Hasil untuk "Labor policy. Labor and the state"

L. TSYBULKO, O. BILETSKYI, I. PLYS

DOI: https://doi.org/10.26565/2074-8922-2025-84-28 Abstract. The article examines the main factors of the formation of legal competencies in future teachers and social workers in the context of educational innovations, in particular digital transformation. The relevance of the study is justified, due to transformational processes in society, the reform of educational and social policy of Ukraine, the need to protect human rights in education and the social sphere, as well as the impact of the COVID-19 pandemic and full-scale war, which stimulated the transition to digital formats of education. The purpose is to analyze the main factors influencing the formation of legal competencies in the system of training teachers and social workers. Research results. The work emphasizes the need to integrate digital educational technologies into the process of forming legal competencies, which requires future specialists to combine legal knowledge with digital literacy. The current state of scientific research in this field by domestic and foreign scientists is analyzed. The main directions that determine the effectiveness of the formation of legal competencies are identified: the use of electronic educational platforms (Moodle, Google Classroom, Coursera), interactive learning tools (video lectures, simulations, multimedia resources), active learning methods (case method, project activities, roleplaying games, modeling of legal processes), as well as an interdisciplinary approach that integrates legal, sociological, psychological and economic components. The importance of professional interaction of students with representatives of legal practice (internships, master classes, guest lectures) is emphasized, which contributes to the consolidation of legal knowledge and the formation of ethical responsibility. Particular attention is paid to the new challenges of the digital era - in particular, expanding the content of legal competence by including digital rights, information security issues, personal data protection, human rights in the digital environment, as well as the problem of digital inequality. The need to adapt educational programs to the needs of the modern labor market is emphasized, in particular by introducing modular training, creating individual educational trajectories and including new courses related to law in the field of digital technologies, artificial intelligence, cybersecurity, etc. Conclusions. The formation of legal competencies in future teachers and social workers should take place comprehensively, taking into account the dynamics of digital transformation, the challenges of the modern world and the needs of legal protection of the individual. Effective legal training involves not only the acquisition of knowledge, but also the development of critical thinking, ethical responsibility, the ability to legal communication and adaptation in conditions of change. The article identifies areas for further research, in particular, regarding the integration of legal education with digital platforms, the development of innovative educational technologies and models focused on training a new generation of specialists. In cites: Tsybulko L., Biletskyi O., Plys I. (2025). Factors in the formation of legal competencies in educational innovations within the system of training teachers and social workers. Problems of Engineering Pedagogic Education, (84), 324-334. https://doi.org/10.26565/2074-8922- 2025-84-28 (in Ukrainian)

Zhanyi Sun, Shuran Song

Visuomotor policies trained via behavior cloning are vulnerable to covariate shift, where small deviations from expert trajectories can compound into failure. Common strategies to mitigate this issue involve expanding the training distribution through human-in-the-loop corrections or synthetic data augmentation. However, these approaches are often labor-intensive, rely on strong task assumptions, or compromise the quality of imitation. We introduce Latent Policy Barrier, a framework for robust visuomotor policy learning. Inspired by Control Barrier Functions, LPB treats the latent embeddings of expert demonstrations as an implicit barrier separating safe, in-distribution states from unsafe, out-of-distribution (OOD) ones. Our approach decouples the role of precise expert imitation and OOD recovery into two separate modules: a base diffusion policy solely on expert data, and a dynamics model trained on both expert and suboptimal policy rollout data. At inference time, the dynamics model predicts future latent states and optimizes them to stay within the expert distribution. Both simulated and real-world experiments show that LPB improves both policy robustness and data efficiency, enabling reliable manipulation from limited expert data and without additional human correction or annotation.

Zhenghai Xue, Lang Feng, Jiacheng Xu et al.

