Constructing female entrepreneurship policy in the UK : is the US a relevant benchmark?

Successive UK governments have introduced a range of policy initiatives designed to encourage more women to start new firms. Underpinning these policies has been an explicit ambition for the UK to achieve similar participation rates as those in the US where it is widely reported that women own nearly half the stock of businesses. The data underlying these objectives are critically evaluated and it is argued that the definitions and measures of female enterprise used in the UK and the US restrict meaningful comparisons between the two. It is suggested that the expansion of female entrepreneurship in the US is historically and culturally specific to that country. UK policy goals should reflect the national socioeconomic context, while drawing upon good practice examples from a range of other countries. The paper concludes by discussing the economic and social viability of encouraging more women in the UK to enter self-employment without fully recognising the intensely competitive sectors in which they are often located

ChemBank: a small-molecule screening and cheminformatics resource database

ChemBank (http://chembank.broad.harvard.edu/) is a public, web-based informatics environment developed through a collaboration between the Chemical Biology Program and Platform at the Broad Institute of Harvard and MIT. This knowledge environment includes freely available data derived from small molecules and small-molecule screens and resources for studying these data. ChemBank is unique among small-molecule databases in its dedication to the storage of raw screening data, its rigorous definition of screening experiments in terms of statistical hypothesis testing, and its metadata-based organization of screening experiments into projects involving collections of related assays. ChemBank stores an increasingly varied set of measurements derived from cells and other biological assay systems treated with small molecules. Analysis tools are available and are continuously being developed that allow the relationships between small molecules, cell measurements, and cell states to be studied. Currently, ChemBank stores information on hundreds of thousands of small molecules and hundreds of biomedically relevant assays that have been performed at the Broad Institute by collaborators from the worldwide research community. The goal of ChemBank is to provide life scientists unfettered access to biomedically relevant data and tools heretofore available primarily in the private sector

Classificatory Theory in Data-Intensive Science: The Case of Open Biomedical Ontologies

publication-status: Publishedtypes: ArticleThis is the author's version of a paper that was subsequently published in International Studies in the Philosophy of Science. Please cite the published version by following the DOI link.Knowledge-making practices in biology are being strongly affected by the availability of data on an unprecedented scale, the insistence on systemic approaches and growing reliance on bioinformatics and digital infrastructures. What role does theory play within data-intensive science, and what does that tell us about scientific theories in general? To answer these questions, I focus on Open Biomedical Ontologies, digital classification tools that have become crucial to sharing results across research contexts in the biological and biomedical sciences, and argue that they constitute an example of classificatory theory. This form of theorizing emerges from classification practices in conjunction with experimental know-how and expresses the knowledge underpinning the analysis and interpretation of data disseminated online.Economic and Social Research Council (ESRC)The British AcademyLeverhulme Trus

The Roles of Standardization, Certification and Assurance Services in Global Commerce

In this article we examine the rapid emergence and expansion of standardized product and process frameworks and a private-sector compliance and enforcement infrastructure that we believe may increasingly be providing a substitute for public and legal regulatory infrastructure in global commerce. This infrastructure is provided by a proliferation of performance codes and standards, many of which define acceptable social and environmental behavior, and a rapidly-growing number of privately-trained and authorized inspectors and certifiers that we call the third-party assurance industry. We offer reasons for this development, evidence of its scope and scale, and then describe the phenomenon in more detail by examining supply chain arrangements in two industries, food products and apparel, where the use of third-party standards and assurance services has expanded especially rapidly. We conclude with a discussion of the implications for the make or buy decision at the core of the theory of the firm. We argue that as quasi-regulatory standards are developed within various industries, and as performance to these standards can be systematically evaluated using third-party inspectors and certifiers, the costs of moving production outside of vertical firm hierarchies drop. We believe this may be an important factor in accelerating the shift to outsourcing that has been observed over the last two decades

GOBLET: the Global Organisation for Bioinformatics Learning, Education and Training

