Different differences: the use of 'genetic ancestry' versus race in biomedical human genetic research

This article presents findings from our ethnographic research on biomedical scientists' studies of human genetic variation and common complex disease. We examine the socio-material work involved in genome-wide association studies (GWAS) and discuss whether, how, and when notions of race and ethnicity are or are not used. We analyze how researchers produce simultaneously different kinds of populations and population differences. Although many geneticists use race in their analyses, we find some who have invented a statistical genetics method and associated software that they use specifically to avoid using categories of race in their genetic analysis. Their method allows them to operationalize their concept of 'genetic ancestry' without resorting to notions of race and ethnicity. We focus on the construction and implementation of the software's algorithms, and discuss the consequences and implications of the software technology for debates and policies around the use of race in genetics research. We also demonstrate that the production and use of their method involves a dynamic and fluid assemblage of actors in various disciplines responding to disciplinary and sociopolitical contexts and concerns. This assemblage also includes particular discourses on human history and geography as they become entangled with research on genetic markers and disease.We introduce the concept of'genome geography' to analyze how some researchers studying human genetic variation'locate' stretches of DNA in different places and times. The concept of genetic ancestry and the practice of genome geography rely on old discourses, but they also incorporate new technologies, infrastructures, and political and scientific commitments. Some of these new technologies provide opportunities to change some of our institutional and cultural forms and frames around notions of difference and similarity. Nevertheless, we also highlight the slipperiness of genome geography and the tenacity of race and race concepts.     

How the Role of Computing is Driving New Genetics' Public Policy

In this paper we will examine some ethical aspects of the role that computers and computing increasingly play in new genetics. Our claim is that there is no new genetics without computer science. Computer science is important for the new genetics on two levels: (1) from a theoretical perspective, and (2) from the point of view of geneticists practice. With respect to (1), the new genetics is fully impregnate with concepts that are basic for computer science. Regarding (2), recent developments in the Human Genome Project (HGP) have shown that computers shape the practices of molecular genetics; an important example is the Shotgun Method's contribution to accelerating the mapping of the human genome. A new challenge to the HGP is provided by the Open Source Philosophy (I computer science), which is another way computer technologies now influence the shaping of public policy debates involving genomics.     

After the fall: Political whitewashing, professional posturing, and personal refashioning in the postwar career of Otmar Freiherr von Verschuer

Despite the numerous books and articles preoccupied with the formidable legitimizing role and unethical medical transgressions of the German human geneticist Otmar von Verschuer (1896-1969) during the Third Reich, scholars have neglected to focus on his career trajectory during the postwar period, especially in the years after he received the first chair of genetics on German soil in 1951. While an examination of von Verschuer's trials, tribulations, and ultimate triumph in post-1945 West Germany is fascinating in its own right, it also raises broader historical issues. First, it lays bare the professional posturing of German biomedical scientists as they attempted to retake control over their once tainted fields of research when Cold War realities opened a window of opportunity for them. Second, it reveals the fine line between adherence to professional ethics and disciplinary solidarity when scientists were faced with a potential outside threat to their profession. Finally, such an analysis demonstrates the macromechanics of professional refashioning on the part of the publicly tainted scientists as they forged a new symbiosis between their field and the politics of a new era in the interest of pursuing research.     

A survey on evaluation of summarization methods

The increasing volume of textual information on any topic requires its compression to allow humans to digest it. This implies detecting the most important information and condensing it. These challenges have led to new developments in the area of Natural Language Processing (NLP) and Information Retrieval (IR) such as narrative summarization and evaluation methodologies for narrative extraction. Despite some progress over recent years with several solutions for information extraction and text summarization, the problems of generating consistent narrative summaries and evaluating them are still unresolved. With regard to evaluation, manual assessment is expensive, subjective and not applicable in real time or to large collections. Moreover, it does not provide re-usable benchmarks. Nevertheless, commonly used metrics for summary evaluation still imply substantial human effort since they require a comparison of candidate summaries with a set of reference summaries. The contributions of this paper are three-fold. First, we provide a comprehensive overview of existing metrics for summary evaluation. We discuss several limitations of existing frameworks for summary evaluation. Second, we introduce an automatic framework for the evaluation of metrics that does not require any human annotation. Finally, we evaluate the existing assessment metrics on a Wikipedia data set and a collection of scientific articles using this framework. Our findings show that the majority of existing metrics based on vocabulary overlap are not suitable for assessment based on comparison with a full text and we discuss this outcome.     