To learn from data collected in diverse dynamics, Imitation from Observation (IfO) methods leverage expert state trajectories based on the premise that recovering expert state distributions in other dynamics facilitates policy learning in the current one. However, Imitation Learning inherently imposes a performance upper bound of learned policies. Additionally, as the environment dynamics change, certain expert states may become inaccessible, rendering their distributions less valuable for imitation. To address this, we propose a novel framework that integrates reward maximization with IfO, employing F-distance regularized policy optimization. This framework enforces constraints on globally accessible states--those with nonzero visitation frequency across all considered dynamics--mitigating the challenge posed by inaccessible states. By instantiating F-distance in different ways, we derive two theoretical analysis and develop a practical algorithm called Accessible State Oriented Policy Regularization (ASOR). ASOR serves as a general add-on module that can be incorporated into various RL approaches, including offline RL and off-policy RL. Extensive experiments across multiple benchmarks demonstrate ASOR's effectiveness in enhancing state-of-the-art cross-domain policy transfer algorithms, significantly improving their performance.

Jongmin Lee, Meiqi Sun, Pieter Abbeel

In the unsupervised pre-training for reinforcement learning, the agent aims to learn a prior policy for downstream tasks without relying on task-specific reward functions. We focus on state entropy maximization (SEM), where the goal is to learn a policy that maximizes the entropy of the state stationary distribution. In this paper, we introduce SEMDICE, a principled off-policy algorithm that computes an SEM policy from an arbitrary off-policy dataset, which optimizes the policy directly within the space of stationary distributions. SEMDICE computes a single, stationary Markov state-entropy-maximizing policy from an arbitrary off-policy dataset. Experimental results demonstrate that SEMDICE outperforms baseline algorithms in maximizing state entropy while achieving the best adaptation efficiency for downstream tasks among SEM-based unsupervised RL pre-training methods.

Juntu Zhao, Wenbo Lu, Di Zhang et al.

Imitation-learning-based visuomotor policies have been widely used in robot manipulation, where both visual observations and proprioceptive states are typically adopted together for precise control. However, in this study, we find that this common practice makes the policy overly reliant on the proprioceptive state input, which causes overfitting to the training trajectories and results in poor spatial generalization. On the contrary, we propose the State-free Policy, removing the proprioceptive state input and predicting actions only conditioned on visual observations. The State-free Policy is built in the relative end-effector action space, and should ensure the full task-relevant visual observations, here provided by dual wide-angle wrist cameras. Empirical results demonstrate that the State-free policy achieves significantly stronger spatial generalization than the state-based policy: in real-world tasks such as pick-and-place, challenging shirt-folding, and complex whole-body manipulation, spanning multiple robot embodiments, the average success rate improves from 0% to 85% in height generalization and from 6% to 64% in horizontal generalization. Furthermore, they also show advantages in data efficiency and cross-embodiment adaptation, enhancing their practicality for real-world deployment. Discover more by visiting: https://statefreepolicy.github.io.

Amit Sinha, Aditya Mahajan

The traditional approach to POMDPs is to convert them into fully observed MDPs by considering a belief state as an information state. However, a belief-state based approach requires perfect knowledge of the system dynamics and is therefore not applicable in the learning setting where the system model is unknown. Various approaches to circumvent this limitation have been proposed in the literature. We present a unified treatment of some of these approaches by viewing them as models where the agent maintains a local recursively updateable agent state and chooses actions based on the agent state. We highlight the different classes of agent-state based policies and the various approaches that have been proposed in the literature to find good policies within each class. These include the designer's approach to find optimal non-stationary agent-state based policies, policy search approaches to find a locally optimal stationary agent-state based policies, and the approximate information state to find approximately optimal stationary agent-state based policies. We then present how ideas from the approximate information state approach have been used to improve Q-learning and actor-critic algorithms for learning in POMDPs.

Chongyang Shi, Shuo Han, Michael Dorothy et al.

This paper studies the synthesis of an active perception policy that maximizes the information leakage of the initial state in a stochastic system modeled as a hidden Markov model (HMM). Specifically, the emission function of the HMM is controllable with a set of perception or sensor query actions. Given the goal is to infer the initial state from partial observations in the HMM, we use Shannon conditional entropy as the planning objective and develop a novel policy gradient method with convergence guarantees. By leveraging a variant of observable operators in HMMs, we prove several important properties of the gradient of the conditional entropy with respect to the policy parameters, which allow efficient computation of the policy gradient and stable and fast convergence. We demonstrate the effectiveness of our solution by applying it to an inference problem in a stochastic grid world environment.

