Abstract:This article deconstructs some of the allegedly positive features of the Fordist era by analyzing postwar Italy from a gender perspective. In the Italian case, the Fordist factory became a paradigmatic image of Italian modernity in the years of the economic miracle, disregarding the diversity of the industrial system and the diversity of labor relations and working conditions, supposedly characterized by the prevalence of stable, full-time, permanent employment. However, job stability was never fully achieved for women in the so-called golden age of the twentieth century. This article analyzes the social and working conditions of women in postwar Italy as a way of addressing the concept and reality of Fordism. It also examines the agency of women trade unionists and parliamentarians, and the role of women's associations in unraveling the gender-blind policy debates on full employment. Finally, the article focuses on the role that women workers, along with women's associations and trade unions, played in gendering social services by passing key legislation between the 1960s and 1970s.
Celeste Campos-Castillo, Xuan Kang, Linnea I. Laestadius
Recently, research into chatbots (also known as conversational agents, AI agents, voice assistants), which are computer applications using artificial intelligence to mimic human-like conversation, has grown sharply. Despite this growth, sociology lags other disciplines (including computer science, medicine, psychology, and communication) in publishing about chatbots. We suggest sociology can advance understanding of human-chatbot interaction and offer four sociological theories to enhance extant work in this field. The first two theories (resource substitution theory, power-dependence theory) add new insights to existing models of the drivers of chatbot use, which overlook sociological concerns about how social structure (e.g., systemic discrimination, the uneven distribution of resources within networks) inclines individuals to use chatbots, including problematic levels of emotional dependency on chatbots. The second two theories (affect control theory, fundamental cause of disease theory) help inform the development of chatbot-driven interventions that minimize safety risks and enhance equity by leveraging sociological insights into how chatbot outputs could attend to cultural contexts (e.g., affective norms) to promote wellbeing and enhance communities (e.g., opportunities for civic participation). We discuss the value of applying sociological theories for advancing theorizing about human-chatbot interaction and developing chatbots for social good.
Purpose: The subject of this work is the study of the use of passive exoskeletons in industrial enterprises. The topic of the work is focused on the analysis of the role of passive exoskeletons as a transitional stage to full robotization of production processes. The purpose of the study is to assess the impact of the introduction of passive exoskeletons on labor productivity, worker safety and economic efficiency of enterprises. Methods: The research methodology includes the collection and analysis of technical data from public sources, as well as directly from internal reports of organizations, on productivity and safety at Russian and foreign enterprises where passive exoskeletons are already used. Results: Foreign experience shows that the use of exoskeletons can reduce the risk of musculoskeletal diseases by 45–58%, reduce the cost of disability compensation by 31-53% and increase labor productivity up to 153% for certain tasks. In Russia, the process of introducing exoskeletons is at an early stage, but there are already successful examples of their use at enterprises that have shown a 13% reduction in task completion time. An expert assessment of the effectiveness of the introduction of exoskeletons confirmed their high social and economic significance. Practical significance: The introduction of exoskeletons in industrial enterprises helps to reduce injuries, improve working conditions and increase productivity, which is especially important in the context of personnel shortages. The use of exoskeletons allows to reduce costs for disability compensation and increase the prestige of the company among potential employees. The article offers recommendations for Russian enterprises on the introduction of exoskeletons, which can contribute to the implementation of tasks set within the framework of national projects and increase the competitiveness of the domestic industry. The introduction of exoskeletons can be an important step towards full automation and robotization of processes. The conclusions emphasize that passive exoskeletons are an effective tool for increasing productivity and labor safety.