Narrative research in climate change adaptation—Exploring a complementary paradigm for research and governance

Climate adaptation research increasingly focuses on the socio-cultural dimensions of change. In this context, narrative research is often seen as a qualitative social science method used to frame adaptation communication. However, this perspective neglects an important insight provided by narrative theory as applied in the cognitive sciences and other practical fields: human cognition is organized around specific narrative structures. In adaptation, this means that how we ‘story’ the environment determines how we understand and practice adaptation, how risks are defined, who is authorized as actors in the change debate, and the range of policy options considered. Furthermore, relating an experience through story-telling is already doing ‘knowledge work’, or learning. In taking narrative beyond its use as an extractive social research methodology, we argue that narrative research offers an innovative, holistic approach to a better understanding of socio-ecological systems and the improved, participatory design of local adaptation policies. Beyond producing data on local knowledge(s) and socio-cultural and affective-emotive factors influencing adaptive capacity, it can significantly inform public engagement, deliberation and learning strategies–features of systemic adaptive governance. We critically discuss narrative as both a self-reflective methodology and as a paradigmatic shift in future adaptation research and practice. We explore the narrative approach as a basis for participatory learning in the governance of socio-ecological systems. Finally, we assemble arguments for investing in alternative governance approaches consistent with a shift to a ‘narrative paradigm’.     

Content still matters. A machine learning model for predicting news longevity from textual and context features

There is an ongoing debate about what is more important in the modern online media newsroom, whether it is the news content and worthiness, or the audience clicks. Using a dataset of over one million articles from five countries (Belarus, Kazakhstan, Poland, Russia, and Ukraine) and a novel machine learning methodology, I demonstrate that the content of news articles has a significant impact on their lifespan. My findings show that articles with positive sentiment tend to be displayed longer, and that high fear emotion scores can extend the lifespan of news articles in autocratic regimes, and the impact is substantial in magnitude. This paper proposes four new methods for improving information management methodology: a flexible version of Latent Dirichlet Allocation (LDA), a technique for performing relative sentiment analysis, a method for determining semantic similarity between a news article and a newspaper's dominant narrative, and a novel approach to unsupervised model validation based on inter-feature consistency.     

Implicit dimension identification in user-generated text with LSTM networks

In the process of online storytelling, individual users create and consume highly diverse content that contains a great deal of implicit beliefs and not plainly expressed narrative. It is hard to manually detect these implicit beliefs, intentions and moral foundations of the writers.We study and investigate two different tasks, each of which reflect the difficulty of detecting an implicit user’s knowledge, intent or belief that may be based on writer’s moral foundation: (1) political perspective detection in news articles (2) identification of informational vs. conversational questions in community question answering (CQA) archives. In both tasks we first describe new interesting annotated datasets and make the datasets publicly available. Second, we compare various classification algorithms, and show the differences in their performance on both tasks. Third, in political perspective detection task we utilize a narrative representation language of local press to identify perspective differences between presumably neutral American and British press.     

Is the commercialisation of scientific research affecting the production of public knowledge?: Global trends in the output of corporate research articles

Judging by the large R&D-active companies that have slimmed down their research labs in recent years, it would seem that corporate research is increasingly managed as an economic asset that is predominantly driven by market forces and ruled by IPR strategies. Has this development significantly affected industry’s basic research and interactions with research communities in the public sector? This paper examines the global trends in an underdeveloped source of information on corporate science: their research articles published in the international scientific and technical journals.Statistical analysis of some 290,000 corporate research articles published in 1996-2001 indicate that, contrary to large increases in patenting and growth in patent citations to research literature, the numbers of research articles that list author affiliate addresses in the corporate sector have declined steadily, especially for those articles authored exclusively by industrial researchers. More detailed analysis of trends in the bio-pharmaceuticals sector and semiconductors sector show sector-specific publication trends and patterns related to specifics of their innovation processes.Overall, these observations provide factual evidence indicating that corporate research is in an on-going process of structural change characterised by a stronger emphasis on the appropriation and commercialisation of in-house research results.     

The impact of downsizing on trust and employee practices in high tech firms: A longitudinal analysis

The literature on trust and human resource management (HRM) indicates that these elements play an important role during periods of downsizing. In addition, researchers acknowledge that downsizing, when it occurs, is usually an industry-wide phenomenon, which gives these elements extra clout. However, the influence of managers' trust in their employees on HRM practices in the high tech industry has yet to be empirically tested. The organizations included in this research were selected from a sample of 114 organizations taken from the Israeli High Tech Guide. In the first and second waves, 43 and 34, respectively, of the 114 designated companies completed our questionnaires, resulting in a response rate of 38% and 30%, respectively. Findings indicate that trust exerted a direct effect on HRM practices and organizational performance. Possible explanations of the findings, as well as their practical implications, are discussed.     

