Crossing the hurdle: the determinants of individual scientific performance

An original cross sectional dataset referring to a medium sized Italian university is implemented in order to analyze the determinants of scientific research production at individual level. The dataset includes 942 permanent researchers of various scientific sectors for a three year time span (2008 - 2010). Three different indicators - based on the number of publications or citations - are considered as response variables. The corresponding distributions are highly skewed and display an excess of zero - valued observations. In this setting, the goodness of fit of several Poisson mixture regression models are explored by assuming an extensive set of explanatory variables. As to the personal observable characteristics of the researchers, the results emphasize the age effect and the gender productivity gap, as previously documented by existing studies. Analogously, the analysis confirm that productivity is strongly affected by the publication and citation practices adopted in different scientific disciplines. The empirical evidence on the connection between teaching and research activities suggests that no univocal substitution or complementarity thesis can be claimed: a major teaching load does not affect the odds to be a non-active researcher and does not significantly reduce the number of publications for active researchers. In addition, new evidence emerges on the effect of researchers administrative tasks, which seem to be negatively related with researcher's productivity, and on the composition of departments. Researchers' productivity is apparently enhanced by operating in department filled with more administrative and technical staff, and it is not significantly affected by the composition of the department in terms of senior or junior researchers.Comment: Revised version accepted for publication by Scientometric

Joint perceptual decision-making: a case study in explanatory pluralism.

Traditionally different approaches to the study of cognition have been viewed as competing explanatory frameworks. An alternative view, explanatory pluralism, regards different approaches to the study of cognition as complementary ways of studying the same phenomenon, at specific temporal and spatial scales, using appropriate methodological tools. Explanatory pluralism has been often described abstractly, but has rarely been applied to concrete cases. We present a case study of explanatory pluralism. We discuss three separate ways of studying the same phenomenon: a perceptual decision-making task (Bahrami et al., 2010), where pairs of subjects share information to jointly individuate an oddball stimulus among a set of distractors. Each approach analyzed the same corpus but targeted different units of analysis at different levels of description: decision-making at the behavioral level, confidence sharing at the linguistic level, and acoustic energy at the physical level. We discuss the utility of explanatory pluralism for describing this complex, multiscale phenomenon, show ways in which this case study sheds new light on the concept of pluralism, and highlight good practices to critically assess and complement approaches

Exploring the interdependencies of research funders in the UK

Investment in medical research is vital to the continuing improvement of the UK's health and wealth. It is through research that we expand our understanding of disease and develop new treatments for patients. Medical research charities currently contribute over £1 billion annually to medical research in the UK, of which over £350 million is provided by Cancer Research UK. Many charities, including Cancer Research UK, receive no government funding for their research activity. Cancer Research UK is engaged in a programme of work in order to better understand the medical research funding environment and demonstrate the importance of sustained investment. A key part of that is the Office of Health Economics‟ (OHE) 2011 report “Exploring the interdependency between public and charitable medical research”. This study found that there are substantial benefits, both financial and qualitative, from the existence of a variety of funders and that reductions in the level of government financial support for medical research are likely to have broader negative effects. This contributed to other evidence which found that the activities and funding of the charity, public and private sectors respectively are complementary, i.e. mutually reinforcing, rather than duplicative or merely substituting for one another. “Exploring the interdependencies of research funders in the UK” by the Office of Health Economics (OHE) and SPRU: Science and Technology Policy Research at the University of Sussex, represents a continued effort to build the evidence base around the funding of medical research. This report uncovers the extent to which funders of cancer research are interdependent, nationally and internationally. Key figures show that two thirds of publications acknowledging external support have relied on multiple funders, while just under half benefited from overseas funding, and almost a fifth are also supported by industry. In addition the analysis shows that the general public would not want tax funding of cancer research to be reduced, but would not donate enough to charities to compensate for any such reduction