Tony Chang, Kiarie Ndegwa, Andreas Gros et al.

This paper explores the application of a novel multi-task vision transformer (ViT) model for the estimation of canopy height models (CHMs) using 4-band National Agriculture Imagery Program (NAIP) imagery across the western United States. We compare the effectiveness of this model in terms of accuracy and precision aggregated across ecoregions and class heights versus three other benchmark peer-reviewed models. Key findings suggest that, while other benchmark models can provide high precision in localized areas, the VibrantVS model has substantial advantages across a broad reach of ecoregions in the western United States with higher accuracy, higher precision, the ability to generate updated inference at a cadence of three years or less, and high spatial resolution. The VibrantVS model provides significant value for ecological monitoring and land management decisions, including for wildfire mitigation.

Umut Yertum

This study aims to determine the working conditions, income levels, job security, discrimination, and professional difficulties of social workers who work as field assistants in an international non-governmental organization operating in Turkey. For this purpose, interviews with 15 social workers using semi-structured interview technique were analyzed with the program Maxqda. All experts apart from the project assistants with overtime hours being compensated for as paid leave and work on-call on a 24/7 basis. The social workers, most of whom have undergraduate degrees, have an average of 3.5 years of seniority, and 66% of them earn a monthly income of 16,000 TL or more. Having witnessed death, injury, or rape among the immigrant groups resulted in 40% of the social workers seeking professional support. Lastly, according to the participants, the most important problems encountered in this area are the indefinite work hours due to being on-call and the fixed-term employment contracts due to being project-based.

Bruno Gawryszewski, Lívia Mouriño de Mello, Natália Silva Pereira

O artigo tem como objetivo discutir o porquê do Novo Ensino Médio ser reivindicado pelos setores dominantes brasileiros como uma janela de oportunidade para adequar a qualificação da força de trabalho às reivindicações das empresas e às aspirações dos jovens. Discutimos o contexto de crise do capital e as transformações do mundo do trabalho e as formulações da CNI acerca da força de trabalho sob o lema da Indústria 4.0. Concluímos que a qualificação reivindicada para a força de trabalho está em consonância com o Novo Ensino Médio, e expressa determinantes e limites do próprio sistema capital. Palavra-chave: Crise do capital; Qualificação; Ensino Médio; Trabalho-Educação.

Dongyun Han, Abdullah-Al-Raihan Nayeem, Jason Windett et al.

Sub-national governments across the United States implement a variety of policies to address large societal problems and needs. Many policies are picked up or adopted in other states. This process is called policy diffusion and allows researchers to analyze and compare social, political, and contextual characteristics that lead to adopting certain policies, as well as the efficacy of these policies once adopted. In this paper, we introduce PDViz, a visual analytics approach for social scientists to dynamically analyze the policy diffusion history and underlying patterns. It is designed for analyzing and answering a list of research questions and tasks posed by social scientists in prior work. To evaluate our system, we present two usage scenarios and conduct interviews with domain experts in political science. The interviews highlight that PDViz provides the result of policy diffusion patterns that align with their domain knowledge as well as the potential to be a learning tool for students and researchers to understand the concept of policy diffusion.

J. J.

Purpose - The objective of this research is to investigate how lowering labor market frictions for female workers affects corporate social responsibility (CSR). Design/methodology/approach - We utilize the staggered adoption of state-level Paid Family Leave (PFL) acts in the U.S. These acts provide significant flexibility for female employees by mandating paid leave for a family or medical events. Our study is based on a sample of 30,027 publicly traded firms in the U.S. from 1991 to 2012. We employ a difference-in-differences research design, considering treated firms as those headquartered in states that enacted PFL laws. Findings - We find that there is a significant increase in the firms’ CSR performance following the adoption of the PFL, suggesting that lowering the labor market frictions for female workers encourages firms to invest in CSR initiatives. Research implications or Originality - This study informs policy makers that PFL enables firms to reduce costly employee turnover and results in an increase in CSR performance.

