Hasil untuk "Labor. Work. Working class"

I. Bernstein

C. Spellman, J. McBride

This paper presents the lived experience of white working‐class women in the UK experiencing in‐work poverty and dependent on food banks to survive. Although the precarious labor market emerges as a significant driver in the women's need for food charity, in‐depth investigations into the lives that precarity produces and reinforces remain scarce. Contributing to this gap, our paper uses an ethnographic qualitative approach drawing on feminist research methods to identify women's experiences of in‐work poverty and being in precarious work. Across 2 food banks, 10 women and 6 volunteers were interviewed, complemented by 24 months of comprehensive field notes where the lead author was a regular volunteer with the charities. The paper revisits “The Hidden Injuries of Class” from Sennett and Cobb's (1972) classic study to use as a theoretical lens to draw out the internalized impacts that the participants experienced. We complement the theoretical framing with an intersectional sensitivity, finding that both gender and class were prevailing identities that influenced the women's lived experiences of the explored themes. The combination of these frameworks helped us to discover how the women face a complex internalized struggle in accessing food banks whilst being employed, heavily characterized by classed and gendered constraints associated with precarious work and other external structural disadvantages. The women experienced guilt, shame, the suppression of emotion, and a struggle for self‐validation. Interactions at the food bank were additionally found to be intersubjectively negotiated between the women and the present volunteers. The intersection of both classed and gendered identities exposes these women to ever greater inequalities both within and beyond the workplace.

Harry Williamson, Dermot Coates, Kevin Daly et al.

Abstract The adoption of AI technology by industry could significantly disrupt our current understanding of “typical” economic activity. As AI comes to pervade more sectors and occupations over time, it is likely that this technology will give rise to challenges and risks but also opportunities and benefits. There is, however, a significant degree of uncertainty regarding how future waves of technological change will impact the economy, including the labour market. Recent research has found that 40% of employment globally is exposed to AI and that this rises to 60% of employment in advanced economies. We analyse exposure and complementarity in tandem in order to better understand the potential impact across occupation types in Ireland. We find that Ireland is relatively more exposed to AI than is the case for other advanced economies. We also find find that female workers in Ireland are more likely to work in highly exposed roles compared to males, that younger Irish workers are more exposed to AI than are older workers, and that both exposure complementarity to AI increase in line with educational attainment. Finally, we contend that the extent to which AI augments, or replaces, human labour in the medium to long-run will depend on a variety of economic, social and policy factors, including levels of AI regulation. JEL classification: J21, J24, O31.

Alex Farach, Alexia Cambon, Jared Spataro

As the digital economy grows increasingly intangible, traditional productivity measures struggle to capture the true economic impact of artificial intelligence (AI). AI systems capable of cognitive work significantly enhance productivity, yet their contributions remain obscured within the residual category of Total Factor Productivity (TFP). This paper explores whether it is time for a conceptual shift to explicitly recognize "digital labor," the autonomous cognitive capability of AI, as a distinct factor of production alongside capital and human labor. We outline the unique economic properties of digital labor, including scalability, intangibility, self-improvement, rapid obsolescence, and elastic substitutability. By integrating digital labor into growth models (such as those by Solow and Romer), we demonstrate strategic implications for business leaders, including new approaches to productivity tracking, resource allocation, investment strategy, and organizational design. Ultimately, treating digital labor as an independent factor offers a clearer view of economic growth and helps organizations manage AI's transformative potential.

Janneke Pieters, Ana Kujundzic, Rulof Burger et al.

Technological change can have profound impacts on the labor market. Decades of research have made it clear that technological change produces winners and losers. Machines can replace some types of work that humans do, while new technologies increase human's productivity in other types of work. For a long time, highly educated workers benefitted from increased demand for their labor due to skill-biased technological change, while the losers were concentrated at the bottom of the wage distribution (Katz and Autor, 1999; Goldin and Katz, 2007, 2010; Kijima, 2006). Currently, however, labor markets seem to be affected by a different type of technological change, the so-called routine-biased technological change (RBTC). This chapter studies the risk of automation in developing country labor markets, with a particular focus on differences between men and women. Given the pervasiveness of gender occupational segregation, there may be important gender differences in the risk of automation. Understanding these differences is important to ensure progress towards equitable development and gender inclusion in the face of new technological advances. Our objective is to describe the gender gap in the routine task intensity of jobs in developing countries and to explore the role of occupational segregation and several worker characteristics in accounting for the gender gap.