Implicit aspect extraction in sentiment analysis: Review,taxonomy, oppportunities,and open challenges

Sentiment analysis is a text classification branch, which is defined as the process of extracting sentiment terms (i.e. feature/aspect, or opinion) and determining their opinion semantic orientation. At aspect level, aspect extraction is the core task for sentiment analysis which can either be implicit or explicit aspects. The growth of sentiment analysis has resulted in the emergence of various techniques for both explicit and implicit aspect extraction. However, majority of the research attempts targeted explicit aspect extraction, which indicates that there is a lack of research on implicit aspect extraction. This research provides a review of implicit aspect/features extraction techniques from different perspectives. The first perspective is making a comparison analysis for the techniques available for implicit term extraction with a brief summary of each technique. The second perspective is classifying and comparing the performance, datasets, language used, and shortcomings of the available techniques. In this study, over 50 articles have been reviewed, however, only 45 articles on implicit aspect extraction that span from 2005 to 2016 were analyzed and discussed. Majority of the researchers on implicit aspects extraction rely heavily on unsupervised methods in their research, which makes about 64% of the 45 articles, followed by supervised methods of about 27%, and lastly semi-supervised of 9%. In addition, 25 articles conducted the research work solely on product reviews, and 5 articles conducted their research work using product reviews jointly with other types of data, which makes product review datasets the most frequently used data type compared to other types. Furthermore, research on implicit aspect features extraction has focused on English and Chinese languages compared to other languages. Finally, this review also provides recommendations for future research directions and open problems.     

Germs in space. Joshua Lederberg,exobiology, and the public imagination, 1958-1964

Under the leadership of Joshua Lederberg, some American biologists and chemists proposed exobiology as the most legitimate program for space research. These scientists used the fear of contamination--of earth and other planets--as a central argument for funding "nonpolitical," "scientifically valid" experiments in extraterrestrial life detection. Exobiology's resemblance to popular science fiction narratives presented a significant challenge to its advocates' scientific authority. Its most practical applications, moreover, bore an unseemly resemblance to the United States Army's research on biological weapons. At the same time that exobiologists wanted to use the media to attract support for their program, they had to monitor their statements carefully in order to maintain their view of exobiology as a peaceful, scientifically valid research program. In examining how exobiology's creators positioned their work in comparison to other space sciences as well as science fiction, this case study highlights how cultural and political imperatives entered science through practice and narrative during the Cold War.     

Career-based influences on scientific recognition in the United States and Europe: Longitudinal evidence from curriculum vitae data

This paper examines how funding patterns, career pathways and collaboration networks influence scientific recognition. We analyze these institutional factors in the early and middle phases of academic careers through comparison of a group of researchers recognized as creative by their peers with a matched group of researchers. Measurement of scientific recognition is based on survey nominations and research prizes in two growing, laboratory-intensive research domains: nanotechnology and human genetics. Curriculum vitae data is used to compare researchers based in the United States and Europe. In the early career model for the United States, we find that scientific recognition is associated with broad academic education, fast completion of PhD, and a record of independent postdoctoral research, while in Europe these factors are much less prominent. The mid-career model suggests that both in the United States and Europe fast job promotion within academia is a strong predictor of future recognition. However, there is a clear divide across the Atlantic regarding other mid-career factors: work experience inside and outside academia, research leadership, external grant income, and prizes from professional associations are connected to scientific recognition in the United States, but are less influential in Europe.     

高被引科学家论文产出力的年龄分析

摘要：采用科学计量学的方法分别对分子生物学与遗传学和物理学两个领域高被引科学家发表论文的生理年龄进行了分析,考虑科学家发表论文的合作者因素,分别采用平均计数法和调节计数法计算其发表的论文数量,揭示出两个领域高被引科学家发表论文的年龄分布是三次多项式模型,高峰期集中在40-55岁（即中年时期）;本文还进一步对老年高被引科学家群体以及科学家个体发表论文的情况进行了观察和分析。     

基于Altmetric Top 100的中国科学论文多维特征分析

[目的/意义]为了推动中国学者学术论文的国际影响力,有利于国内学者在发表国际论文时有更好的选择依据。[方法/过程]以2013—2019年Altmetric Top 100中国科学论文为研究样本,通过对其Altmetrics数据和传统计量数据进行统计,分析研究其特征。[结果/结论]论文聚焦于医学、生物和社会研究等学科,主要由中国科学院和国内985高校(双一流)研究完成,与欧美发达国家合作较多,主要发表于非付费获取方式的高影响因子国际期刊,一般由社会公众在Twitter上讨论与传播,其Altmetrics评分与被引频次的相关性极弱。     