This article considers the managerial aspect of digital transformation - various programs and infrastructure that have recently received the general name “algorithmic management”. The boom in the use of such tools occurred during the covid-19 pandemic as a unique set of circumstances for the digitalization of human life. The authorities of several countries monitored their citizens’ behavior, including with the QR-code systems that limited their rights, in the fight against the spread of the covid-19, which has caused discussions and even protests. Businesses accelerated their digital transformation in HR management due to government restrictions and lockdown measures and to production needs in the new conditions. Quarantines are over, but the active development of algorithmic management continues; it extends beyond the platform economy and plays an integral role in Industry 4.0, which makes the study of algorithmic management relevant and timely. A significant contribution to understanding algorithmic management was made by the report of the experts from the European Commission and International Labor Organization. Based on the relevant publications up to 2022, they suggested giving up the narrow understanding of algorithmic management as a platform economy issue; however, most studies are still based on this interpretation. The article presents a broader definition to identify additional social contradictions and challenges of digital transformation. The author considers algorithmic management in the perspective of sociology of management and sociology of technology, in particular the works of A. Feenberg and P. Edwards. The approach of sociology of technologies studies (STS) allowed the author not only to analyze the events of the recent pandemic but also to consider the future of such technologies under the transition towards Industry 4.0. The article identifies three elements of algorithmic management together with hidden social-managerial biases and contradictions related to their implementation and shows how the new approach integrates direct and indirect control in management.
Modern economic processes, with their dynamism, complexity, and unpredictability, often surpass the explanatory power of traditional economic theories. These theories, while valuable, can be insufficient in understanding the behavior of business entities and predicting future trends. This inadequacy underscores the growing relevance of behavioral economics, which integrates the achievements of psychology, cognitive sciences, and sociology into economic analysis. Behavioral economics studies how psychological factors, such as emotions, cognitive biases, social norms, and personal values, influence economic decision-making. It reveals that people do not always act rationally, as assumed in classical economic models. Instead, their behavior is often driven by emotional reactions, cognitive limitations, and the influence of the social context. The ongoing transformational shifts, mainly digital transformation, profoundly impact the behavior of business entities and the labor market. Changes in technology, communications, and business organization lead to new forms of employment, new employee requirements, and new consumption patterns. Digital transformation promotes the development of e-commerce, remote work, online education, and other forms of economic activity that change traditional ideas about work, consumption, and human interaction. In this context, traditional management and marketing methods are becoming less effective. Businesses must adapt to new conditions, consider behavioral factors when developing products and services, and use digital tools to interact with customers and partners. Behavioral economics is crucial in understanding and managing economic processes in transformational shifts. It is instrumental in developing more effective economic policies by considering the psychological and social factors influencing human behavior. Further research in the field of behavioral economics is vital for predicting future economic trends and adapting to them. Keywords: digital transformation, behavioral economics, business entities, interdisciplinary approach, economic science.
Francisco de Arriba-Pérez, Silvia García-Méndez, Javier Otero-Mosquera
et al.
New technologies such as Machine Learning (ML) gave great potential for evaluating industry workflows and automatically generating key performance indicators (KPIs). However, despite established standards for measuring the efficiency of industrial machinery, there is no precise equivalent for workers' productivity, which would be highly desirable given the lack of a skilled workforce for the next generation of industry workflows. Therefore, an ML solution combining data from manufacturing processes and workers' performance for that goal is required. Additionally, in recent times intense effort has been devoted to explainable ML approaches that can automatically explain their decisions to a human operator, thus increasing their trustworthiness. We propose to apply explainable ML solutions to differentiate between expert and inexpert workers in industrial workflows, which we validate at a quality assessment industrial workstation. Regarding the methodology used, input data are captured by a manufacturing machine and stored in a NoSQL database. Data are processed to engineer features used in automatic classification and to compute workers' KPIs to predict their level of expertise (with all classification metrics exceeding 90 %). These KPIs, and the relevant features in the decisions are textually explained by natural language expansion on an explainability dashboard. These automatic explanations made it possible to infer knowledge from expert workers for inexpert workers. The latter illustrates the interest of research in self-explainable ML for automatically generating insights to improve productivity in industrial workflows.
Isura Manchanayaka, Zainab Razia Zaidi, Shanika Karunasekera
et al.