Isabella Di Filippo, Bruno Escobar, Juan Facal

We study how increases in remote work opportunities for men affect their spouses' labor supply. Exploiting variation in the change in work-from-home (WFH) exposure across occupations before and after the COVID-19 pandemic, we find that increases in men's WFH exposure led to sizable improvements in their wives' labor-market outcomes: annual employment rose by roughly 2.5 percentage points (from a 69% pre-treatment mean), earnings increased by about 5%, weekly hours worked rose by roughly half an hour, weeks worked increased by about 1.3%, and the likelihood of part-time work declined by approximately 9%. Evidence from time-use diaries and childcare questionnaires suggests these effects are driven by intra-household reallocation of child-caring time: women are less likely to engage in primary childcare activities, while men working at home partially compensate by covering more for their spouse. These results highlight the role of households in shaping the labor market consequences of remote work.

David Marguerit

Artificial intelligence (AI) is reshaping the labor market by changing the task content of occupations. This study investigates the impact of AI development on the emergence of new work, employment, and wages in the United States from 2015 to 2022. I develop innovative methods to measure occupational and industry exposure to AI technologies that substitute labor (automation AI ) or enhance workers' output (augmentation AI), and to identify new work (i.e., new job titles). To address endogeneity, I use instrumental variable estimators, leveraging AI development in countries with limited economic ties to the United States. The findings indicate that automation AI negatively impacts new work, employment, and wages in low-skilled occupations, while augmentation AI fosters the emergence of new work and raises wages for high-skilled occupations. These results suggest that AI may contribute to rising wage inequality.

Gianna Williams, Maya De Los Santos, Alexandra To et al.

The global AI surge demands crowdworkers from diverse languages and cultures. They are pivotal in labeling data for enabling global AI systems. Despite global significance, research has primarily focused on understanding the perspectives and experiences of US and India crowdworkers, leaving a notable gap. To bridge this, we conducted a survey with 100 crowdworkers across 16 Latin American and Caribbean countries. We discovered that these workers exhibited pride and respect for their digital labor, with strong support and admiration from their families. Notably, crowd work was also seen as a stepping stone to financial and professional independence. Surprisingly, despite wanting more connection, these workers also felt isolated from peers and doubtful of others' labor quality. They resisted collaboration and gender-based tools, valuing gender-neutrality. Our work advances HCI understanding of Latin American and Caribbean crowdwork, offering insights for digital resistance tools for the region.

Sana Khalil, Angela Warner

We highlight the barriers shaping women's economic opportunities in Pakistan, where female labor force participation remains among the lowest globally. Labor force surveys (2020-21) show a stark rural-urban divide: 28 percent for rural women versus 69 percent for rural men, and 10 percent for urban women versus 66 percent for urban men. Unemployment is higher for women (7 percent in rural areas; 16 percent in urban areas) than for men (5 and 6 percent, respectively). Women are concentrated in agriculture (68 percent), with limited presence in services (17 percent) and industry (15 percent), and mostly in rural (51 percent) or home-based (30 percent) work; only 14 percent are in formal business settings. Employment status reflects vulnerability: 63 percent of rural women are unpaid contributing family workers versus 17 percent of urban women. Interviews with married women in Karachi underscore childcare constraints, harassment and safety concerns, transport barriers, and family opposition. Together, the evidence points to structural and cultural constraints that restrict access to paid work; easing them will require labor market reforms, better transport and childcare, stronger protections against harassment and discrimination, and a gradual change in gender norms and household decision-making.

Natalia Reich-Stiebert, L. Froehlich, J. Voltmer

With this literature review, we provide a systematic overview on and working definition of mental labor in the context of unpaid work—an inherent cognitive component of daily routines primarily related to domestic or childcare tasks. Our methodology followed PRISMA guidelines, and 31 full-text articles were included. Articles were peer-reviewed and published in social science, sociological, and psychological journals. The studies applied quantitative and qualitative methodological approaches including, interviews, online surveys, observations of family routines, time estimates, and experiments. The samples covered a wide age range, consisting mostly of U.S. American or European middle-class women and men (married or in a relationship). Predominantly, the articles show that women perform the larger proportion of mental labor, especially when it comes to childcare and parenting decisions. Further, women experience more related negative consequences, such as stress, lower life and relationship satisfaction, and negative impact on their careers. We offer an integrative theoretical perspective to explain the gendered distribution of mental labor and cognitive load. We consider theoretical and practical implications of these findings for reducing gender inequality in mental labor in the context of unpaid work within the household and childcare.

