Hasil untuk "Industrial sociology. Social conditions of labor"

Gonzague Isirabahenda

In recent years, Romania's higher education landscape and labor market have undergone significant changes due to demographic factors, modernization, economic progress, and globalization. One notable transformation is the internationalization of higher education, which requires universities to align their curricula with labor market demands. Additionally, Romania has experienced growth in the service industry and increased involvement from multinational companies. However, little is known about the employment experiences of young people in the early years following graduation. This is particularly concerning given the significant rise in the number of university graduates occupying positions that do not match their educational qualifications or skill levels and those working in non-graduate professions. This study addressed this gap by using ethnographic case study data to analyze the experiences of young university graduates working as customer support representatives (CSRs). Informed by the social constructivism paradigm, data were collected through participatory observation, semi-structured interviews, and field notes and analyzed using a reflexive thematic analysis strategy. The results challenge employers' claims of a lack of skills among young university graduates, emphasizing the need for a broader range of skills in the recruitment process and workplace. This study highlights the growing patterns of precarity affecting underemployed young Romanian graduates. The findings suggest that digital technologies used by outsourced companies deskill and diminish the dignity of CSR work, while work productivity strategies, measurement, and corporate working conditions create uncertainty in CSRs' career prospects. Furthermore, it underscores that non-collaboration remains a significant issue in Romanian work culture, complicating the education-job mismatch. By shedding light on the university-to-work phenomenon and the value of higher education in the Romanian labor market, this study contributes to the sociology of work and employment by revealing that post-university trajectories are considerably diverse and necessitate further qualitative investigation beyond the educational outcomes typically discussed in the context of graduate employability.

Maxence Morin, Baptiste Hemery, Fabrice Jeanne et al.

Social network analysis is pivotal for organizations aiming to leverage the vast amounts of data generated from user interactions on social media and other digital platforms. These interactions often reveal complex social structures, such as tightly-knit groups based on common interests, which are crucial for enhancing service personalization or fraud detection. Traditional methods like community detection and graph matching, while useful, often fall short of accurately identifying specific groups of users. This paper introduces a novel framework specifically designed to identify groups of users within transactional graphs by focusing on the contextual and structural nuances that define these groups.

Alina Nikolaevna Tsygankova

The article examines in detail the problem of labor instability in Russia and its impact on the social and economic situation of workers. Job insecurity includes aspects such as temporary contracts, low job security, underemployment, and lack of social guarantees. Various forms of unstable employment relationships are also being explored, such as short-term contracts, part-time employment, seasonal work, and work with free schedules. The scale of the problem in different sectors of the economy and its consequences are assessed, including a deterioration in the quality of life of workers, a decrease in income levels, limited access to medical services and pension provision. Important attention is paid to the social consequences of job insecurity, such as rising inequality, poverty, and social tension. The work uses methods of statistical analysis and sociological research, which are aimed at identifying and evaluating factors that affect the level of job insecurity. These methods include processing quantitative data such as the unemployment rate, staff turnover, as well as qualitative research based on surveys and interviews with employees. In recent years, there has been a significant trend in employment instability, which is caused by various factors such as economic crises, the pandemic, industrial automation and globalization. These processes lead to an increase in the number of temporary, partial, and low-paying jobs, as well as an increase in the number of workers facing job loss risks. Due to the instability of labor relations, many employees cannot count on long-term employment, stable income or social guarantees, which creates additional tension in society. Based on the analysis of the current situation, it is important to develop effective government measures aimed at reducing the level of instability in the labor market. An important step is also to strengthen the social protection of workers, especially in crisis situations, through the expansion of insurance programs, professional development and retraining, as well as improving conditions for workers in areas with high instability. Such an integrated approach will create a more stable and secure work environment, which will contribute to social and economic well-being.

