Hasil untuk "Labor policy. Labor and the state"

B. Xiang, J. Lindquist

Based on the authors’ long-term field research on low-skilled labor migration from China and Indonesia, this article establishes that more than ever labor migration is intensively mediated. Migration infrastructure – the systematically interlinked technologies, institutions, and actors that facilitate and condition mobility – serves as a concept to unpack the process of mediation. Migration can be more clearly conceptualized through a focus on infrastructure rather than on state policies, the labor market, or migrant social networks alone. The article also points to a trend of “infrastructural involution,” in which the interplay between different dimensions of migration infrastructure make it self-perpetuating and self-serving, and impedes rather than enhances people's migratory capability. This explains why labor migration has become both more accessible and more cumbersome in many parts of Asia since the late 1990s. The notion of migration infrastructure calls for research that is less fixated on migration as behavior or migrants as the primary subject, and more concerned with broader societal transformations.

Zhe Sun, Liang Zhao, Ankit Mehrotra et al.

The rise of cutting‐edge technologies motivates corporations to undertake and carry forward green innovation, aiding economic development by maintaining environmental sustainability. Using A‐share listed firms from 2013 to 2022 as the research sample, the paper empirically examines the impact of digital transformation on corporate green innovation from an affordance perspective. The findings suggest that the higher the level of digital transformation, backed by accumulative and variational affordances, in a firm, the more conducive it is to corporate green innovation as it enables the homogenization, recombination, and transformation of existing information related to green environmental protection and low‐carbon energy efficiency, facilitating firms to achieve targeted and breakthrough green innovations. The analysis of the moderating effects of public environmental concern, economic policy uncertainty, and regional innovation readiness suggested that public environmental concern and regional innovation readiness positively moderate the relationship between digital transformation and corporate green innovation, while economic policy uncertainty perception negatively moderates this relationship. Heterogeneity analyses suggest that digital transformation positively affects corporate green innovation within labor‐intensive firms and state‐owned enterprises. The study contributes to the literature by enhancing our understanding of the affordance theory in the domain of digital transformation. By investigating the key organizational and institutional affordances – economic policy uncertainty perception, public environmental concern, and regional innovation readiness – the research provides valuable insight to policymakers in fostering green innovation.

Juan Federico VON ZESCHAU, Marcial S¡NCHEZ-MOSQUERA

Nous évaluons ici le fonctionnement du conseil économique et social de la République argentine (CES-A) durant ses deux années d’activité (2021-2022). Pour ce faire, nous étudions le déploiement du CES-A dans le cadre institutionnel hiérarchisé de l’économie argentine et comparons l’instance au conseil sur le salaire minimum (CSMVM) en mettant l’accent sur leurs complémentarités institutionnelles. À partir d’informations secondaires, d’observations participantes et d’entretiens semi-structurés, nous mettons en évidence les contraintes internes et externes qui ont influencé le changement institutionnel que le CES-A devait apporter. L’arrivée au pouvoir d’un nouveau gouvernement en 2023, conjugué à un manque de résultats, a entraîné la dissolution du CES-A. 

Taewook Nam, Sung Ju Hwang

Recent advances in robotic policy learning have enabled complex manipulation in real-world environments, yet the execution speed of these policies often lags behind hardware capabilities due to the cost of collecting faster demonstrations. Existing works on policy acceleration reinterpret action sequence for unseen execution speed, thereby encountering distributional shifts from the original demonstrations. Reinforcement learning is a promising approach that adapts policies for faster execution without additional demonstration, but its unguided exploration is sample inefficient. We propose SpeedAug, an RL-based policy acceleration framework that efficiently adapts pre-trained policies for faster task execution. SpeedAug constructs behavior prior that encompasses diverse tempos of task execution by pre-training a policy on speed-augmented demonstrations. Empirical results on robotic manipulation benchmarks show that RL fine-tuning initialized from this tempo-enriched policy significantly improves the sample efficiency of existing RL and policy acceleration methods while maintaining high success rate.

Lingwei Zhu, Han Wang, Yukie Nagai

Sparse continuous policies are distributions that can choose some actions at random yet keep strictly zero probability for the other actions, which are radically different from the Gaussian. They have important real-world implications, e.g. in modeling safety-critical tasks like medicine. The combination of offline reinforcement learning and sparse policies provides a novel paradigm that enables learning completely from logged datasets a safety-aware sparse policy. However, sparse policies can cause difficulty with the existing offline algorithms which require evaluating actions that fall outside of the current support. In this paper, we propose the first offline policy optimization algorithm that tackles this challenge: Fat-to-Thin Policy Optimization (FtTPO). Specifically, we maintain a fat (heavy-tailed) proposal policy that effectively learns from the dataset and injects knowledge to a thin (sparse) policy, which is responsible for interacting with the environment. We instantiate FtTPO with the general $q$-Gaussian family that encompasses both heavy-tailed and sparse policies and verify that it performs favorably in a safety-critical treatment simulation and the standard MuJoCo suite. Our code is available at \url{https://github.com/lingweizhu/fat2thin}.