Ilze Vidžupe

The Baltic States are three small countries on the Baltic coast - Estonia, Latvia and Lithuania, which are united by their geographical location, many centuries-old history, as well as joint cooperation. Since 2018, a new tax reform has entered into force in Latvia, which is planned to be implemented gradually from 2018 to 2021. In Estonia, too, significant changes were made in tax policy in 2018. In Lithuania, the new tax reform was introduced in 2019, which, similarly to Latvia, will continue until 2021. Changes in all countries affected labor taxes, which in turn affected the calculation of wages. The study provided a theoretical description of wages, as well as labor taxes in the Baltic States, changes in their application and the impact on wages.

D. Malets

The article examines the forms of work, directions and methods of work of the search movement in the context of state policy, in particular the project “All-Union campaign of Komsomol members and youth to the places of revolutionary, military and labor glory of the Communist Party and the Soviet people”. The analysis of the sources allows us to characterize the movement of the “red pathfinders” as a youth-patriotic movement, whose activities were aimed at the formation of historical and cultural heritage.

Philippe Pomier Layrargues

Abordamos o perfil da Sociedade de Consumo pela perspectiva da Ecologia Política, para, a partir da análise histórica da constituição desse modelo societário, (a) construir um entendimento de quais foram as transformações que a definem, (b) compreender a influência dos Anos Dourados do Capitalismo; e a partir daí, (c) pensar a questão das necessidades ante o padrão de produção e consumo sustentável. Efetuar tal caracterização ganha relevo no contexto da disputa ideológica da constituição do imaginário sobre qual comportamento de consumo adotar na sociedade orientada pelo American Way of Life. Palavras-chave: Ecologia Política; Educação Ambiental; Sociedade de Consumo; Anos Dourados do Capitalismo; Produção-Destrutiva

T. V. Kashirina

The article is devoted to the problem of concluding the NAFTA agreement in the context of US-Mexican relations and its revision in 2018. The conclusion of the NAFTA agreement took place during the neoliberal reforms carried out in Mexico by Presidents Miguel de la Madrid (1982 – 1988), carlos Salinas de Gortari (1988 – 1994) and Ernest Zedillo (1994 – 2000), and implied the reduction of state regulation of the country’s economic sector, liberalization of banking and credit operations, as well as foreign economic sphere. Neoliberal reforms in Mexico were carried out in the spirit of the «Washington consensus» - economic policy, «economic recommendations», which the United States tried to extend to other states. During this period, branches of the American TNC «Maquiladoras» began to gain more and more weight in the economic life of Mexico. It is proved that the initial war gave an impetus to the development of production and export-oriented goods, but secured to a certain extent the dependent position of the country within the framework of the treaty. The treaty also significantly undermined the development of Mexico’s agricultural sector. But on the other hand, the treaty promoted the economic cooperation of its participants, foreign policy contacts, and the strengthening of diplomatic and social ties. During the election campaign of the future US President D.Trump presented the agreement in the context of the desire of the United States to withdraw from the free trade zone. In the spirit of protectionism, D. Trump believed that NAFTA led to the «overflow» of American production capacities, the deindustrialization of the country’s economic sector and the growth of the surplus in trade with the United States. The firm intentions of the US president to reform the agreement resulted in the reset of NAFTA. The renewal of the USMcA agreement in 2018 strengthened the access of American companies to the Mexican market, and especially to the oil-producing sphere. The new USMCA agreement regulates a wide range of economic areas: the automotive industry, wage issues and the labor market, intellectual property and electronic commerce, financial transactions, exchange rates, dairy agricultural products and dispute resolution issues.It is concluded that both the initial and subsequent versions of the NAFTA/USMcA agreement were more beneficial to the United States. But even for Mexico, despite the concessions made, the agreement is a factor in maintaining relations with Washington.The article is devoted to the problem of concluding the NAFTA agreement in the context of USMexican relations and its revision in 2018. It is proved that the initial version of NAFTA contributed to the recovery of Mexico from the economic crisis, but secured to a certain extent the country’s dependent position within the framework of the treaty. The renewal of the agreement in the USMcA format in 2018 strengthened the access of American companies to the Mexican market, and especially to the oil sector. It is concluded that both the initial and subsequent versions of the NAFTA/USMCA agreement were more beneficial to the United States. But for Mexico, despite the concessions made, the agreement is a factor in maintaining relations with Washington.