Pegah Moradi, Karen Levy, Cristobal Cheyre

Self-service machines are a form of pseudo-automation; rather than actually automate tasks, they offset them to unpaid customers. Typically implemented for customer convenience and to reduce labor costs, self-service is often criticized for worsening customer service and increasing loss and theft for retailers. Though millions of frontline service workers continue to interact with these technologies on a day-to-day basis, little is known about how these machines change the nature of frontline labor. Through interviews with current and former cashiers who work with self-checkout technologies, we investigate how technology that offsets labor from an employee to a customer can reconfigure frontline work. We find three changes to cashiering tasks as a result of self-checkout: (1) Working at self-checkout involved parallel demands from multiple customers, (2) self-checkout work was more problem-oriented (including monitoring and policing customers), and (3) traditional checkout began to become more demanding as easier transactions were filtered to self-checkout. As their interactions with customers became more focused on problem solving and rule enforcement, cashiers were often positioned as adversaries to customers at self-checkout. To cope with perceived adversarialism, cashiers engaged in a form of relational patchwork, using techniques like scapegoating the self-checkout machine and providing excessive customer service in order to maintain positive customer interactions in the face of potential conflict. Our findings highlight how even under pseudo-automation, workers must engage in relational work to manage and mend negative human-to-human interactions so that machines can be properly implemented in context.

Venkat Ram Reddy Ganuthula

This paper introduces Agency-Driven Labor Theory as a new theoretical framework for understanding human work in AI-augmented environments. While traditional labor theories have focused primarily on task execution and labor time, ADLT proposes that human labor value is increasingly derived from agency - the capacity to make informed judgments, provide strategic direction, and design operational frameworks for AI systems. The paper presents a mathematical framework expressing labor value as a function of agency quality, direction effectiveness, and outcomes, providing a quantifiable approach to analyzing human value creation in AI-augmented workplaces. Drawing on recent work in organizational economics and knowledge worker productivity, ADLT explains how human workers create value by orchestrating complex systems that combine human and artificial intelligence. The theory has significant implications for job design, compensation structures, professional development, and labor market dynamics. Through applications across various sectors, the paper demonstrates how ADLT can guide organizations in managing the transition to AI-augmented operations while maximizing human value creation. The framework provides practical tools for policymakers and educational institutions as they prepare workers for a labor market where value creation increasingly centers on agency and direction rather than execution.

Opeyemi Akanbi

Rey Hikaru Y. Estoce, O. M. Ngan, P. Calderon

Dubbed the “inequality virus”, coronavirus disease (COVID-19) has unveiled and magnified many of the global society’s long-standing inequalities and health inequities. This work brings together the phenomena of increased inequality and health inequities felt by the poor and young working class of the Philippines and how they interact negatively with existing vaccine policies. The poor and the young were more likely to have experienced employment disruptions with limited access to technologies that allowed for teleworking. Informal economy workers suffered from diminished labor protection and draconian lockdowns. Disadvantaged areas persistently dealt with limited health resources, and the working class was disproportionately vulnerable to COVID-19 infection. Utilitarian vaccine policies such as mandatory vaccination and the prioritization scheme negatively interacted with these COVID-induced inequalities and health inequities. While the young working class was more likely to be unemployed, mandatory vaccine policy required that they get vaccinated before seeking re-employment. However, the prioritization scheme adopted by the government failed to target them as a priority. This left them in a vulnerable state of prolonged unemployment while on standby for better supply and improved infrastructure for vaccine rollout. Future prospects in terms of economic recovery and health equity will be affected by issues such as potential increased taxation, the rapidly digitalizing labor market that is evolving to favor highly-skilled workers, and the staging of universal healthcare in the country.