Wenkang Ji, Huaben Chen, Mingyang Chen et al.

The development of control policies for multi-robot systems traditionally follows a complex and labor-intensive process, often lacking the flexibility to adapt to dynamic tasks. This has motivated research on methods to automatically create control policies. However, these methods require iterative processes of manually crafting and refining objective functions, thereby prolonging the development cycle. This work introduces \textit{GenSwarm}, an end-to-end system that leverages large language models to automatically generate and deploy control policies for multi-robot tasks based on simple user instructions in natural language. As a multi-language-agent system, GenSwarm achieves zero-shot learning, enabling rapid adaptation to altered or unseen tasks. The white-box nature of the code policies ensures strong reproducibility and interpretability. With its scalable software and hardware architectures, GenSwarm supports efficient policy deployment on both simulated and real-world multi-robot systems, realizing an instruction-to-execution end-to-end functionality that could prove valuable for robotics specialists and non-specialists alike.The code of the proposed GenSwarm system is available online: https://github.com/WindyLab/GenSwarm.

Joseph Marvin Imperial, Harish Tayyar Madabushi

Policy compliance assessment is a fundamental task of evaluating whether an input case strictly complies with a set of human-defined rules, more generally known as policies. In practice, human experts follow a systematic, step-by-step process to identify violations with respect to specific stipulations outlined in the policy. However, such documentation of gold-standard, expert-level reasoning processes is costly to acquire. In this paper, we introduce Policy Reasoning Traces (PRT), a form of specialized generated reasoning chains that serve as a reasoning bridge to improve an LLM's policy compliance assessment capabilities. Our empirical evaluations demonstrate that the use of PRTs for both inference-time and training-time scenarios significantly enhances the performance of open-weight and commercial models, setting a new state-of-the-art for HIPAA and GDPR policies. Beyond accuracy gains, we also highlight how PRTs can improve an LLM's ability to accurately cite policy clauses, as well as influence compliance decisions through their high utilization from the raw chains of thought.

Hangyu Mao, Guangting Dong, Zhicheng Dou

We present the Generalized Policy Gradient (GPG) Theorem, specifically designed for Transformer-based policies. Notably, we demonstrate that both standard Policy Gradient Theorem and GRPO emerge as special cases within our GPG framework. Furthermore, we explore its practical applications in training Large Language Models (LLMs), offering new insights into efficient policy optimization.

Ikhlaq Ahmed, H. Wagan, J. G. M. Sahito et al.

In this chapter, a comparative and rigorous analysis of how changes in the Real Effective Exchange Rate (REER) affect three macroeconomic variables which include Gross Domestic Product (GDP) growth, agricultural exports, and Foreign Direct Investment (FDI) in Pakistan, India, and China is made. The states mentioned above, although geographically close to each other and of importance to the global economy as a block, are quite different in terms of institutional frameworks, exchange-hate regimes, structural composition and policy autonomy, thus, creating quite different transmission mechanisms of REER. The country is typified by endemic structural weaknesses in its three main forms, a small export base, overdependence on imported energy as well as insufficient fiscal cushions, that increase its susceptibility to REER misalignments. Empirical studies show that REER overvaluation reduces long-term growth in GDP by reducing the competitiveness of exports but gains on depreciation are often immediately offset by imported inflation that often exceeds 20 per cent in crisis. Agricultural exports which make up close to a quarter of GDP and half of the labour force are acutely sensitive to real appreciation; a 1 per cent appreciation of the REER will reduce the volumes of exports by 0.6-0.9 per cent with the effect lasting more than two years due to asymmetric adjustment processes. Moreover, REER volatility discourages FDI inflows that stand at a modest US$ 23 billion a year on average because investors face increased macroeconomic uncertainty especially in capital intensive industries, thus putting at risk strategic programmes like the China-Pakistan Economic Corridor (CPEC). By contrast, China takes advantage of its institutional strength, vast foreign -exchange holdings (above US 3 trillion), and a state -based economic system to transform the REER into a policy instrument. The people bank of China plays a crucial role in the changes of the exchange rates to maintain the export-led growth without destabilizing inflation and moderate depreciation to help boost the industrial production in the coastal provinces and protect the agricultural sector with subsidies and strategic reserves. The shift of China towards high-value agricultural exports and the use of currency swap agreements as a part of the Belt and Road Initiative is an additional step of China to shelter its external sector against REER volatility. As a result, China becomes the leading destination of FDI in the developing economies where it receives more than US180 billion every year as it takes the exchange-rate policy and integrates it with infrastructure construction and technology modernization to create a virtuous cycle of competitiveness and integration. India holds an intermediate position, which is typified by an exchange rate regime that is market driven. Dominating regime structure, democratic form of governance and dualistic economy. Although, the Balassa-Samuelson effect has led to the loss of cost competitiveness in labor-intensive production, and hampered the program of Make in India, the moderate depreciation has a positive effect on agriculture output by increasing rural incomes. Exporting agricultural products, however, is vulnerable to the fluctuations of the currency (Increasing by 0.7 per cent of exports of rice with a single per cent appreciation of the REER), and farmers who are not hedged are especially vulnerable; value-added processing is slowly making agricultural products more resilient in that regard. The inflows of foreign direct investment (FDI) of about US 60-80 billion a year are bifurcated market seeking investment in services is relatively insensitive to the fluctuations in exchange rate, and export-platform FDI is deterred by exchange-rate volatility. The larger domestic marketplace as well as the diversification of energy inherent in India gives it some cushion against imported inflation.

