Hasil untuk "Labor. Work. Working class"

Min Zhang

Abstract In this paper, we examine whether digital finance affects employment quality of migrant workers in China. Based on a nationwide micro data, our empirical results show that migrant workers do benefit from digital finance at the aspect of employment quality. Migrant workers in cities with higher level of digital finance have a higher level of employment quality. The results are robust to a number of variations in our empirical models. Moreover, the positive effect of digital finance on employment quality of migrant workers is stronger for younger, female, and new generation migrant workers, and for migrant workers with lower employment quality and those working in the eastern region. The results of this article are of great significance for clarifying the relationship between digital finance and the employment quality of migrant workers, improving policies and measures related to the floating population, and promoting high-quality economic development.

Les auteurs examinent la capacité des syndicats et de la négociation collective d’entreprise à améliorer les conditions de travail dans les usines de confection approvisionnant les marques et distributeurs multinationaux. Ils montrent, à partir de données recueillies par le programme Better Work au Bangladesh, au Cambodge, à Haïti, en Indonésie, en Jordanie, au Nicaragua et au Viet Nam, que leur rôle peut être positif, même dans les pays qui restreignent la liberté syndicale et la négociation collective. Ils confirment ainsi en partie que l’implication des institutions et acteurs locaux permet d’améliorer le respect des normes du travail du côté production des chaînes d’approvisionnement mondiales.

Anis Omri, Hatem Afi

This article investigates the nexus between artificial intelligence (AI) and employment for people with disabilities, emphasizing the moderating role of governance quality across economic, political, and institutional dimensions. Using panel data from 25 developed countries (2010-2022), the study examines both linear (direct) and nonlinear (complex) effects of AI on employment rates, measured by annual patent applications and industrial robots. The findings reveal that AI initially reduces employment, but its effects diminish and eventually reverse beyond critical adoption thresholds. Gendered differences emerge, with men with disabilities experiencing stronger negative impacts due to their higher concentration in automation-prone industries, while women with disabilities face smaller but still significant effects. Economic governance—through effective policies and regulatory frameworks—mitigates AI’s adverse effects on employment by fostering regulatory environments that promote workforce adaptability and inclusion. Institutional governance—including the rule of law and control of corruption—reinforces these efforts by ensuring fair labor policies and legal protections that safeguard employment opportunities for people with disabilities, thereby reducing the risks associated with AI-driven job displacement. However, political governance shows no significant influence. These findings underscore the importance of integrating AI adoption with strong economic and institutional governance frameworks, which are essential for moderating AI’s impact and shaping inclusive workforce opportunities for people with disabilities.

Kwai-Kong Ng, Min-Fong Yang

The investigation of nonequilibrium thermodynamics in quantum many-body systems underscores the importance of quantum work, which differs from its classical counterpart due to its statistical nature. Recent studies have shown that quantum work can serve as an effective indicator of quantum phase transitions in systems subjected to sudden quenches. However, the potential of quantum work to identify thermal phase transitions remains largely unexplored. In this paper, we examine several types of thermal phase transitions in a sudden-quench hard-core boson model, including Ising, three-state Potts, and Berezinskii-Kosterlitz-Thouless transitions. Through finite-size scaling analysis, we conclude that work statistics can also characterize the critical behaviors of thermal phase transitions in generic many-body systems. Our investigation paves the way for applying work statistics to characterize critical behavior in many-body systems, with implications that may extend to broader contexts.

Dana Calacci, Varun Nagaraj Rao, Samantha Dalal et al.

Rideshare workers experience unpredictable working conditions due to gig work platforms' reliance on opaque AI and algorithmic systems. In response to these challenges, we found that labor organizers want data to help them advocate for legislation to increase the transparency and accountability of these platforms. To address this need, we collaborated with a Colorado-based rideshare union to develop FairFare, a tool that crowdsources and analyzes workers' data to estimate the take rate -- the percentage of the rider price retained by the rideshare platform. We deployed FairFare with our partner organization that collaborated with us in collecting data on 76,000+ trips from 45 drivers over 18 months. During evaluation interviews, organizers reported that FairFare helped influence the bill language and passage of Colorado Senate Bill 24-75, calling for greater transparency and data disclosure of platform operations, and create a national narrative. Finally, we reflect on complexities of translating quantitative data into policy outcomes, nature of community based audits, and design implications for future transparency tools.

Yeonsun Yang, Sang Won Lee, Jean Y. Song et al.