Inna Šteinbuka, Aldis Austers, Oļegs Barānovs et al.

The decision of EU and the response of the national governments to COVID-19 crisis provide the basis for returning “back to normal”. A key challenge is the transition to economic recovery in the presence of the ongoing COVID-19 risk. Adequate policy mix and forward-looking actions of the public institutions are crucial to mitigate the devastating impact of the crisis and to preserve growth. Governments need to facilitate positive changes in the labor market, adjust the macroeconomic and fiscal regimes, and mitigate the post-crisis “fatigue” of societies. The turmoil of the EU economy is symmetrical, as the pandemic has affected all EU Member States, but the impact of the pandemic varies considerably from one country to another, as does their ability to absorb the economic crisis. Also, variation in the vaccination performance is partly due to different institutional characteristics across countries. Small countries are more vulnerable to external economic shocks; however, they can increase their resilience by efficient governance and social response. Extraordinary pandemic crisis can be seen as a stress test for the small and open Latvian economy, and it is worth analyzing the lessons that Latvia had learned and its future prospects. The aim of this paper is to evaluate the economic and social consequences of the ongoing crisis in Latvia, assess the effectiveness of the response of the government to the crisis, analyse people's perceptions, and to identify the future scenarios. The authors applied a special theoretical framework for the assessment of the effectiveness of institutions. Institutional analysis of crises response by the Latvian government reveals that the government managed to avoid serious functional disruptions; however, it failed to show convincing ability to learn by doing. The authors also provide a comprehensive analysis of the macroeconomic trends of the “COVID-sick” Latvian economy and conclude that future-oriented solutions relate to international competitiveness and that the key factor of competitiveness is a productivity renaissance. The pandemic crisis has fostered the state support for healthcare, which in Latvia for decades has been underfinanced. The right choice of fiscal instruments is crucial to accelerate the economic recovery and better healthcare. Research is based on the macroeconomic assessment and survey-based analysis. The comparison of statistically justified findings with the public perception helps formulate conclusions on the future scenarios and policies.

Ritesh Goenka, Eashan Gupta, Sushil Khyalia et al.

Policy Iteration (PI) is a widely used family of algorithms to compute optimal policies for Markov Decision Problems (MDPs). We derive upper bounds on the running time of PI on Deterministic MDPs (DMDPs): the class of MDPs in which every state-action pair has a unique next state. Our results include a non-trivial upper bound that applies to the entire family of PI algorithms; another to all "max-gain" switching variants; and affirmation that a conjecture regarding Howard's PI on MDPs is true for DMDPs. Our analysis is based on certain graph-theoretic results, which may be of independent interest.

Gabriele Borg, Diego Gentile Passaro, Santiago Hermo

The recent rise of sub-national minimum wage (MW) policies in the US has resulted in significant dispersion of MW levels within urban areas. In this paper, we study the spillover effects of these policies on local rental markets through commuting. To do so, for each USPS ZIP code we construct a "workplace" MW measure based on the location of its resident's jobs, and use it to estimate the effect of MW policies on rents. We use a novel identification strategy that exploits the fine timing of differential changes in the workplace MW across ZIP codes that share the same "residence" MW, defined as the same location's MW. Our baseline results imply that a 10 percent increase in the workplace MW increases rents at residence ZIP codes by 0.69 percent. To illustrate the importance of commuting patterns, we use our estimates and a simple model to simulate the impact of federal and city counterfactual MW policies. The simulations suggest that landlords pocket approximately 10 cents of each dollar generated by the MW across directly and indirectly affected areas, though the incidence on landlords varies systematically across space.