Шматко Наталья Анатольевна
Институт статистических исследований и экономики знаний
Профессиональные интересы
Должности
- Главный научный сотрудник — Институт статистических исследований и экономики знаний
- Заведующий отделом — Институт статистических исследований и экономики знаний
Био
- · Начала работать в НИУ ВШЭ в 2009 году.
- · Научно-педагогический стаж: 44 года.
Образование
- 1986 · Кандидат философских наук: Институт социологии АН СССР
- 1978 · Специалитет: Московский государственный университет им. М.В. Ломоносова, факультет: психологии, специальность «Психология», квалификация «Психолог. Преподаватель психологии»
Награды и поощрения
- · Благодарственное письмо проректора НИУ ВШЭ (февраль 2024)
- · Почетная грамота Министерства науки и высшего образования Российской Федерации (декабрь 2022)
- · Медаль 10 лет (декабрь 2021)
- · Благодарность Высшей школы экономики (декабрь 2013)
- · Надбавка за публикацию в международном рецензируемом научном издании (2022–2023, 2021–2022, 2020–2022, 2018–2020)
- · Надбавка за статью в зарубежном рецензируемом журнале (2015–2017)
Гранты и проекты
- — · на соискание учёной степени кандидата наук
Конференции (7)
Показать все
- · 2020: XXI Апрельская международная научная конференция по проблемам развития экономики и общества (Москва). Доклад: Цифровые навыки кандидатов и докторов наук в России: уровень владения и заинтересованность в улучшении
- · 2019: 14th annual conference of the Society for Higher Education Research (Магдебург). Доклад: The Value of PhD in the Changing World of Work: traditional and alternative research career
- · 2018: XIX Апрельская международная научная конференция по проблемам развития экономики и общества (Москва). Доклад: Востребованные и перспективные компетенции в области робототехники в эпоху цифровой экономики
- · 2015: Professions, Bonds and Boundaries Visioning a globalising, managed and inclusive professionalism Milano, 19th - 21st March 2015 (Milan). Доклад: Researcher's competencies for future knowledge-intensive labour market
- · 2014: Инженеры будущего - 2014 (Уфа). Доклад: Какие компетенции нужны современным инженерам
- · 2013: Четвертая Всероссийская научно-практическая конференция «Принципы и механизмы формирования национальной инновационной системы в Российской Федерации» (Дубна). Доклад: Форсайт профессиональных компетенций: что должен знать и уметь современный инженер
- · 2012: Второй международный молодежный промышленный форум «Инженеры будущего 2012». Доклад: Знать и уметь: какие компетенции нужны инженеру?
Идентификаторы исследователя
- ORCID:
0000-0001-5369-0752 - ResearcherID:
J-9666-2012 - SPIN РИНЦ:
5411-4887 - Google Scholar: https://scholar.google.ru/citations?hl=ru&user=cIp4hnsAAAAJ&view_op=list_works
- Scopus AuthorID:
6507223957
Публикации (68)
Bridging skill gap in robotics: global and national environment
2020 · ARTICLE · en
This article focuses on the demand for skills of highly qualified scientific and technical professionals (engineers and researchers) in robotics, on both a global and national level. Information is collected using the text-mining of open-access vacancies for understanding the global trends and in-depth interviews with experts for a more detailed study of national trends. The study explores the combination of hard and soft skills, as well as interdisciplinary skills. Soft skill requirements play an important role in the demanded skill set of the specialist, but the claims for hard skills (including digital) are not becoming less strict. Programming and the knowledge of specialized software packages are the most important skills, but must be combined with practical skills (assembly, welding, soldering). The broad range of application areas for robotic systems creates demand for new multidisciplinary skills (knowledge of artificial intelligence, new materials, and biology). Rapid technological development underlines the growing importance of soft skills, such as communication skills, self-motivation, and a willingness to learn. Lists of the most demanded skills in different countries principally coincide. Results can be applied for developing policies aimed at eliminating the skill gap in prospective technological areas.
Skill-Sets for Prospective Careers of Highly Qualified Labor
2020 · CHAPTER · en
Until recently, the career prospects of engineers and researchers have changed considerably. The chances of getting a permanent job, of getting a good position at a university or research center depend not only on one’s academic degree but also on individuals’ experience, competencies, and portfolio. Skills received during the period of study at the university or dissertation research can no longer be considered as sufficient for career. Lifelong learning is becoming the dominant model and should become an integral part of all career plans by means of constantly updating and developing the individuals’ “portfolio of competencies.” At the same time, successful companies should focus not on the staff but on the organizational stock skills, i.e., the aggregate “portfolio of competencies” of employees with different professions, which allows the company to formulate for specific tasks and projects different sets of competencies required in each specific case. The chapter analyzes the most in-demand and dynamically changing sets of competencies in two high-tech areas – robotics and biotechnology.