Fang Xu, Jing Gao, Qian Wang

This study is part of the project “Research on intelligent processing of bill documents based on SVM and LD algorithm”. This study addresses the challenges associated with State Grid Corporation's internal process of medical insurance claims, including demanding workload, varying medical insurance policies in different regions, and medical documents with changing formats and unqualified image quality. It innovatively presents a novel insurance claims processing workflow integrated with intelligent techniques. This solution works with an intelligent mechanism for claims process automation, risk management, and business data monitoring, in a bid to transform claims processing into an AI-powered, efficient system. Using this solution, OCR can automatically extract key information, including units and amounts from medical invoices, while with the support of natural language processing, the conditions and prescriptions listed in diagnosis certificates can be analyzed quickly. Furthermore, it thoroughly screens and verifies medical content, prices and other cost details from medical insurance data. The rule-based system that the system hinges on automatically matches insurance claims with insurance policies, making the verification of medical insurance premiums and corresponding compensation faster and more efficient. In addition to reducing labor costs and raising processing efficiency, this technology also allows for an intelligent compensation self-service procedure, which is conducive to enterprises’ transformation into the digital environment and scale both their economic and societal value creation.

K. Petrenko, Marta Ravska

The article examines the impact of external environment instability on the effectiveness of foreign economic activity of enterprises in the automotive industry. In the context of global economic turbulence, geopolitical tensions, disruption of supply chains and fluctuations in exchange rates, automotive enterprises are experiencing significant pressure, which reduces their competitiveness in international markets. The automotive industry, as one of the most important components of the industry, has undergone serious structural transformations, lost part of its production capacity and logistics routes, which negatively affected export volumes, participation in global supply chains and the competitiveness of Ukrainian products in foreign markets. Particular attention is paid to the analysis of the main types of instability - economic, political and institutional - and the mechanisms of their influence on foreign economic operations. Based on statistical data and examples of the activities of leading Ukrainian and foreign companies in the industry, the key risk factors that lead to a decrease in the efficiency of exports and imports, loss of positions in foreign markets, and an increase in logistics and insurance costs are analyzed. The author's definition of instability in foreign economic activity is proposed as a set of unpredictable economic, political, technological, and legal changes that require adaptive behavior of enterprises. The challenges that enterprises face when adapting to changes in customs regulations, trade restrictions, and sanctions are separately considered. Directions for increasing the stability of foreign economic activity in conditions of instability are proposed: diversification of sales markets, digitalization of logistics processes, introduction of flexible risk management strategies, expansion of partnership relations within international integration associations. The need to form an adaptive model of foreign economic policy of enterprises in the automotive industry, which takes into account the multifactorial nature of the risks of the modern global environment, is substantiated. The results of the study can be used in developing strategies for foreign economic activity of enterprises, forming state policy to support export-oriented industries, as well as in scientific research devoted to the issues of economic security and industrial development in order to increase the international stability of Ukrainian automobile manufacturing enterprises.

A. Orloff

T. Bartik

Place-based jobs policies seek to create jobs in particular local labor markets. Such policies include business incentives provided by state and local governments, which cost almost 50 billion USD annually. The most persuasive rationale for these policies is that they can advance equity and efficiency by increasing long-term employment rates in distressed local labor markets. However, current incentives are not targeted at distressed areas. Furthermore, incentives have high costs per job created. Lower costs can be achieved by public services to business, such as manufacturing extension, customized job training, and infrastructure. Reforms to place-based jobs policies should focus on greater targeting of distressed areas and using more cost-effective policies. Such reforms could be achieved by state and local governments acting in their residents' interests or could be encouraged by federal interventions to cap incentives and provide aid to distressed areas.