Non-native English speakers performing English-related tasks at work struggle to sustain EFL learning, despite their motivation. Often, study materials are disconnected from their work context. Our formative study revealed that reviewing work-related English becomes burdensome with current systems, especially after work. Although workers rely on LLM-based assistants to address their immediate needs, these interactions may not directly contribute to their English skills. We present LingoQ, an AI-mediated system that allows workers to practice English using quizzes generated from their LLM queries during work. LingoQ leverages these on-the-fly queries using AI to generate personalized quizzes that workers can review and practice on their smartphones. We conducted a three-week deployment study with 28 EFL workers to evaluate LingoQ. Participants valued the quality-assured, work-situated quizzes and constantly engaging with the app during the study. This active engagement improved self-efficacy and led to learning gains for beginners and, potentially, for intermediate learners. Drawing on these results, we discuss design implications for leveraging workers' growing reliance on LLMs to foster proficiency and engagement while respecting work boundaries and ethics.

Alan de Castro Silva, Marta Maria Pinheiro, Lygia Maria de Figueiredo Melo et al.

Este estudo relata a elaboração de uma tecnologia educativa, no formato de cartilha, para dar orientações acerca da mamografia de rastreamento em uma maternidade escola. Trata-se de um estudo descritivo, do tipo relato de experiência, sobre a construção de uma cartilha educativa com orientações acerca da mamografia de rastreio. A elaboração ocorreu em três momentos: identificação das dúvidas com as usuárias sobre o tema; elaboração das perguntas norteadoras e respostas acerca da mamografia de rastreamento; e elaboração da identidade gráfica. A escolha para essa forma de comunicação ocorreu pelo potencial de disseminar informações e compartilhar saberes criativos e transformadores. A elaboração desta tecnologia configura um avanço nas atividades de educação popular em saúde, uma vez que ela representa uma ferramenta com abordagem participativa, por dialogar com as principais fragilidades apontadas pelas usuárias em função das vivências e dos saberes pessoais delas no trajeto percorrido para a realização da mamografia de rastreamento.

Paul Bouffartigue

Salomé Perez-Rosero, Robert Dyer, Samuel W. Flint et al.

Many software engineering maintenance tasks require linking a commit that induced a bug with the commit that later fixed that bug. Several existing SZZ algorithms provide a way to identify the potential commit that induced a bug when given a fixing commit as input. Prior work introduced the notion of a "work item", a logical grouping of commits that could be a single unit of work. Our key insight in this work is to recognize that a bug-inducing commit and the fix(es) for that bug together represent a "work item." It is not currently understood how these work items, which are logical groups of revisions addressing a single issue or feature, could impact the performance of algorithms such as SZZ. In this paper, we propose a heuristic that, given an input commit, uses information about changed methods to identify related commits that form a work item with the input commit. We hypothesize that given such a work item identifying heuristic, we can identify bug-inducing commits more accurately than existing SZZ approaches. We then build a new variant of SZZ that we call Work Item Aware SZZ (WIA-SZZ), that leverages our work item detecting heuristic to first suggest bug-inducing commits. If our heuristic fails to find any candidates, we then fall back to baseline variants of SZZ. We conduct a manual evaluation to assess the accuracy of our heuristic to identify work items. Our evaluation reveals the heuristic is 64% accurate in finding work items, but most importantly it is able to find many bug-inducing commits. We then evaluate our approach on 821 repositories that have been previously used to study the performance of SZZ, comparing our work against six SZZ variants. That evaluation shows an improvement in F1 scores ranging from 2% to 9%, or when looking only at the subset of cases that found work item improved 3% to 14%.

Ross Macmillan, R. Gartner

Chengke Wu, Xiao Li, Rui Jiang et al.