The rise of social media has been accompanied by a dark side with the ease of creating fake accounts and disseminating misinformation through coordinated attacks. Existing methods to identify such attacks often rely on thematic similarities or network-based approaches, overlooking the intricate causal relationships that underlie coordinated actions. This work introduces a novel approach for detecting coordinated attacks using Convergent Cross Mapping (CCM), a technique that infers causality from temporal relationships between user activity. We build on the theoretical framework of CCM by incorporating topic modelling as a basis for further optimizing its performance. We apply CCM to real-world data from the infamous IRA attack on US elections, achieving F1 scores up to 75.3% in identifying coordinated accounts. Furthermore, we analyse the output of our model to identify the most influential users in a community. We apply our model to a case study involving COVID-19 anti-vax related discussions on Twitter. Our results demonstrate the effectiveness of our model in uncovering causal structures of coordinated behaviour, offering a promising avenue for mitigating the threat of malicious campaigns on social media platforms.
The present paper posits that female labor force in the Moroccan agricultural sector plays a crucial role in production and provides specific expertise, leading to an increasingly visible feminization of the sector. Taken into consideration their invaluable contributions, the primary objective of this field-based study is to unveil the working conditions that female farm workers endure, including extended working hours, high physical demands, and health risks caused by either climate change or industrial fertilizers. It also seeks to comprehend gender stereotypes that perpetuate these inequalities. Consequently, this study avoids treating this group of women as a homogeneous ensemble. Instead, the purpose is to closely observe female workers and listen to their speeches to gain an insight into their daily experiences. This is achieved through a micro-sociological framework that involves direct observation of female workers on the farms, as well as semistructured interviews. The research findings confirm that female workers encounter gender-based differentiations in the workplace, stigmatizing representations from their surroundings, and restrictions on access to the workplace. Additionally, they are subject to the negative impact of the working environment on their health and well-being.
The article regarding the working conditions of an industrial enterprise describes approaches to rational differentiation of wages taking into account the following: qualifications of jobs and employees; quantitative results of labor; working conditions, which means difficult and special sanitary and hygienic conditions of work processes; the role of an employee (profession) in production, which determines the degree of his influence on the results of collective work on manufacturing of the main production. It is substantiated that increasing production volumes and increasing profit on investments requires constant improvement of wage accounting in case of changes in wage payment systems and wide use of modern computing equipment. It was concluded, that for small-scale production it is advisable to display the corresponding rate of payment together with the performance of various non-repetitive works or operations in the orders. For the brigade form of work, it is advisable to provide the necessary data for calculating earnings and their distribution among the members of the brigade on the reverse page of the order, taking into account the labor participation rate of each member of the brigade, which will contribute to the efficient operation of enterprises in conditions of intense competition. Rationalization of various allowances and payments additional to official salaries, as well as bonuses and rewards, which are systematic, in case of systematic reduction of total costs was performed. The implementation of the electronic form of sick leaves and the electronic register of sick leaves in the employer’s personal account causes the accounting staff to rationalize the “ready for payment” operation. The organization of the technological process of accounting for both sick leaves at the expense of the social insurance fund and additional vacations for liquidators of the consequences of the accident at the Chernobyl Nuclear Power Plant is detailed. The mechanism for regulating inter-job salaries and intra-production tariffs, taking into account the qualifications of an employee, his education, the degree of responsibility for the work performed, initiative, length of service at the given enterprise, and the results of qualification certification of workers was improved. A rational report form has been developed to avoid discrepancies, numerous errors and inaccuracies in the process of accruing and transferring of preferential pensions at the expense of the funds of enterprises and organizations which are paid and delivered by employees of the Pension Fund.