A. Nurbatsin

This research investigates how territorial and sociodemographic conditions influence household financial provision roles in Kazakhstan. Based on a nationally representative interview survey, the research uses hierarchical clustering and count-model statistical analysis to analyze distributional patterns of financial assignment, whether husband, wife, both, or others by age group, marital status, sector of employment, and territorial location. The findings reveal marked heterogeneity in household economic roles, testifying to the interplay of labor market structure, cultural norms, and levels of regional development. Young and middle-aged respondents report tradition and shared financial arrangements, whereas older and divorced respondents report female-headed and other household support. Urban areas demonstrate greater heterogeneity than rural and peripheral areas, with potential impacts attributable to processes of modernization and access to institutions. Sector of employment is also heavily involved in financial distribution patterns, testifying also to labor market segmentation and participation impacts on intrahousehold relations. In general, the research testifies to financial provision roles as determined neither solely by personal choice nor independent of personal agency and personal tastes and preferences. Instead, financial provision roles are strongly embedded in higher-order sociodemographic and territorial conditions. The research suggests a need for social and economic policies targeted by region to acknowledge heterogeneities of household form and changing dimensions of gendered financial roles within and from contemporary urban and industrial contexts such as Kazakhstan.

Julian Maj, Maksym Nowakivskyi

The full-scale Russian invasion of Ukraine in 2022 has profoundly affected the geopolitical and socio-economic landscape of Central and Eastern Europe, with Poland positioned at the center of regional transformation processes. As Ukraine’s largest neighbor on the western border and one of the most active supporters of Ukrainian sovereignty, Poland became a key transit, humanitarian, logistical, and political platform in the context of the war. These unprecedented circumstances significantly influenced Poland’s economic dynamics, labor market structure, public finances, foreign policy orientation, and internal political debates. The inflow of millions of Ukrainian refugees, changes in trade and energy routes, the reorientation of supply chains, and heightened security concerns reshaped national priorities and intensified cooperation within Euro-Atlantic institutions. Therefore, examining the multifaceted consequences of the war on Poland is essential for understanding the country’s strategic development under conditions of prolonged regional instability. The aim of the study is to analyze the economic and political implications of the war in Ukraine for Poland, identify structural shifts in national policies, evaluate the impact on macroeconomic performance and electoral preferences, and define long-term strategic consequences for regional stability and integration processes within the European Union and NATO. The study is based on a multidisciplinary methodological approach combining political analysis, economic evaluation, and comparative research. Statistical data from the Polish Central Statistical Office (GUS), Eurostat, and the World Bank are used to assess changes in GDP growth rates, inflation, employment, and public spending. Political developments are examined through content analysis of governmental statements, parliamentary debates, and policy documents. Comparative analysis with other EU member states helps contextualize Poland’s position within broader European responses to the war. The research also incorporates secondary sources from think tanks specializing in security studies, migration policy, and energy diversification. The findings demonstrate that the war has had both stabilizing and destabilizing effects on Poland’s economy and political environment. Economically, the arrival of more than one million Ukrainian refugees boosted labor supply, particularly in sectors with structural shortages, contributing to sustained employment levels and partially mitigating demographic decline. At the same time, increased public spending on humanitarian aid, military support, and social integration programs placed additional pressure on the national budget. Inflation accelerated due to disruptions in energy markets, although Poland’s rapid diversification away from Russian gas strengthened long-term energy security. Politically, the war deepened Poland’s role as a regional security leader and enhanced its standing within NATO and the EU. Support for Ukraine became a central element of foreign policy, strengthening ties with the United States and aligning Poland more closely with security-oriented EU members. Domestically, however, political discourse intensified, with parties differing on migration policy, defense expenditures, and the scope of state support for Ukrainian citizens. The war also influenced public opinion, increasing societal polarization regarding foreign policy priorities, economic burdens, and identity-related issues. The war in Ukraine significantly transformed Poland’s economic structure, labor dynamics, energy strategy, and political landscape. While short-term economic pressure and political polarization present challenges, long-term benefits include strengthened regional leadership, enhanced security cooperation, and a more diversified economic base. Poland’s strategic importance within Europe has increased, positioning the country as a critical actor in shaping the future architecture of regional security. Future research should focus on long-term labor market integration of Ukrainian migrants, the fiscal sustainability of support programs, and the evolution of Poland’s political alliances in the EU. Another important direction is assessing the impact of defense sector expansion on industrial modernization and economic growth.