K. Chen, S. Islam

While the effects of labor unions on objective conditions have been extensively studied, little is known about their role in individuals’ perceptions of economic circumstances. We investigate whether union density affects the subjective well-being of area residents by exploiting the staggered adoption of right-to-work laws in the United States through a border-county design. We find that unionization promotes happiness for those of low socioeconomic status, including non-college-educated residents and current or former blue-collar job holders, but has no discernible impact on their high-status counterparts. Of affected residents, workers stand to reap the most benefit. We also find that the favorable effect of unionization is transmitted through the assessment of improved financial situation, personal health, and workplace quality. This finding highlights the role of pecuniary and nonpecuniary benefits (for example, on-the-job safety, work-life balance, interpersonal trust, and workers’ autonomy) that unions afford to protect society’s most marginalized groups.

Eduard Storm

Abstract Using German survey and expert data on job tasks, this paper explores the presence of omitted-variable bias suspected in conventional task data derived from expert assessment. I show expert task data, which is expressed at the occupation-level, introduces omitted-variable bias in task returns on the order of 26–34%. Motivated by a theoretical framework, I argue this bias results from expert data ignoring individual heterogeneity rather than fundamental differences on the assessment of tasks between experts and workers. My findings have important implications for the interpretation of conventional task models as occupational task returns are overestimated. Moreover, a rigorous comparison of the statistical performance of various models offers guidance for future research regarding choice of task data and construction of task measures.

Zahid Mehmood, Zubair Ahmad, Asad Ullah et al.

Background: Understanding students' perception of the educational environment and their cognitive load in this context is crucial for optimizing the effectiveness of e-learning platforms. Objective: To compare educational environment perception and cognitive load in under-graduates Doctor of Physical Therapy (DPT) and post-graduate Master in Science of Physical Therapy (MSPT) students having online learning experiences. Methodology: In this comparative cross-sectional study, data was collected through non-probability convenient sampling from n=274 under-graduates DPT (n=225) and post-graduates MSPT(n=49) students of either gender having one-semester experience of online learning, Dundee Ready Education Environment Measure (DREEM) for measuring educational environmental perception and Rating Scale of Mental Effort (RSME) for measurement of cognitive load. Online self-structured was developed questionnaire and shared through communication media platform and data analysis was made through SPSS version 28. Results: There were n=225 under-graduates (DPT) and n=49 post-graduates (MSPT) students in which, there were n=208 females and n=66 males. The overall DREEM score showed that MSPT students are more significantly positive (p<0.001, Cohen’s d=1.01) than DPT students regarding the perception of the educational environment with a large effect size. While there was no significant difference (p=0.114) between MSP and DPT students regarding cognitive load. Conclusion: Post-graduates (MSPT) students have better educational environmental perception than undergraduate (DPT) students but there was no significant difference in cognitive load in undergraduate (DPT) and post-graduates (MSPT) students. Keywords: cognition; cognitive load; mental effort; e-learning; physiotherapist.

Ildiko Racz-Antal

The paper focuses on some labour law questions which arise from work in the metaverse. The first question is whether meta-work could be the next new type of work as standard employment relationship, which is going through a transformation in general. Indeed, the idea of personal work – as a main pillar of the employment relationship – was challenged by platform work in the recent years, but metaverse seems to further question the old paradigms. The article shortly examines the question of wages, for instance, as the metaverse generally relies on cryptocurrency (CC) to pay for transactions and purchases. Subsequently, the paper mainly concentrates on the analysis of health and safety at work and of the discrimination ban in metaverse.

Matthew Nice, Matthew Bunting, George Gunter et al.

This work demonstrates a new capability in roadway control: Speed-adaptive, infrastructure-linked connected and automated vehicles. We develop and deploy a lightly modified vehicle that is able to dynamically adjust the vehicle speed in response to posted variable speed limit messages generated by the infrastructure using LTE connectivity. This work describes the open source hardware and software platform that enables integration between infrastructure-based variable posted speed limits, and existing vehicle platforms for automated control. The vehicle is deployed in heavy morning traffic on I-24 in Nashville, TN. The control vehicle follows the posted variable speed limits, resulting in as much as a 25% reduction in speed variability compared to a human-piloted vehicle in the same traffic stream.

Sebastian T. Braun, Jan Stuhler

With 70 million dead, World War II remains the most devastating conflict in history. Among the survivors, millions were displaced, returned maimed from the battlefield, or endured years of captivity. We examine the effects of such war exposures on labor market careers, showing that they often become apparent only at certain life stages. While war injuries reduced employment in old age, former prisoners of war prolonged their time in the workforce before retiring. Many displaced workers, especially women, never returned to employment. These responses align with standard life-cycle theory and thus likely hold relevance for other conflicts.