INTRODUCTION: On the basis of competent statistical materials updated in accordance with the All-Russian Classifier of Types of Economic Activity (ARCoToEA 2) and ICD-10, a retrospective analysis of occupational morbidity in different types of economic activity and professional cohorts of the industrial sector of the Saratov region in 20092019 was carried out by generally accepted methods. AIM: This a comprehensive analysis of current trends and trends in the prevalence, dynamics and nosology of occupational morbidity of workers in the industrial sector in the context of types of economic activity on the example of the Saratov region. MATERIALS AND METHODS: The information base of the study was presented by statistical materials of Rosstat, the Rospotrebnadzor Department for the Saratov Region and the Ministry of Labor and Social Protection of the Saratov Region, updated by us in accordance with ARCoToEA 2 (version OK 029-2014). A retrospective epidemiological statistical analysis of occupational morbidity for the period from 2009 to 2019 was carried out. RESULTS: During the analyzed period, the number of people employed in the industrial sector of the regions economy decreased by 17.5% from 380.3 (2009) to 313.7 (2019), while the level of primary occupational morbidity decreased by 2.7 times from 0.68 to 0.25 per 10,000 workers against the background of an increase in the share of workers in harmful working conditions in the extraction of minerals (+27.9 percentage points), in construction (+16.8 percentage points) and manufacturing industries (+11.5 percentage points). The main risk factors for occupational morbidity were physical effects (noise, general and local vibration), pollution of the respiratory zone with industrial aerosols, and the severity of the labor process. The nosological structure of the accumulated occupational morbidity was mainly represented by sensorineural hearing loss (SHL) 48.7%, vibration sickness (VS) 15.4%, radiculopathy 9.6% and chronic dusty non-obstructive bronchitis (CDNB) 7.7%. Workers in manufacturing industries were mainly identified by SHL (32.4%), VS (17.2%), CDNB (12.4%); transport workers SHL (77.2%), radiculopathy (10.9%), VS (7.9%); those employed in oil and gas production SHL (35.7%), VS (28.6%), radiculopathy (17.9%); in construction VS (22.2%), SHL (18.5%), radiculopathy (18.5%). CONCLUSION: The results of the identification of deterministic nosologies of the occupational morbidity, characteristic of certain sectors of the economy and professional cohorts, should form associative diagnostic alertness during regulated medical examinations and serve as a scientific basis for the development of targeted regional programs to promote health in the workplace.
Tech workers -- professional workers in the technology industry including software engineers, product managers, UX designers, etc. -- are not normally associated with labor activism. Yet, since 2017, we have seen a significant rise in labor actions among this group. Using an original dataset, we demonstrate how, in the case of tech workers, periods of intense workplace social activism preceded later periods of heightened labor activism. Regression analysis confirms that participation in social activism increases the likelihood of labor activism six months to one year later at the same company. This finding extends Fantasia's cultures of solidarity argument to professional workers. We find that organizing emerges out of collective action and ensuing conflict with management: first, tech workers, guided by their professional interest in socially beneficial work, engage in workplace social activism. This generates solidarity among employee-participants but also creates conflict with management and leads to the emergence of labor activism among professionals.
The basis of the intensive development of the digital economy is modern technologies for the development of information. At the same time, it is possible to identify many reasons, prerequisites and principles that led to the formation of the digital economy. New technological platforms and infrastructure are being created and a large-scale technological transformation of the digital economy is being carried out. Under the influence of end-to-end technologies, the organizational structures of enterprises that increase the efficiency of the digital economy are being improved. Under these conditions, a neo-industrial system of social division of labor is quickly formed as the basis for the development of the digital economy.
This article has attempted to highlight the importance of child labor, child misery, and social and economic changes in the Age of Industrialization as depicted in the novel Oliver Twist by Charles Dickens (1837–1839). The study utilizes the descriptive qualitative research method to analyze how Dickens portrays helpless children whose childhoods are taken away by harsh reality. “Industrial Revolution” refers to the change from rural and handcrafted lifestyles to an industrialized society built on manufacturing. Poor people moved from the countryside to the cities, where they lived in slums and crowded places due to the Industrial Revolution, negatively affecting their quality of life. During this time, children were excessively labored, working under challenging conditions for minimal pay. In this novel, Charles Dickens denounces how poor children were forced into labor, mistreated, exploited, and denied an education. He also criticized how the capitalist system, based on class distinctions, gave rise to villains who would do anything to stay at the top of their social level. Dickens has depicted the anguish of impoverished children in this novel, who were denied parental love and education while working long hours in unfavorable circumstances. The current study argued that child labor is the fundamental result of the industrial revolution with reference to previous literature and will be helpful for future researchers to get overall idea of later consequences.