N. Potapova

The purpose of the article is to study the traditional phenomenon of seasonal migration from the Russian villages, namely the temporary departure of rural residents from their permanent homes for work. In the 1920s and the first half of the 1930s, it underwent transformation aimed at establishing state control over labor migration, particularly from the village, and organizing the supply of workers to industry. The study shows that throughout the 1920s, the Soviet government attempted to limit the spontaneous movement of the rural population, seeing it as a reason for rising unemployment and worsening socio-economic conditions in cities. To combat unregulated movements within the country and to evenly provide the industry with labor, the state implemented a system of economic recruitment. However, by the late 1920s to 1930s, unemployment was replaced by a “staff shortage”, and the demand for labor first exceeded supply. This shift required the authorities to introduce new measures to ensure the growing industry had enough workforce. Therefore, before the beginning of the passportization campaign, two channels for hiring workforce from the village remained economic recruitment and seasonal migration, but for peasants who signed contracts with economic authorities, agricultural benefits were introduced to attract them to participate in the seasonal migration. Concurrently, due to the policy pursued by the Bolsheviks in the villages and the onset of famine, the problem of mass outflow of population from villages worsened. This led to disruptions in commodity supply, intensifying the housing crisis, and leading to an increase in criminal activity in cities. Administrative documentation often classified such migrants were also referred to as seasonal migrants, although they were not related to labor migration. In the context of the flight of peasants, the government took measures aimed at keeping village residents in the villages and socially cleansing cities by introducing passports - a kind of filter whose possession granted the right to reside in cities, especially in restricted areas. New documents were not issued to rural residents, which limited their mobility across the country. Now, to leave the village, a peasant was required to provide documents confirming their intention to engage in “socially useful labor” in production, institutions, schools; documents of this kind included a job invitation, a recruitment contract, a certificate from the collective farm's administration about the departure, etc. The introduction of the passport system effectively transformed seasonal migration from a spontaneous labor migration into a system of organized supply for the industrial sector, while mass movement from the village was prohibited under the threat of administrative and repressive measures against violators of the new regime.

Dídimo Castillo Fernández

In this article, the theoretical perspective centered on “dynamic inequality” and inter-category or individual differences is questioned, while the structural approach of extra-categorical analysis is sustained as essential and pertinent to sociological discussions of inequality and, further, attributable to social class, rather than internal or individual differences as posited by some theorists of inequality. From this position, an attempt is made to offer a frame of reference for the analysis and understanding the distributive structure of income in contemporary Panama. Despite presenting one of the best positioned minimum wage and average income structures in Latin America, Panama occupies one of the worst income distributions in the region. The approach subscribed to in this investigation is based on the theoretical assumption that links the conditions of income inequality with the structures of occupation and class location of the workers. The purpose is to build an empirical model of class structures associated with the occupational categories of the workers and, from this, to analyze the trends in the distribution of income in the country. The data analysis was carried out based on the Labor Market Survey of the National Institute of Statistics and Census of the Comptroller General of the Republic for 2000 and 2021.