Construction projects face various constraints in terms of materials, labor, equipment, and documents, which can interrupt the scheduled work. Package‐based constraint management (PCM) is a state‐of‐the‐art graph‐based approach that follows the lean theory to effectively model, monitor, and remove constraints before the commencement of work, ensuring smooth construction and minimizing delay and waste. PCM relies on exploring and investigating project knowledge bases (KBs), formed by entity‐relation‐entity triples of constraints. However, most PCM KBs are incomplete and suffer from poor semantics, which hinders the PCM functions. Although many KB completion (KBC) methods exist in the field of artificial intelligence, they primarily focus on general knowledge and exclude the features of specific domains. Therefore, they cannot be directly applied to complete PCM KBs. To address the issue, this study proposes a novel deep learning model, referred to as the domain information enhanced graph neural network (D‐GNN). The features of the developed D‐GNN include (1) building a domain ontology to enrich semantics with rule reasoning, (2) applying the GNN to learn and encode embeddings of constraint entities and relations, and (3) employing a convolution neural network (CNN) for decoding and identifying missing triples. D‐GNN improves the existing KBC methods by integrating two types of domain information, namely, the ontological classes and working contexts into GNN and CNN, respectively. The experimental results verified that the D‐GNN reached an accuracy of 0.848–0.951, and the domain information integration increased the performance by up to 0.263. In practical testing, the D‐GNN significantly reduced the KBC time to 1/6–1/35 of the manual approach and reached higher accuracy. Therefore, the proposed D‐GNN can facilitate PCM by providing complete KBs and supporting downstream constraint monitoring and removal.

Rolando Rodríguez Puga

Según cifras de la Organización Internacional del Trabajo (OIT), cada año fallecen aproximadamente más de 2 millones de personas a causa de enfermedades y accidentes laborales; además de registrarse cerca de 200 millones de casos por dolencias profesionales al año Atendiendo a esta problemática, la salud ocupacional se enfoca sobre todo en prevenir y controlar los riesgos, disminuir las enfermedades y los accidentes asociados a cualquier tipo de trabajo. Para ello, se utiliza la capacitación mediante la información y el aporte al intelecto con énfasis en los factores de riesgo

Zhilu Lian, Yangzi Li, Zhixiang Chen et al.

Working set size estimation (WSS) is of great significance to improve the efficiency of program executing and memory arrangement in modern operating systems. Previous work proposed several methods to estimate WSS, including self-balloning, Zballoning and so on. However, these methods which are based on virtual machine usually cause a large overhead. Thus, using those methods to estimate WSS is impractical. In this paper, we propose a novel framework to efficiently estimate WSS with eBPF (extended Berkeley Packet Filter), a cutting-edge technology which monitors and filters data by being attached to the kernel. With an eBPF program pinned into the kernel, we get the times of page fault and other information of memory allocation. Moreover, we collect WSS via vanilla tool to train a predictive model to complete estimation work with LightGBM, a useful tool which performs well on generating decision trees over continuous value. The experimental results illustrate that our framework can estimate WSS precisely with 98.5\% reduction in overhead compared to traditional methods.

Hirotaka Goto

Individual participants in human society collectively exhibit aggregation behavior. In this study, we present a simple microscopic model of labor force migration based on the active Brownian particles framework. In particular, agent-based simulations show that the model produces clusters of agents from a random initial distribution. Furthermore, two empirical regularities called Zipf's and Okun's laws were observed. To reveal the mechanism underlying the reproduced aggregation phenomena, we use our microscopic model to derive an extended Keller--Segel system, which is a classic model describing the aggregation behavior of biological organisms called taxis. The obtained macroscopic system indicates that the concentration of the workforce in the real world can be explained through a new type of taxis central to human behavior, highlighting the relevance of urbanization to blow-up phenomena in the derived PDE system. We then characterize the transition between the aggregation and diffusion regimes both analytically and computationally. The predicted long-term dynamics of urbanization -- originating in the asymmetric natures of employed and unemployed agents -- are compared with global empirical data, particularly in the realms of labor statistics and urban indicators.

Paolo Padovani, Michele Cirasuolo, Remco van der Burg et al.

Since 2005 ESO has been working with its community and industry to develop an extremely large optical/infrared telescope. ESO's Extremely Large Telescope, or ELT for short, is a revolutionary ground-based telescope that will have a 39-metre main mirror and will be the largest visible and infrared light telescope in the world. To address specific topics that are needed for the science operations and calibrations of the telescope, thirteen specific working groups were created to coordinate the effort between ESO, the instrument consortia, and the wider community. We describe here the goals of these working groups as well as their achievements so far.