The purpose of the article is to study the place and role of occupational standards in providing industry with qualified personnel and to define main tasks and problems of their implementation in Ukraine. Research methods: dialectical, abstract-logical, induction and deduction, analysis and synthesis, analogy and comparisons, system, complex and content analysis. Approaches to the formation of modern industrial policy are analyzed, attention is focused on the main determinants of EU industrial policy - the creation of a favorable environment for the development of small and medium-sized businesses and equal opportunities in conditions of competition, which means the struggle to achieve better conditions of access to limited resources. The role of qualified personnel as the scarcest resource that determines the competitiveness of industry is shown. The problem of the shortage of qualified labor for industry in Ukraine is highlighted, the solution of which requires the creation of conditions for the development of competition and ensuring the training of professional personnel in accordance with the needs of industry, in particular – by modernizing occupational standards of industrial specialties. The place and importance of the implementation of occupational standards in providing industry with qualified personnel, their relationship with the education system and the labor market, and main problems of implementation are defined. It has been proven that employers' decision to introduce occupational standards "affects" the most sensitive foundations of labor relations – employment (the employees’ compliance with the requirements for qualifications, education, etc.), remuneration of labor (rate fixing), conditions and safety of work. Conclusions were made about the need to develop the Methodology for the introduction of occupational standards, the existence of a wide field for the joint activity of social partners on the basis of ensuring the transparency of the transition to occupational standards for employees, the use of existing mechanisms of social dialogue for the participation of personnel, in particular – through the representation of trade unions, in the activities of the working group on the introduction of occupational standards.
The world economy crucially depends on multi-layered value chains with high degrees of sector-related specialization. Its final products are of international character and serve the needs and wants of the global citizen. However, many production processes are causing severe damage to the environment and moreover create health hazard for workers and local populations. This research article focuses on the increasing global unequal economic- and ecological exchange, fundamentally embedded in international trade. Resource extraction and labor conditions in the Global South as well as the implications for climate change originating from industry emissions in the North are investigated with an agent-based model. The model serves as a testbed for simulation experiments with evolutionary political economic policies. An international institution is introduced sanctioning the polluting extractivist sector in the Global South as well as the emitting industrial capital good producers in the North with the aim of subsidizing innovation reducing environmental and social impacts. Both regions are modelled as macroeconomic complex adaptive systems where international trade is restricted to a three-sector value chain, originating from mining resources in the South that are traded to capital good producers in the North crafting machinery which is eventually traded to consumer good firms, both in the North and South. The main outcome of the study is that sanctions alone are not effective in countering unequal exchange. They only make a difference in combination with subsidies for innovation activities, which are protecting labor and reducing local pollution in mines as well as reducing carbon-emissions in capital good production.
As social media sites are penetrating our daily lives in an ever-increasing manner, there is a need to revisit and reexplore the theoretical concepts that have gone through paradigm shifts due to the influence of these platforms. In this regard, audience labor theory, which was originally conceptualized in the context of mass media, needs to be reexamined as the divide between production and consumption is getting narrower. Users are no longer passive consumers since social media sites have reduced the cost of production and resulted in the advent of the term “prosumption.” In such a case, as production involves performing work and results in surplus-value, it needs to be investigated whether users are being exploited for the free work they provide on these platforms. From the several identified forms of digital labor, I will focus on the concept of audience labor. To this end I will focus on identifying labor strategies that Iranian Instagram influencers employ; these strategies involve exploiting their followers to perform tasks that produce fame and visibility as well as monetary gains but leave the users uncompensated for the work they have performed. By conducting content analysis of the 2,130 stories created by 71 Iranian Instagram influencers, this study will identify the strategies that these influencers use to exploit their followers.
Simone Casale-Brunet, Mirko Zichichi, Lee Hutchinson
et al.