The industrial safety of health and medical workers who struggling on the front lines of diseases and disasters to protect public health and life, is threatened by working environment hazard factors that damage health. Despite they are exposing to hazard factors and accumulating mental well-being risks frequently, the social discussions and national efforts for their health were insufficient due to complacent perceptions that “They would be safe from occupational diseases and industrial accidents because of the working environment characteristic that set as medical work”. Korean society needs to enhance the importance of industrial safety because if the mental well-being risk of health and medical workers is not healed in proper time, the deterioration of work engagement can harm personal health and patient life and threat public health and cause a national crisis. Therefore, this study analyzed occupational safety hazard factors that hinder health and medical worker's mental well-being focusing on doctor, nurse, medical technician based on Rutter's ‘Cumulated Risk Model’ that explaining the more accumulate of exposure to simultaneous risk factors, the greater ripple effect of human's internalization and externalization problem. The multiple regression analysis were performed with SPSS Statistics 29.0 for 749 health and medical workers who attended the 6th Korean Working Conditions Survey published by the Korea Occupational Safety and Health Research. As a result, the health and medical worker's mental well-being were hindered whey they exposure to occupational safety hazard factors, emotional labor and quantitative labor intensity were finally verified as occupational safety hazard factors that threatened the mental well-being of them. Based on the results, this study suggested ① services and policies to effectively counter occupational safety hazard factors that hinder the health and medical worker's mental well-being, ② prevention and solution plan about exposure problem to occupational safety hazard factors, ③ customized strategies to promote health and medical workers' mental well-being.

Keno Moenck, Duc Trung Thieu, Julian Koch et al.

In recent years, the upstream of Large Language Models (LLM) has also encouraged the computer vision community to work on substantial multimodal datasets and train models on a scale in a self-/semi-supervised manner, resulting in Vision Foundation Models (VFM), as, e.g., Contrastive Language-Image Pre-training (CLIP). The models generalize well and perform outstandingly on everyday objects or scenes, even on downstream tasks, tasks the model has not been trained on, while the application in specialized domains, as in an industrial context, is still an open research question. Here, fine-tuning the models or transfer learning on domain-specific data is unavoidable when objecting to adequate performance. In this work, we, on the one hand, introduce a pipeline to generate the Industrial Language-Image Dataset (ILID) based on web-crawled data; on the other hand, we demonstrate effective self-supervised transfer learning and discussing downstream tasks after training on the cheaply acquired ILID, which does not necessitate human labeling or intervention. With the proposed approach, we contribute by transferring approaches from state-of-the-art research around foundation models, transfer learning strategies, and applications to the industrial domain.

Simindokht Jahangard, Zhixi Cai, Shiki Wen et al.

Understanding human social behaviour is crucial in computer vision and robotics. Micro-level observations like individual actions fall short, necessitating a comprehensive approach that considers individual behaviour, intra-group dynamics, and social group levels for a thorough understanding. To address dataset limitations, this paper introduces JRDB-Social, an extension of JRDB. Designed to fill gaps in human understanding across diverse indoor and outdoor social contexts, JRDB-Social provides annotations at three levels: individual attributes, intra-group interactions, and social group context. This dataset aims to enhance our grasp of human social dynamics for robotic applications. Utilizing the recent cutting-edge multi-modal large language models, we evaluated our benchmark to explore their capacity to decipher social human behaviour.

Jose A. Garcia Gutierrez

The analysis of social media information has undergone significant evolution in the last decade due to advancements in artificial intelligence (AI) and machine learning (ML). This paper provides an overview of the state-of-the-art techniques in social media mining, with a practical application in analyzing trends in the 2024 French legislative elections. We leverage natural language processing (NLP) tools to gauge public opinion by extracting and analyzing comments and reactions from the AgoraVox platform. The study reveals that the National Rally party, led by Marine Le Pen, maintains a high level of engagement on social media, outperforming traditional parties. This trend is corroborated by user interactions, indicating a strong digital presence. The results highlight the utility of advanced AI models, such as transformers and large language models (LLMs), in capturing nuanced public sentiments and predicting political leanings, demonstrating their potential in real-time reputation management and crisis response.