An assessment of knowledge growth stages in organizations

This paper examines the stages of knowledge growth in 50 companies through a qualitative research study that asked employees to identify where their organization ranks along Bohn's eight-stage scale ranging from complete ignorance to complete knowledge. Participants were also asked to identify their competitors ranking and the ideal stage of knowledge to which their company should strive. The results found that companies today rank on the Bohn scale between stage three (the measure stage) where knowledge is typically written and stage four (control of the mean) where knowledge is written and embodied in hardware. Respondents also stated that their companies were perceived as usually slightly ahead of their competitors, but not nearly at the ideal level that they believe their organizations should achieve. Recommendations are made for further qualitative and empirical research regarding the stages of knowledge growth at organizations, and how organizations can support movement toward complete knowledge.     

Research in information science: An assessment

A critical analysis of research methods in the published literature in the field of information science. Report on the results of the comparison made between a set of 430 articles published 1969–1971 and another set of 152 articles published in 1974. Overall findings indicate that while the amount of research reported is remaining stable, the methods have improved somewhat in 1974, as compared to earlier years.     

How and why accelerators enhance female entrepreneurship

This study was driven by an initial finding that female founders' participation rate in Israeli accelerators is significantly higher (15.3 %) than their participation rate in the Israeli startup sector (7.4 %). Linking accelerators' design to the known barriers to female entrepreneurship, we examined how accelerators may enhance female entrepreneurship by addressing their specific needs. Based on a dataset (N = 779) of structured interviews with startup founders who participated in accelerator programs in Israel during 2011–2019, we present evidence that female founders seek and gain more entrepreneurial knowledge, network building, and entrepreneurial self-efficacy during their participation in accelerators than do male founders. Female founders also seek to increase their legitimacy more than do their male counterparts but did not report making more progress in this aspect. Finally, both the goal of and progress in obtaining access to capital and improving fundraising skills received lower ratings from female founders than from male founders. We further ask whether accelerators are more helpful for women because they are better adapted to the female gender or because they are generally better adapted to founders with those background conditions that often characterize women. We found that the startup's stage of development and the founder's prior entrepreneurial experience mediated most gender differences, supporting the latter possibility. We discuss the implications of our findings for accelerators and other support programs as a means of increasing women's participation rates in innovative entrepreneurship.     

从国际顶级期刊的论文发表看广东省基础研究的水平与影响力

本文统计了2003-2012年广东省大学、科研机构和企业在国际顶级期刊Science和Nature上发表的论文明细,并对论文的数量分布、论文发表机构、论文研究领域等进行了分析。剖析了广东省在基础研究领域的优势和特点,提出了4点提高广东省基础研究的水平和影响力的建议和对策。     

文化地理学研究方法及学科影响

文化地理学是人文地理学的一个分支学科,经过近90年的发展,逐步形成了稳定的学科研究框架及研究方法。本文基于对新旧文化地理学的教科书、经典著作、代表性文章的初步归纳,梳理出了有关文化地理学的4个方面内容：第一,文化地理学的核心概念为“文化区”和“地方”;第二,围绕核心概念,文化地理学的研究框架可分为两部分：文化区和地方的形成机制研究以及文化区和地方的尺度间转换研究：第三,针对形成机制和尺度转换的研究,文化地理学分别有不同的研究方法论;第四．文化地理学核心概念可以为其他人文地理学分支提供学术支撑。     

Standing on the shoulders of giants: How star scientists influence their coauthors

We examine whether and when star scientist collaborations produce indirect peer effects. We theorize that a star's social status causes a collaboration to act as a prism; it reduces quality uncertainty, leading to increased recognition of coauthors' ideas. We identify two moderators of prisms, other scientists' quality uncertainty and awareness of the collaboration, and link prisms to “sleeping beauties”, articles that are initially overlooked and then rediscovered later. Empirically, we examine the effect on citations of collaborating with a star who either won, or – serving as the control group – who was nominated for but did not win, the Nobel Prize in Physics. We find that articles by the winners' coauthors (and which were published prior to the focal coauthor's first collaboration with the winner) receive a citation boost after the Nobel Prize is awarded, relative to articles by the coauthors of nominees, and that awareness and quality uncertainty moderate this effect. We further find that this difference in citations causes sleeping beauties written by the coauthors of Nobel Prize winners to be rediscovered faster. Our results clarify how star scientists' indirect peer effects impact their coauthors and, through sleeping beauties, how prisms matter for science more broadly.