This paper presents an analysis of the role of social media, specifically Twitter, in the context of non-fungible tokens, better known as NFTs. Such emerging technology framing the creation and exchange of digital object, started years ago with early projects such as "CryptoPunks" and since early 2021, has received an increasing interest by a community of people creating, buying, selling NFT's and by the media reporting to the general public. In this work it is shown how the landscape of one class of projects, specifically those used as social media profile pictures, has become mainstream with leading projects such as "Bored Ape Yacht Club", "Cool Cats" and "Doodles". This work illustrates how heterogeneous data was collected from the Ethereum blockchain and Twitter and then analysed using algorithms and state-of-art metrics related to graphs. The initial results show that from a social network perspective, the collections of most popular NFTs can be considered as a single community around NFTs. Thus, while each project has its own value and volume of exchange, on a social level all of them are primarily influenced by the evolution of values and trades of "Bored Ape Yacht Club" collection.
Ishita Vohra, Meher Shashwat Nigam, Aryan Sakaria
et al.
The pandemic required efficient allocation of public resources and transforming existing ways of societal functions. To manage any crisis, governments and public health researchers exploit the information available to them in order to make informed decisions, also defined as situational awareness. Gathering situational awareness using social media has been functional to manage epidemics. Previous research focused on using discussions during periods of epidemic crises on social media platforms like Twitter, Reddit, or Facebook and developing NLP techniques to filter out relevant discussions from a huge corpus of messages and posts. Social media usage varies with internet penetration and other socioeconomic factors, which might induce disparity in analyzing discussions across different geographies. However, print media is a ubiquitous information source, irrespective of geography. Further, topics discussed in news articles are already newsworthy, while on social media newsworthiness is a product of techno-social processes. Developing this fundamental difference, we study Twitter data during the second wave in India focused on six high-population cities with varied macroeconomic factors. Through a mixture of qualitative and quantitative methods, we further analyze two Indian newspapers during the same period and compare topics from both Twitter and the newspapers to evaluate situational awareness around the second phase of COVID on each of these platforms. We conclude that factors like internet penetration and GDP in a specific city influence the discourse surrounding situational updates on social media. Thus, augmenting information from newspapers with information extracted from social media would provide a more comprehensive perspective in resource deficit cities.
The study aims to reveal the mechanism and features of attracting German immigrants from the USSR to labor service in Nazi Germany at the final stage of World War II. The research methodology is based on the principles of historicism and objectivity and a set of special and general scientific methods. Scientific novelty. Based on the involvement of an extensive array of archival documents, for the first time in historiography, an attempt was made to comprehensively illuminate the problem of using the labor of German immigrants from the USSR in the economy of the Third Reich. Conclusions. German refugees were taken out by the decision of the Nazi authorities in 1943-1944. from the occupied regions of the USSR to the homeland of their ancestors, in the conditions of declared total war, they naturally became part of the Third Reich's labor resources. Most of them were concentrated in the agricultural and industrial sectors of the economy. At the same time, the bulk immigrants' movement to the territory of Warthegau was caused not by the objective needs of the region for additional labor but by the geopolitical plans of the Nazi leadership. Attempts by some areas of Germany to make up for the acute shortage of human resources in agriculture at the expense of the refugees who arrived were unsuccessful. Their aspirations were shattered by the inert position of Himmler and his inner circle. They did not want to go beyond the concept of using German settlers and the bureaucratic mechanisms associated with it. Only officials who defended the interests of the German military-industrial complex were able to achieve certain concessions. The majority of Soviet Germans in the system of social and labor relations in Nazi Germany were reduced mainly to the level of foreign labor, which is especially clearly evidenced by their relationship with employers and living conditions.
Reduction in gender inequality has become a major component of development agendas, cited as a mechanism for improved access to health care, declining fertility rates, reduced poverty, and increased political and social participation of women. While women’s participation in the labor force is an essential component of increasing gender equity in the developing world, such participation can only be made possible under conditions that allow women to possess the level of autonomy and mobility necessary for engaging in the labor market. In this article, I explain that while women’s labor force participation is an essential component of gender equity, it is not the key to ensuring gender equality. To explain this, I examine India’s decline in women’s labor force participation rate (LFPR) despite its growing economy. I challenge arguments that rationalize that this decline is attributed to the U-shaped hypothesis, and I assert that this decline is associated with existing gendered notions of labor and persisting patriarchal and traditional values that discourage women from re-entering the labor force in the industrial and service sectors.