S. E. Kaidarova, G. Baibash, N. Abdildinova et al.

State management of the region's image plays a key role in the strategic development of territories. The image of a region is formed under the influence of many factors, including economic indicators, social conditions, environmental conditions, cultural heritage and information policy. In this article, the object of research is the Pavlodar region, considered from the point of view of image formation. The factors of political influence and mechanisms of information support that contribute to the creation of a positive image and increase in the investment attractiveness of the region are analyzed. The Pavlodar region has significant natural resources and developed industrial and transport infrastructure, which creates the basis for economic growth. In order to leverage these advantages, it is necessary to target image management focused on long-term strategies. focused on long-term strategies. The conducted sociological survey revealed the strengths and weaknesses of the region. The authors determined that the image of a region is influenced by various factors, including natural resources, development of economic infrastructure, cultural heritage and quality of life of the population. The activities of government agencies aimed at strengthening and promoting a positive image of the region play an important role. Comprehensive strategies aimed at developing tourism and investment attractiveness, improving the urban environment, supporting local entrepreneurship and strengthening social infrastructure ensure the formation of a sustainable, favourable image and increasing the region's competitiveness in the international arena. In the context of the digital transformation of the economy of Kazakhstan, in order to improve the image of the region, the authors propose optimizing the branding and positioning of the region, which requires the use of modern models and approaches, such as: digital integration, omnichannel, sustainable positioning, brand ecosystem, interactivity. These approaches help adapt branding to new digital conditions and strengthen the presence of the region in the national and international arenas.

Orel Beilinson

Nearly a century after Bernard Lewis’ seminal article, much about craft guilds in Islamic societies remains unknown. Even less is known about journeymen, a stratum of hired workers who were neither apprentices nor master craftsmen. European thought and historiography—especially Marxism, under whose influence much of the works on guilds were written—ascribed to them an essential role in the history of labor and politics. In the Middle East, it is unclear whether such a position existed, when it emerged, whether it was imported, and under what conditions. When journeymen do seem to appear in the sources, it is still difficult to say whether they matched their Western European equivalents in conditions, demographics, aspirations, and political potential. These questions are crucial for comparing guilds, social structures, and life courses across time and space. At the heart of this dossier are six texts, which are also reproduced here in translation. These sources—a contemporary description and five works of historical scholarship written in Arabic, Serbian, Russian, Albanian, and Georgian—remain fundamental studies of guilds in the Middle East, the Caucasus, and Central Asia. The translations thus provide access to non-Anglophone scholarship. The accompanying article analyzes the historiography and puts these sources under scrutiny. It shows the limitations of imposing European models on Islamic guilds, including misinterpretations. Analyzing and contextualizing these interpretations reveals dynamics worth exploring, raises new questions, and revives old debates abandoned prematurely. These include the relationship between religious and craft associations, the management of young and mobile men, and the logic of industrial development in Europe, the Islamic World, and beyond.

S. Yekimov, S. Kontsevaya, Anastasiya S. Poltorak et al.

The formation of agro-industrial clusters makes it possible to increase the competitiveness of agricultural regions. Agricultural clusters allow increasing food production, as well as creating an integrated, geographically localized structure that includes the entire chain involved in the production of agricultural products, starting from the sale and maintenance of agricultural machinery and ending with the storage and processing of crops. The agro-industrial cluster allows the dissemination of innovations among the enterprises participating in this cluster. Within the framework of the agricultural cluster, favorable conditions are created for the exchange of experience and knowledge, which contributes to the creation and implementation of new technologies and ideas. Agricultural clusters can be in demand by private investors, as well as attract skilled labor from other sectors of the economy. Agricultural clusters help the development of ecosystems in agricultural regions. These ecosystems include agricultural producers, research centers, universities and food industry enterprises. Successful agricultural clusters can contribute to the development of green tourism in the region. The creation of agricultural clusters contributes to the development of regional social infrastructure, provides conditions for the sustainable development of the region, improves the standard of living of the population, which makes it possible to reduce migration flows to other regions.

Liam Hebert, Gaurav Sahu, Yuxuan Guo et al.

We present the Multi-Modal Discussion Transformer (mDT), a novel methodfor detecting hate speech in online social networks such as Reddit discussions. In contrast to traditional comment-only methods, our approach to labelling a comment as hate speech involves a holistic analysis of text and images grounded in the discussion context. This is done by leveraging graph transformers to capture the contextual relationships in the discussion surrounding a comment and grounding the interwoven fusion layers that combine text and image embeddings instead of processing modalities separately. To evaluate our work, we present a new dataset, HatefulDiscussions, comprising complete multi-modal discussions from multiple online communities on Reddit. We compare the performance of our model to baselines that only process individual comments and conduct extensive ablation studies.