Integrating professional and academic knowledge: the link between researchers skills and innovation culture
2019 · ARTICLE · en
Approaches to innovation have been thoroughly studied in the last decades. It’s well understood that an organizations’ culture is among the crucial factors for success and renewal of organizations. Yet culture is made by people and their attitudes. Innovation culture requires skills and competence by employees which are presumably beyond the traditional basic knowledge taught at undergraduate, graduate and post graduate level. This is even more evident for university graduates who’re mainly finding professional careers in the private sector who has special requirements to employees. Graduates’ skills are strongly influenced by curricula and the cultural values and norms outside curricula transferred by universities to students. But frequently these skills are designed by universities without profound knowledge of the actual skills required. At the same time organizations acting as potential graduates employers value researcher skills and competencies differently from how these are perceived. The paper suggests that understanding the professional and universal skills of researchers perceived and needed is one element of innovation culture. Thereby the skills in discussion go beyond purely academic skills only; instead it is proposed that skills which increase the absorptive capacity of companies are crucial for implementing effective productive innovation management.
Что такое цифровая экономика? Тренды, компетенции, измерение: докл. к XX Апр. междунар. науч. конф. по проблемам развития экономики и общества, Москва, 9–12 апр. 2019 г.
2019 · CHAPTER · ru
В докладе, подготовленном коллективом Института статистических исследований и экономики знаний (ИСИЭЗ) НИУ ВШЭ, представлены ключевые аспекты развития цифровой экономики — тренды развития цифровых технологий, изменения под их влиянием условий жизни человека, цифровизация государственного управления и сферы науки, трансформация рынка труда и спроса на компетенции кадров. Рассмотрены международные и российские практики государственной поддержки развития цифровой экономики. Впервые представлены оригинальные подходы к статистическому измерению цифровой экономики, экспериментальные расчеты объема и структуры затрат на ее развитие в России, оценки вклада цифровой экономики в экономический рост.
Компетенции XXI века в финансовом секторе: перспективы радикальной трансформации профессий
2019 · ARTICLE · ru
В статье рассматривается влияние прорывных технологических направлений, таких как искусственный интеллект, большие данные, интернет вещей, блокчейн, на традиционные профессии и функции сотрудников банков. Выводы основаны на обширной информации, полученной в ходе исследования кадров высшей квалификации в 2017-2018 гг. и включающей результаты текст-майнинга, анализа кейсов и экспертных интервью. Оценка изменений требований к кадрам и компетенциям учитывала текущий уровень развития технологий (включая наличие реализованных проектов по внедрению продуктов и сервисов в зарубежных и российских компаниях) и вероятность замещения отдельных функций в рамках профессий автоматизированными решениями в среднесрочной перспективе. Результаты исследования показывают, что влияние технологий на функциональные блоки банковской организации неоднородно. Большинство рассмотренных профессий трансформируются в направлении расширения набора выполняемых функций, однако некоторые профессии попадают в категорию «умирающих». В ближайшие годы весь функционал по сбору и первичному анализу данных возьмут на себя автоматизированные системы, но они не заменят полностью сотрудников банков, поскольку выступают в роли вспомогательных инструментов для повышения эффективности и результативности специалистов, расширения информационной базы, ускорения процессов принятия решений, сокращения расходов, снижения рисков.
Comparing the topological rank of journals in Web of Science and Mendeley
2019 · ARTICLE · en
Recently, there has been a surge of interest in new data emerged due to the rapid development of the information technologies in scholarly communication. Since the 2010s, altmetrics has become a common trend in scientometric research. However, researchers have not treated in much detail the question of the probability distributions underlying these new data. The principal objective of this study was to investigate one of the classic problems of scientometrics—the problem of citation and readership distributions. The study is based on the data obtained from two information systems: Web of Science and Mendeley. Here we based on the concept of the cumulative empirical distribution function to explore the differences and similarities between citations and readership counts of biological journals indexed in Web of Science and Mendeley. The basic idea was to determine, for any journal, a “size” (it is said to be the topological rank) of citation and readership empirical cumulative distributions, and then to compare distributions of the topological ranks of Web of Science and Mendeley. In order to verify our model, we employ it to the bibliometric and altmetric research of 305biological journals indexed in Journal Citation Reports 2015. The findings show that both distributions of the topological rank of biological journals are statistically close to the Wakeby distribution. The findings presented in this study add to our understanding of information processes of the scholarly communication in the new digital environment.
Атлас профессий будущего
2019 · BOOK · ru
Книга представляет результаты исследования, посвященного выявлению наиболее перспективных профессий высокой квалификации. Профессии отбирались исходя из прогнозных оценок спроса на них, глобальных трендов научно-технологического развития, динамики изменений российского и мирового рынков труда. По каждой профессии приведены основные функции и задачи специалистов; необходимые знания и навыки; драйверы, барьеры и динамика роста спроса на рынке труда; магистерские программы Национального исследовательского университета «Высшая школа экономики» (НИУ ВШЭ), на которых ведется соответствующая подготовка. Исследование выполнено с использованием системы интеллектуального анализа больших данных iFORA, разработанной специалистами Института статистических исследований и экономики знаний (ИСИЭЗ) НИУ ВШЭ. Книга предназначена для абитуриентов и студентов, желающих получить востребованные в будущем знания и навыки; работодателей, заинтересованных в найме высококвалифицированных специалистов; преподавателей, исследователей и всех тех, кто следит за современным рынком труда и тенденциями его развития.
