Busy academics share less: The impact of professional and family roles on academic withholding behaviour

Although academics are increasingly expected to share their research data and materials with other academics, many appear reluctant to do so. While extant research emphasises commercial involvement and peer influence as determinants of withholding behaviour, we hypothesise that the volume of competing commitments plays an important role in preventing academics from sharing. Using rich, multi-source data on 876 academics at a large research university, we explore how withholding behaviour is related to the breadth of professional and family roles. We find that academics engaged in more activities, including research, teaching and commercialisation, and with more young children, are more likely than their colleagues to withhold research data and materials from their previously published research. We explore the implications of these findings for scientific production and exchange, and for academics' workloads

An APRI+ALBI Based Multivariable Model as Preoperative Predictor for Posthepatectomy Liver Failure.

OBJECTIVE AND BACKGROUND Clinically significant posthepatectomy liver failure (PHLF B+C) remains the main cause of mortality after major hepatic resection. This study aimed to establish an APRI+ALBI, aspartate aminotransferase to platelet ratio (APRI) combined with albumin-bilirubin grade (ALBI), based multivariable model (MVM) to predict PHLF and compare its performance to indocyanine green clearance (ICG-R15 or ICG-PDR) and albumin-ICG evaluation (ALICE). METHODS 12,056 patients from the National Surgical Quality Improvement Program (NSQIP) database were used to generate a MVM to predict PHLF B+C. The model was determined using stepwise backwards elimination. Performance of the model was tested using receiver operating characteristic curve analysis and validated in an international cohort of 2,525 patients. In 620 patients, the APRI+ALBI MVM, trained in the NSQIP cohort, was compared with MVM's based on other liver function tests (ICG clearance, ALICE) by comparing the areas under the curve (AUC). RESULTS A MVM including APRI+ALBI, age, sex, tumor type and extent of resection was found to predict PHLF B+C with an AUC of 0.77, with comparable performance in the validation cohort (AUC 0.74). In direct comparison with other MVM's based on more expensive and time-consuming liver function tests (ICG clearance, ALICE), the APRI+ALBI MVM demonstrated equal predictive potential for PHLF B+C. A smartphone application for calculation of the APRI+ALBI MVM was designed. CONCLUSION Risk assessment via the APRI+ALBI MVM for PHLF B+C increases preoperative predictive accuracy and represents an universally available and cost-effective risk assessment prior to hepatectomy, facilitated by a freely available smartphone app

Observations on the changing language of accounting

The meaning of words can change over time. In addition, new words may enter a language, sometimes replacing other words. This article extends prior literature on language change in accounting by drawing to a larger extent on theories from linguistics, and by placing greater emphasis on mechanisms of and motivations for change. Particular emphasis is placed on the need to verbalize new concepts, and sociocultural change. The latter is illustrated with examples from the development of accounting as an occupational interest group, and the adoption of Anglo-American accounting terminology and culture. The article concludes that language change in accounting, including transmission between languages and cultures, can inform accounting historians about the transfer of technical developments, as well as about socio-economic, political or ideological processes, power relationships, and the importance of terminology in jurisdictional disputes

PiggyBac transposon tools for recessive screening identify B-cell lymphoma drivers in mice.

B-cell lymphoma (BCL) is the most common hematologic malignancy. While sequencing studies gave insights into BCL genetics, identification of non-mutated cancer genes remains challenging. Here, we describe PiggyBac transposon tools and mouse models for recessive screening and show their application to study clonal B-cell lymphomagenesis. In a genome-wide screen, we discover BCL genes related to diverse molecular processes, including signaling, transcriptional regulation, chromatin regulation, or RNA metabolism. Cross-species analyses show the efficiency of the screen to pinpoint human cancer drivers altered by non-genetic mechanisms, including clinically relevant genes dysregulated epigenetically, transcriptionally, or post-transcriptionally in human BCL. We also describe a CRISPR/Cas9-based in vivo platform for BCL functional genomics, and validate discovered genes, such as Rfx7, a transcription factor, and Phip, a chromatin regulator, which suppress lymphomagenesis in mice. Our study gives comprehensive insights into the molecular landscapes of BCL and underlines the power of genome-scale screening to inform biology

Come engage with me: The role of behavioural and attitudinal cohort effects on academic's levels of engagement with industry

Trabajo presentado a la DRUID-DIME Academy Winter Conference 2010 for doctoral students in "Innovation, Knowledge and Entrepreneurship" celebrada en Aalborg (Dinamarca) del 21 al 23 de Enero de 2010.Although academics have considerable autonomy, they work in a highly institutionalized environment and are subject to social expectations and pressures from a range of domains, including their colleagues, their department leadership, their university and members of their discipline. Recent efforts to understand how the behavior of an academic’s peers shapes the nature of academic’s engagement with industry have suggested that there are strong cohort effects, in that the entrepreneurial behavior of one’s colleagues in the same department will encourage academics to become entrepreneurs themselves. This study builds on and extends this work by exploring how both the behaviors and attitudes of colleagues shape an academic’s engagement with industry. In doing so, it separates out the effects of what local peers do from what they think about industry engagement in order to gain better understanding the nature of the social processes that shape an academic’s decision to engage with industry. The analysis builds on a set of rich datasets that cover the industrial engagements of large sample of UK academics from physical and engineering sciences. The paper argues - and empirically demonstrates - that both behavioral and attitudinal cohort effects shape individual engagement behavior and attitudes, yet behavioral effects have a stronger impact than attitudinal effects. It explores the implications of these findings our understanding of cohort effects in professional organizations and for policies designed to encourage academics to engage with industry.Peer Reviewe

How to create productive partnerships with universities

Too often, companies pursue collaboration with university researchers in an ad hoc, piecemeal manner. But by giving more thought to the relationship structure, companies can achieve better results

In good company : the influence of peers on industry engagement by academic scientists

Recent research has explored behavioral peer group influences on academics’ engagement with industry, but has not explicitly addressed under which circumstances these influences are more pronounced. Analyzing multi-source data for 1200 UK academic scientists and engineers, we find that peers’ behavior shape individual engagement behavior, yet the effect of social learning is stronger for individuals in the early stage of their career, while it is weaker for star scientists and academics who have worked in industry in the past. While peer effects appear to be strong, we find no organization-level effects. We explore implications for research on professional organizations and policies designed to encourage academics to engage with industry

In good company : the influence of peers on industry engagement by academic scientists

Previous research on academic entrepreneurship and engagement with industry has found that the behaviour of academics is influenced by their local social context. However, we know little about the mechanisms that produce this effect. We argue that academic scientists’ industry engagement is influenced significantly by the behaviour of their peers, that is, the behaviour of colleagues of similar seniority. Using insights from social psychology, we hypothesize that these peer effects are produced by the mechanism of social comparison. In an analysis of data from multiple sources for 1370 UK academic scientists and engineers, we find that peer effects are stronger for early career individuals and weaker for star scientists, suggesting the incidence of social comparison. We argue that individuals look to their immediate peers for inspiration, because they view them as an important reference group and use them as a benchmark for their own ambitions and behaviours. Our findings have important implications for how universities may encourage scientists’ behaviours by paying attention to local work contexts