Xiangguo Sun, Hong Cheng, Bo Liu et al.

Modern sociology has profoundly uncovered many convincing social criteria for behavioural analysis. Unfortunately, many of them are too subjective to be measured and presented in online social networks. On the other hand, data mining techniques can better find data patterns but many of them leave behind unnatural understanding. In this paper, we propose a fundamental methodology to support the further fusion of data mining techniques and sociological behavioral criteria. Our highlights are three-fold: First, we propose an effective hypergraph awareness and a fast line graph construction framework. The hypergraph can more profoundly indicate the interactions between individuals and their environments because each edge in the hypergraph (a.k.a hyperedge) contains more than two nodes, which is perfect to describe social environments. A line graph treats each social environment as a super node with the underlying influence between different environments. In this way, we go beyond traditional pair-wise relations and explore richer patterns under various sociological criteria; Second, we propose a novel hypergraph-based neural network to learn social influence flowing from users to users, users to environments, environment to users, and environments to environments. The neural network can be learned via a task-free method, making our model very flexible to support various data mining tasks and sociological analysis; Third, we propose both qualitative and quantitive solutions to effectively evaluate the most common sociological criteria like social conformity, social equivalence, environmental evolving and social polarization. Our extensive experiments show that our framework can better support both data mining tasks for online user behaviours and sociological analysis.

Preslav Nakov, Firoj Alam, Yifan Zhang et al.

Fighting the ongoing COVID-19 infodemic has been declared as one of the most important focus areas by the World Health Organization since the onset of the COVID-19 pandemic. While the information that is consumed and disseminated consists of promoting fake cures, rumors, and conspiracy theories to spreading xenophobia and panic, at the same time there is information (e.g., containing advice, promoting cure) that can help different stakeholders such as policy-makers. Social media platforms enable the infodemic and there has been an effort to curate the content on such platforms, analyze and debunk them. While a majority of the research efforts consider one or two aspects (e.g., detecting factuality) of such information, in this study we focus on a multifaceted approach, including an API,\url{https://app.swaggerhub.com/apis/yifan2019/Tanbih/0.8.0/} and a demo system,\url{https://covid19.tanbih.org}, which we made freely and publicly available. We believe that this will facilitate researchers and different stakeholders. A screencast of the API services and demo is available.\url{https://youtu.be/zhbcSvxEKMk}

Dilara Keküllüoğlu, Walid Magdy, Kami Vaniea

Date of birth (DOB) has historically been considered as private information and safe to use for authentication, but recent years have seen a shift towards wide public sharing. In this work we characterize how modern social media users are approaching the sharing of birthday wishes publicly online. Over 45 days, we collected over 2.8M tweets wishing happy birthday to 724K Twitter accounts. For 50K accounts, their age was likely mentioned revealing their DOB, and 10% were protected accounts. Our findings show that the majority of both public and protected accounts seem to be accepting of their birthdays and DOB being revealed online by their friends even when they do not have it listed on their profiles. We further complemented our findings through a survey to measure awareness of DOB disclosure issues and how people think about sharing different types of birthday-related information. Our analysis shows that giving birthday wishes to others online is considered a celebration and many users are quite comfortable with it. This view matches the trend also seen in security where the use of DOB in authentication process is no longer considered best practice.