Willingness of Russian Researchers to Digital Transformation: Basic Digital Literacy and Advanced Skills
2019 · CHAPTER · en
The development of information technologies and rapid growth in the volume of accumulated data makes it necessary to develop new scientific approaches, technologies and methods for collecting, processing and storing information. Digitalization has significantly affected people employed in science and technology: the ability to work with large amounts of information, the knowledge of statistics, and the ability to correctly publish research results became crucially important. For researchers the possession of digital skills signifies the confident use of new data analysis tools and implementation of new technologies. Research practices and competencies of Russian doctorate holders are examined within the framework of the project “Monitoring survey of Highly Qualified R&D Personnel” (National Research University Higher School of Economics, 2010-2019). One of the objectives of the project was to assess the readiness of Russian researchers for digital transformation and to found out to what extent modern digital technologies have taken over the activities of Russian Doctorate holders. It was analyzed whether Russian scientists are familiar with modern digital terminology, whether they apply modern data processing tools in practice and whether they are ready to improve own digital skills. The sample included the total of 2061 Russian Doctorate holders, representing all fields of science, and employed in the academic sector (research institutes and universities), as well as in industrial and service sector companies. The professional activity of most Russian Doctorate holders is associated with the regular use of information technologies. Among the surveyed PhD holders, 85% reported that they regularly use computers and the Internet, another 10% use them periodically. But scientific work involves not only basic computer skills, but also advanced data analysis tools. Our results show that less than half of Russian Doctorate holders are aware of modern digital technologies, except for Big Data Analysis. Moreover, a number of digital tools and technologies are well-known, but have not yet found widespread practical application. The “digital outlook” can come from the general erudition of the Doctorate holder or from the practical experience of using various digital tools: researchers can be clearly divided into “abstractly informed” and “practitioners”. Employees of research institutes, who are more aware of the meaning of digital terminology, use new digital technologies much less frequently than their colleagues from universities and the non-academic sector. A similar situation is observed when comparing age groups: while the youngest scientists are more often aware of the meaning of digital terms, middle-aged and older scientists, if they know the digital technologies, also quite often use them in practice. Every third Doctorate holder in Russia at least occasionally uses Big Data analysis, every fourth – Data Mining, User interface design, Cloud and distributed computing, every fifth – Text Mining, Machine Learning, Applied Mathematical Optimization. The use of particular digital technologies varies according to the type of organization: User Interface Design is more often practiced outside the academic sector, while Big Data Analysis and Machine Learning are more actively used by Doctorate holders employed in research institutes and universities. The biggest number of employees who deal with Mobile Application Development appeared in the research Institutes. The most advanced digital users are those who specialized in natural sciences, engineering sciences, social sciences, and mathematics; PhD holders in agriculture are the least informed. A significant part of Russian scientists already have experience in improving their digital skills by taking part in various computer courses. Over the last 3 years, every fifth Doctorate holder (18.9%) attended computer courses. However, emphasizing digital skills, it is important not to forget about the importance of soft and hard skills, that employers expect from researchers.
Twenty-First Century Skills in Finance: Prospects for a Profound Job Transformation
2019 · ARTICLE · en
This paper analyzes the impact of breakthrough technological areas, such as artificial intelligence (AI), big data, the internet of things, and blockchain upon on conventional banking professions and skill sets. Our conclusions are based upon a large array of data collected over the course of a survey of top personnel conducted in 2017-2018 using text mining, case studies, and expert interviews. The changing requirements for workers and their competences were assessed taking into account the level of technological development (including use of relevant products and services by Russian and international companies) as well as the probability of certain professional skills being substituted by automated solutions in the medium term. The results indicate that technologies’ impact upon various functional segments of banks’ operations is varied. While most of the analyzed professions are evolving towards broader functionality, others are sliding into the “obsolete” group. In the next few years, automated systems will take full responsibility for data collection and its initial analysis, though they will not replace bank personnel fully given that they simply remain tools that help boost workers’ productivity and efficiency, extend the information base, accelerate decision-making, cut costs, and reduce risks.
The distinction machine: Physics journals from the perspective of the Kolmogorov–Smirnov statistic
2019 · ARTICLE · en
An informal notion of distinction between scholarly journals is deeply embedded in bibliometric practice. Distinctions can be viewed as an operationalization of statistical relationships between journals. Bibliometric distinction can be regarded as a relative concept parameterized by the Kolmogorov--Smirnov statistic used as a basis for determining similarity or difference of journals. Within this framework, a systematic study of the probability distribution of distinctions makes it easier to understand the structure of the current scholarly communication. Using the Wakeby distribution, we propose a statistical description of the ``distinction machine'' at the core of the journals' diversity. In this paper, empirical research is based on a dataset of 230 physics journals indexed in Scopus in 2010 to 2015. The ranking of physics journals is obtained by computing the stationary probabilities in terms of Markov chain using transition probabilities derived from the distinction distribution. We perform a clustering of the physics journals according to a similarity that represents the statistical indistinguishability between the journals. This study could help practitioners to make decisions based on a deep understanding of the structure of scholarly communication.
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