In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy--paradoxically, many are actually closing "niche" bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all

GOBLET: The Global Organisation for Bioinformatics Learning, Education and Training

In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy—paradoxically, many are actually closing “niche” bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all

Top-Level Categories of Constitutively Organized Material Entities - Suggestions for a Formal Top-Level Ontology

Application oriented ontologies are important for reliably communicating and managing data in databases. Unfortunately, they often differ in the definitions they use and thus do not live up to their potential. This problem can be reduced when using a standardized and ontologically consistent template for the top-level categories from a top-level formal foundational ontology. This would support ontological consistency within application oriented ontologies and compatibility between them. The Basic Formal Ontology (BFO) is such a foundational ontology for the biomedical domain that has been developed following the single inheritance policy. It provides the top-level template within the Open Biological and Biomedical Ontologies Foundry. If it wants to live up to its expected role, its three top-level categories of material entity (i.e., 'object', 'fiat object part', 'object aggregate') must be exhaustive, i.e. every concrete material entity must instantiate exactly one of them.By systematically evaluating all possible basic configurations of material building blocks we show that BFO's top-level categories of material entity are not exhaustive. We provide examples from biology and everyday life that demonstrate the necessity for two additional categories: 'fiat object part aggregate' and 'object with fiat object part aggregate'. By distinguishing topological coherence, topological adherence, and metric proximity we furthermore provide a differentiation of clusters and groups as two distinct subcategories for each of the three categories of material entity aggregates, resulting in six additional subcategories of material entity.We suggest extending BFO to incorporate two additional categories of material entity as well as two subcategories for each of the three categories of material entity aggregates. With these additions, BFO would exhaustively cover all top-level types of material entity that application oriented ontologies may use as templates. Our result, however, depends on the premise that all material entities are organized according to a constitutive granularity

Correction to: Health-related qualify of life, angina type and coronary artery disease in patients with stable chest pain

The original article [1] contained an error in coauthor, Balazs Ruzsics’s name which has since been corrected

Health-related qualify of life, angina type and coronary artery disease in patients with stable chest pain

Background: Health-related quality of life (HRQoL) is impaired in patients with stable angina but patients often present with other forms of chest pain. The aim of this study was to compare the pre-diagnostic HRQoL in patients with suspected coronary artery disease (CAD) according to angina type, gender, and presence of obstructive CAD. Methods: From the pilot study for the European DISCHARGE trial, we analysed data from 24 sites including 1263 patients (45.9% women, 61.1 ± 11.3 years) who were clinically referred for invasive coronary angiography (ICA; 617 patients) or coronary computed tomography angiography (CTA; 646 patients). Prior to the procedures, patients completed HRQoL questionnaires: the Short Form (SF)-12v2, the EuroQoL (EQ-5D-3 L) and the Hospital Anxiety and Depression Scale. Results: Fifty-five percent of ICA and 35% of CTA patients had typical angina, 23 and 33% had atypical angina, 18 and 28% had non-anginal chest discomfort and 5 and 5% had other chest discomfort, respectively. Patients with typical angina had the poorest physical functioning compared to the other angina groups (SF-12 physical component score; 41.2 ± 8.8, 43.3 ± 9.1, 46.2 ± 9.0, 46.4 ± 11.4, respectively, all age and gender-adjusted p < 0.01), and highest anxiety levels (8.3 ± 4.1, 7.5 ± 4.1, 6.5 ± 4.0, 4.7 ± 4.5, respectively, all adjusted p < 0.01). On all other measures, patients with typical or atypical angina had lower HRQoL compared to the two other groups (all adjusted p < 0.05). HRQoL did not differ between patients with and without obstructive CAD while women had worse HRQoL compared with men, irrespective of age and angina type. Conclusions: Prior to a diagnostic procedure for stable chest pain, HRQoL is associated with chest pain characteristics, but not with obstructive CAD, and is significantly lower in women. Trial registration: Clinicaltrials.gov, NCT02400229