Seyyada Tahniat Ali, Gulnaz Zaheer, Iqra Shad

Background: In the health care profession, communication skills serve as the backbone of patient care. Objectives: This analytical study is to investigate the effects of physiotherapists’ communication skills on the patient satisfaction level Methods: Data was collected from private and government setups in different cities between November 2020 to January 2021 after informed consent from patients (N=243) receiving physiotherapeutic management by using a patient satisfaction questionnaire and Kalamazoo essential element checklist. Patients aged between 25-35 years receive physical therapy for more than a week in private and government physical therapy centers. Patients with hearing, neurological and cognitive impairments were excluded. The study reveals the highest average scores for communication and time spent with a physical therapist on a patient satisfaction questionnaire while on Kalamazoo essential element checklist, the highest scores go to open discussion between patient and physical therapist. Results: A total of 243 patients were recruited out of which 123 lie in the age group 25-30 while 120 lie in the age group 30-35. 54.7% were male and 45.3% were female. The results showed that the correlation between communication skills and level of patient satisfaction is weak, but it was significant statistically (r=0.258, p-value<0.05). Conclusion: The communication skills of physiotherapists have a positive impact on satisfaction levels of a patient. This may also be affected by time spent and how the physiotherapist builds relationships with his patient. Keywords: Communication skills, health care profession, Physiotherapist-patient relationship

Eric Moench

A causa de la pandemia Covid-19, los Contact Centers debieron implementar el teletrabajo, transformándose aceleradamente la gestión laboral en base a nuevas prescripciones de supervisión a distancia y la demanda de nuevas capacidades de trabajo para mantener la productividad desde los hogares. Proponemos entender esta transformación reconstruyendo las características del management antes y durante la pandemia, describiendo sus efectos entre la/os agentes de Contact Centers, y analizándolos en torno al concepto de “gubernamentalidad” de Foucault, definido como un encuentro entre técnicas de poder ejercidas sobre otros y técnicas de poder que el individuo ejerce sobre sí, estructurando un campo posible de conductas. Concluimos que la actual eficacia managerial no es meramente un producto tecno-organizativo, sino que se vincula, esencialmente, a disposiciones de auto-organización y auto-control de la/os agentes de Contact Centers (que redefinen sus relaciones con los otros y consigo misma/os), y preanuncia un futuro de gubernamentalidad masiva de teletrabajadores.

hafsah gul khattak

Telerehabilitation provides an alternative way for delivering rehabilitation services without in person contact of the patient and physician. Various technologies are used for communication between therapist and patient for example, use of videos calls, voice call via telephone and internet based conferences. Virtual or augmented environments generated via computers can be used for stroke patient rehabilitation, where patient completes a task shown on computer screen. In the time of covid-19 pandemic where quarantine and isolation strategies are practiced to mitigate spread of virus, utilization of this technology will help in delivering rehabilitation services to stroke survivors in a safe manner. Stroke or cerebrovascular accident is the most common cause of mortality and a leading cause of disability across the world. Stroke survivors often face difficulty performing activities of daily living (ADL) and have limitation in participating in societal activities. Thus increasing the economic cost and increasing the burden. The use of this technology for stroke survivors can improve physical and mental functions without unnecessary visits to hospitals thus reducing the risk of corona virus infection. Maintenance of social distancing provokes psychological stressors like depression and anxiety among stroke patients worsening the conditions further. Telerehabilitation can help in improving psychological health of patients.........

Xiangci Li, Jessica Ouyang

Academic research is an exploration activity to solve problems that have never been resolved before. By this nature, each academic research work is required to perform a literature review to distinguish its novelties that have not been addressed by prior works. In natural language processing, this literature review is usually conducted under the "Related Work" section. The task of automatic related work generation aims to automatically generate the "Related Work" section given the rest of the research paper and a list of cited papers. Although this task was proposed over 10 years ago, it received little attention until very recently, when it was cast as a variant of the scientific multi-document summarization problem. However, even today, the problems of automatic related work and citation text generation are not yet standardized. In this survey, we conduct a meta-study to compare the existing literature on related work generation from the perspectives of problem formulation, dataset collection, methodological approach, performance evaluation, and future prospects to provide the reader insight into the progress of the state-of-the-art studies, as well as and how future studies can be conducted. We also survey relevant fields of study that we suggest future work to consider integrating.

Matz Dahlberg, Johan Egebark, Gülay Özcan et al.

This study uses a randomized control trial to evaluate a new program for increased labor market integration of refugees. The program introduces highly intensive assistance immediately after the residence permit is granted. The early intervention strategy contrasts previous integration policies, which typically constitute low-intensive help over long periods of time. We find positive effects on employment of the program. The magnitude of the effect is substantial, corresponding to around 15 percentage points. Our cost estimates suggest that the new policy is less expensive than comparable labor market programs used in the past.