Machine-actionable assessment of research data products

Research data management is a relevant topic for academic research which is why many concepts and technologies emerge to face the challenges involved, such as data growth, reproducibility, or heterogeneity of tools, services, and standards. The basic concept of research data management is a research data product; it has three dimensions: the data, the metadata describing them, and the services providing both. Traditionally, the assessment of a research data product has been carried out either manually via peer-review by human experts or automated by counting certain events. We present a novel mechanism to assess research data products. The current state-of-the-art of machine-actionable assessment of research data products is based on the assumption that its quality, impact, or relevance are linked to the likeliness of peers or others to interact with it: event-based metrics include counting citations, social media interactions, or usage statistics. The shortcomings of event-based metrics are systematically discussed in this thesis; they include dependance on the date of publication and the impact of social effects. In contrast to event-based metrics benchmarks for research data products simulate technical interactions with a research data product and check its compliance with best practices. Benchmarks operate on the assumption that the effort invested in producing a research data product increases the chances that its quality, impact, or relevance are high. This idea is translated into a software architecture and a step-by-step approach to create benchmarks based on it. For a proof-of-concept we use a prototypical benchmark on more than 795,000 research data products deposited at the Zenodo repository to showcase its effectiveness, even with many research data products. A comparison of the benchmark’s scores with event-based metrics indicate that benchmarks have the potential to complement event-based metrics and that both weakly correlate under certain circumstances. These findings provide the methodological basis for a new tool to answer scientometric questions and to support decision-making in the distribution of sparse resources. Future research can further explore those aspects of benchmarks that allow to improve the reproducibility of scientific findings.Dass das Management von Forschungsdaten ein relevantes Thema ist, zeigt sich an der Vielzahl an konzeptioneller und technischer Antworten auf die damit einhergehenden Herausforderungen, wie z.B. Datenwachstum, Reproduzierbarkeit oder Heterogenität der genutzten Tools, Dienste und Standards. Das Forschungsdatenprodukt ist in diesem Kontext ein grundlegender, dreiteilig aufgebauter Begriff: Daten, Metadaten und Dienste, die Zugriffe auf die beiden vorgenannten Komponenten ermöglichen. Die Beurteilung eines Forschungsdatenprodukts ist bisher händisch durch den Peer Review oder durch das Zählen von bestimmten Ereignissen realisiert. Der heutige Stand der Technik, um automatisiert Qualität, Impact oder Relevanz eines Forschungsdatenprodukts zu beurteilen, basiert auf der Annahme, dass diese drei Eigenschaften mit der Wahrscheinlichkeit von Interaktionen korrelieren. Event-basierte Metriken umfassen das Zählen von Zitationen, Interaktionen auf sozialen Medien oder technische Zugriffe. Defizite solcher Metriken werden in dieser Arbeit systematisch erörtert; besonderes Augenmerk wird dabei auf deren Zeitabhängigkeit und den Einfluss sozialer Mechanismen gelegt. Benchmarks sind Programme, die Interaktionen mit einem Forschungsdatenprodukt simulieren und dabei die Einhaltung guter Praxis prüfen. Benchmarks operieren auf der Annahme, dass der Aufwand, der in die Erzeugung und Wartung von Forschungsdatenprodukte investiert wurde, mit deren Qualität, Impact und Relevanz korreliert. Diese Idee wird in dieser Arbeit in eine Software-Architektur gegossen, für deren Implementierung geeignete Hilfsmittel bereitgestellt werden. Ein prototypischer Benchmark wird auf mehr als 795.000 Datensätzen des Zenodo Repositorys evaluiert, um die Effektivität der Architektur zu demonstrieren.Ein Vergleich zwischen Benchmark Scores und event-basierten Metriken legt nahe, dass beide unter bestimmten Umständen schwach korrelieren. Dieses Ergebnis rechtfertigt den Einsatz von Benchmarks als neues szientrometrisches Tool und als Entscheidungshilfe in der Verteilung knapper Ressourcen. Der Einsatz von Benchmarks in der Sicherstellung von reproduzierbaren wissenschaftlichen Erkenntnissen ist ein vielversprechender Gegenstand zukünftiger Forschung

Parents, Caregivers, and Peers: Patterns of Complementarity in the Social World of Children in Rural Madagascar

Research on childhood in anthropology and neighboring disciplines has continuously broadened the range of the social partners that are considered relevant for young children’s development—from parents to other caregivers, siblings, and peers. Yet most studies as well as interventions in early childhood still focus exclusively on parents, who are presumed to be the most significant socializing agents. Objecting to such a hierarchical understanding of the social world of children, I propose a complementarity view. Rather than being linearly ranked in a hierarchy of significance, children’s social partners may complement each other by providing different but equally significant experiences. My suggestions are based on an ethnographic study in a rural community in Madagascar. Focusing on children in the first 3 years of life, I explore the full range of their social partners and the respective experiences they provide. Caregivers focus on children’s physical needs and aim to keep them in a calm emotional state, while other young, related children are the most crucial partners when it comes to play, face-to-face interaction, and the exchange of intense emotions. These complementary roles, I argue, lead to the parallel formation of two distinct socio-emotional modes—a hierarchical and an egalitarian one

Empowering open science with reflexive and spatialised indicators

Bibliometrics have become commonplace and widely used by authors and journals to monitor, to evaluate and to identify their readership in an ever-increasingly publishing scientific world. This contribution introduces a multi-method corpus analysis tool, specifically conceived for scientific corpuses with spatialised content. We propose a dedicated interactive application that integrates three strategies for building semantic networks, using keywords (self-declared themes), citations (areas of research using the papers) and full-texts (themes derived from the words used in writing). The networks can be studied with respect to their temporal evolution as well as to their spatial expressions, by considering the countries studied in the papers under inquiry. The tool is applied as a proof-of-concept on the papers published in the online open access geography journal Cybergeo since its creation in 1996. Finally, we compare the three methods and conclude that their complementarity can help go beyond simple statistics to better understand the epistemological evolution of a scientific community and the readership target of the journal. Our tool can be applied by any journal on its own corpus, fostering thus open science and reflexivity

Complementary or Conflictual? Formal Participation, Informal Participation, and Organizational Performance

Most studies of worker participation examine either formal participatory structures or informal participation. Yet, increasingly, works councils and other formal participatory bodies are operating in parallel with collective bargaining or are filling the void left by its decline. Moreover, these bodies are sprouting in workplaces in which workers have long held a modicum of influence, authority, and production- or service-related information. This study leverages a case from the healthcare sector to examine the interaction between formal and informal worker participation. Seeking to determine whether or not these two forces—each independently shown to benefit production or service delivery—complement or undermine one another, we find evidence for the latter. In the case of the 27 primary care departments that we study, formal structures appeared to help less participatory departments improve their performance. However, these same structures also appeared to impede those departments with previously high levels of informal participation. While we remain cautious with respect to generalizability, the case serves as a warning to those seeking to institute participation in an environment in which some workers have long felt they had the requisite authority, influence, and information necessary to perform their jobs effectively