I. Denisenko, A. Kuzubov, N. Shashlo

Introduction. In 2021 the labor market takes on a new format. Under the influence of various factors, a new social and labor platform “Trud” is being formed. The COVID-19 virus pandemic has dealt a devastating blow to the economy and the world of work in all countries and in the world in particular, causing triple consequences for eco­nomic growth - a supply shock, a demand shock, and an international trade shock. Three main phe­nomena of our time - demography - XXI, globaliza­tion - XXI and "Industry 4.0" have changed and continue to radically change the world of econom­ics, institutions and the world of society [18]. Digi­talization, virtualization of the economy, its hybrid nature, the emergence of various modifications - platform economy, on-demand economy, general consumption economy, gig economy - transform not only the social and labor space [19]. Changes are taking place in the entire social structure of the economy and society, the classic lines between pro­ducers and consumers, workers and employers are being erased; the former polarity of relations and interdependence between the owners of labor and owners of capital is changing. Thus, the social stra­tum of the new digital economy and network socie­ty is acquiring the character of non-classical, atypi­cal, dynamic and unstable forms. The whole system of social and labor relations in the labor market is becoming the same. In the short term, in the econ­omy and society as a whole, under the influence of information and communication and other break­through technologies, the growth of the availability of digital infrastructure, certain changes will occur in the labor market, in this connection, the article highlights groups of technologies that will signifi­cantly affect it: cognitive technologies, cloud tech­nologies, artificial intelligence, industrial Internet, Internet of things, Big Date, blockchain, quantum technologies, neurotechnologies, virtual reality technologies. It has been proven that technologies have already rapidly entered human life, radically changing the conditions of life, motivational at­titudes, and the value of forming the competitive­ness of labor resources. Thus, the transformations taking place in the social and labor sphere under the influence of information and communication technologies, network systems, other resources and institutions of the new digital economy are a com­plete, comprehensive transformation of values, mo­tivational attitudes, hierarchies, sources of develop­ment, resource structure, forms and technologies. interaction, forms and scale of employment, level, structure, income differentiation.Materials and methods. The study was car­ried out on the basis of the following methodologi­cal framework, namely: an integrated approach, a systematic approach, methods of comparative, situational analysis and synthesis, a method of abstract-logical assessment, a method of concre­tization, methods of detailing, typology, grouping, systematization and generalization, induction and deduction, methods of statistical analysis, graphi­cal method.Research results. As a result of the study, an assessment was made of the potential for intra-in­dustry polarization, taking into account the use of information and communication technologies (here­inafter - ICT). It has been proven that information and communication technologies replace individual tasks that are performed by people; respectively, in the market the share of highly qualified experts as well as low-skilled service personnel will increase.The proportion of workers who used ICT in their activities is identified. It was determined that in Russia the maximum number of workers who used ICT in their professional activities were employed in the fields of information and telecommunica­tions, as well as scientific and technical activities. Indicators of the share of workers who used ICTs that were close to the average for Russia were noted in industry, the minimum use of ICTs was in the field of transport, warehousing, postal and courier activities, in the field of water supply. As a result, this made it possible to identify a number of enter­prises with the maximum potential for introducing the latest breakthrough technologies and for refor­matting the structure of the employed population.Discussion and conclusion. The role of the skills and competencies of workers necessary for the formation of competitive labor resources and over­coming various challenges in the labor market is revealed. A core of skills and competencies for effec­tive employment is proposed based on the O*NET content model. It has been proved that promoting the development of non-routine skills is the most relevant strategy for the formation of the competi­tiveness of labor resources in the context of digital and post-viral trends in the transformation of so­ciety. Non-routine social skills related to employee interpersonal interactions and social perception are complemented by ICT applications, with the aim of empowering human capabilities with technology.

Yiding Cao, Yingjun Dong, Minjun Kim et al.

Collective idea generation and innovation processes are complex and dynamic, involving a large amount of qualitative narrative information that is difficult to monitor, analyze, and visualize using traditional methods. In this study, we developed three new visualization methods for collective idea generation and innovation processes and applied them to data from online social network experiments. The first visualization is the Idea Cloud, which helps monitor collective idea posting activity and intuitively tracks idea clustering and transition. The second visualization is the Idea Geography, which helps understand how the idea space and its utility landscape are structured and how collaboration was performed in that space. The third visualization is the Idea Network, which connects idea dynamics with the social structure of the people who generated them, displaying how social influence among neighbors may have affected collaborative activities and where innovative ideas arose and spread in the social network.