formen auf. Der zweite Teil der Arbeit geht auf die institutionelle Ebene über und untersucht, wie effizient europäische Universitäten in Forschung und Lehre agieren. Effizienz wird hierbei über die Relation von Inputs und Outputs modelliert, die neben bibliometrischen Daten auch amtliche Statistiken zu Finanz- und Studierendenzahlen miteinbeziehen. Vergleichbar mit dem Resultat des ersten Teils wird offenbar, dass universitäre Effizienz je nach fachlichem Schwerpunkt von einer Reihe unterschiedlicher Faktoren bedingt wird. Abschließend erfolgt im dritten Teil der Arbeit die Betrachtung eines groß angelegten Programms zur Förderung der Hochschullehre in Deutschland. Die kompetitive Mittelvergabe des Qualitätspakts Lehre lässt darauf schließen, dass die Drittmittelakquise deutlich positive Pfadabhängigkeiten aufweist und somit das potenzielle Risiko birgt, finanzielle Ungleichheiten zu intensivieren

Language and Literacy Multilevel Constructs in Young Nonmainstream American English Speakers: Examining Relationships between Latent Variables

According to the National Assessment of Education Progress (NAEP, 2013), children from race and language minority groups continue to perform significantly lower than their peers on reading achievement tests. Current perspectives suggest that multiple factors (e.g., household income, parent education) likely contribute to the achievement gap between African American children and their White peers and children from low income and middle income households (Barton & Coley, 2010; Chatterji, 2006; Jencks & Phillips, 1998), leading to multiple approaches (e.g., Head Start Early Reading First) to prevent or alleviate the trend (Barnett, Coralon, Fitzgerald, & Squires, 2011). However, African American children continue to perform lower than their White peers, and continue to be over-represented in special services. It has become increasingly important to understand the contributors to early reading development among African American children. The purpose of this study was to provide a descriptive view of early language and literacy among typically developing children in prekindergarten who speak nonmainstream American English at child and classroom levels. Approximately 673 typically developing children in 95 prekindergarten classrooms were included in this study from a larger cross-sectional study. Results support a model with language, literacy, and dialect as separate constructs at the child level while language and literacy as one construct and dialect as the second construct at the classroom level. Language and literacy were highly related but distinct at the child level but perfectly correlated at the classroom level. The dialect construct was moderately and negatively related to language and literacy at both levels

A Multilevel Multitrait-Multimethod Analysis of the Child Behavior Checklist

Behavioral and emotional problems (BEPs) are known to affect children's ability to shape and maintain effective social relationships. BEPs are typically categorized into two main factors: internalizing and externalizing behaviors. Internalizing behaviors represent introverted problems, directed inwardly to the individual. While externalizing behavior patterns represent behaviors that are directed outwardly. Behaviors, emotions and thoughts are experienced by all people but on a continuum rather than in terms of absence versus presence of the behavior. The child behavior checklist (CBCL) is used to measure BEPs. The system of CBCL (parent form) measures also includes a teacher rating form and a youth self-report. Using 62 teachers and 311 students, the present study assessed convergent and discriminant validity using a correlated trait, correlated method minus one [CT-C(M-1)] model. The results showed low to moderate teacher-student agreement on the traits. To extend the theoretical structure of the teacher and self-report forms, the present study assessed the nested structure of the data using a multilevel model. Results revealed the nested structure of the data should not be ignored

The MinK Framework: An Integrated Framework to Assess Individual Knowledge in Organisational Context.

Knowledge is the currency of the global economy, the foundation of wealth creation, and the sole antecedent of sustainable competitive advantage in today’s markets. In the current business environment, success of organisations is dependent upon their ability to develop and implement resilient Knowledge Management (KM) strategies to leverage and exploit their knowledge assets. Yet, knowledge is intrinsically linked to individuals and their exclusive abilities to create, share and apply knowledge thereby creating value for their organisations. Knowledge holders are without doubt the valuable assets which lead the increasing velocity of organisational transformation in order to cope with market pressures and confront uncertainty. Effectual KM thus implicates knowledge assessment capability that enables the identification of knowledge holders within the firm and accordingly optimises the allocation of knowledge assets. Identifying and retaining knowledge holders requires a systematic KM initiative to help managers assess the individual knowledge of their employees and hence formulate and evaluate knowledge management and retention strategies. This research therefore attempts to focus on knowledge assessment practice and explores the underlying constructs of individual knowledge in the organisational context. In light of the knowledge-based view of the firm[1][2][3], a comprehensive theoretical model highlights the crucial role of individuals in organisational knowledge dynamics based on seminal KM theories of Stocks and Flows of Knowledge[4], Intellectual Capital[5] [6] [7], and the SECI Model of Knowledge Creation[8]. Evolving from this conceptual foundation, the MinK framework is proposed as an innovative framework that endows organisations in delineating knowledge stocks and visualising knowledge flows by providing an integrated assessment platform for decision makers. The presented framework ensures that individual knowledge is accurately assessed from a number of perspectives using a well-defined set of theoretically grounded and industry validated indicators stemming from a multi-dimensional scorecard. Flexibility is embedded in the MinK framework, allowing managers to customise the key measures according to the firm’s specific context. Adopting the 360-degree approach, the assessment process uses self evaluations and multi-source knowledge appraisals to provide rich and insightful results. An Individual Knowledge Index (IK-Index) that denotes the overall knowledge rating of each employee is another research outcome spanning out of a unique formula that combines a number of Multi-Criteria Decision Analysis (MCDA) techniques to consolidate assessment results into a single reflective numeral. The incorporation of technology enables the complete automation of the assessment process and helps to address parametric multiplicity and arithmetic complexity. Armed with advances in Information Technology, the MinK Web System offers a user-friendly interface supported by a sophisticated computational module and a smart deep learning algorithm to ensure the efficiency, security, and accuracy of the assessment process. Companies that used MinK in the pilot study have described the framework as an accurate assessment solution which can enable managers to make informed decisions, particularly in human capital planning. Such an approach balances the art and science of KM while taking into account the culture and dynamics of the organisation. Ultimately, this research advocates a people-centric KM approach that places the individual knowledge holder at the core of KM activity, and suggests that effective KM is essentially effective management of knowledge workers