Eduardo Sá Barreto

O artigo examina o descompasso atual entre a formação científica de economistas e a acelerada transformação de seu objeto, tanto em sua dimensão propriamente socioeconômica quanto em sua dimensão ambiental. Orientada para a temática ecológica, a discussão apresenta as principais tradições de pensamento econômico a ela dedicadas, apontando como as limitações e possibilidades de cada uma refletem os imperativos e impossibilidades do próprio objeto de investigação ao qual se dedicam. Isso fornece uma chave de leitura para entendermos alguns déficits de formação decisivos que povoam a formação corrente de economistas Palavra-chave: Ensino de economia; Economia ambiental; Economia ecológica; Ecologia marxista.

M. D. Volkova, M. S. Kruglova

Objective: to identify the main trends in the studies of the PRC demographic problems by Chinese researchers; to determine the main directions of developments within the concept of demographic dividend in terms of their main problems and prospects for further adjustments in accordance with the ever-changing state demographic policy and the goals of sustainable development.   Methods: qualitative methods (comparative analysis, generalization) of a systematic review of empirical studies.   Results: the main trends and directions of modern Chinese demographic research are highlighted, one of which is the study of demographic processes as an important factor in the development of further trajectory of the PRC sustainable development. It is concluded that Chinese authors often write about the aging population as a competitive advantage of China. They explainthat with a competent economic and demographic policy, the “silver generation” will become an active participant in the economic and production activities of the country, making a noticeable contribution to GDP. We also analyze alternative approaches to the concept of demographic dividend, in which the main factor of China’s economic growth is determined notas the quantity but as the quality of labor force.   Scientific novelty: the article systematizes the works by Chinese researchers in the context of the demographic dividend and identifies their main problems and focuses.   Practical significance: the main conclusions of the article can be used in scientific and pedagogical activities in the study of economic and demographic policy of China. The research results can also be studied to clarify the demographic policy of the Russian Federation.

Melissa Bertolini, Francis Kanashiro Meneghetti

O trabalho discute sobre a apropriação dos fundos públicos na educação pública no Brasil e o protagonismo das grandes corporações privadas nesse âmbito. É um recorte da dissertação defendida junto à Universidade Tecnológica Federal do Paraná, em 2023 e a ideia central é a Lei como um artefato tecnológico e seus propósitos moldados por teleologias pré-estabelecidas, refletindo disputas de poder de uma sociedade e período. Agrega à Teoria dos Artefatos na Ciência Jurídica e sua hermenêutica. A lei é analisada à luz das dimensões de CTS, através da análise crítica da Lei 14.533/2023, sobre a política para a educação digital no país. Palavra-chave: Lei; Artefato Tecnológico; Não Neutralidade; CTS.  

Wenjia Meng, Qian Zheng, Long Yang et al.

Policy-based methods have achieved remarkable success in solving challenging reinforcement learning problems. Among these methods, off-policy policy gradient methods are particularly important due to that they can benefit from off-policy data. However, these methods suffer from the high variance of the off-policy policy gradient (OPPG) estimator, which results in poor sample efficiency during training. In this paper, we propose an off-policy policy gradient method with the optimal action-dependent baseline (Off-OAB) to mitigate this variance issue. Specifically, this baseline maintains the OPPG estimator's unbiasedness while theoretically minimizing its variance. To enhance practical computational efficiency, we design an approximated version of this optimal baseline. Utilizing this approximation, our method (Off-OAB) aims to decrease the OPPG estimator's variance during policy optimization. We evaluate the proposed Off-OAB method on six representative tasks from OpenAI Gym and MuJoCo, where it demonstrably surpasses state-of-the-art methods on the majority of these tasks.

Jeovane Honorio Alves, Radu State, Cinthia Obladen de Almendra Freitas et al.

In an era of information overload, manually annotating the vast and growing corpus of documents and scholarly papers is increasingly impractical. Automated keyphrase extraction addresses this challenge by identifying representative terms within texts. However, most existing methods focus on short documents (up to 512 tokens), leaving a gap in processing long-context documents. In this paper, we introduce LongKey, a novel framework for extracting keyphrases from lengthy documents, which uses an encoder-based language model to capture extended text intricacies. LongKey uses a max-pooling embedder to enhance keyphrase candidate representation. Validated on the comprehensive LDKP datasets and six diverse, unseen datasets, LongKey consistently outperforms existing unsupervised and language model-based keyphrase extraction methods. Our findings demonstrate LongKey's versatility and superior performance, marking an advancement in keyphrase extraction for varied text lengths and domains.

Rita Terezinha Schmidt

We have been living through challenging times, of fear and violence, real and symbolic, as the tentacles of COVID-19 took by assault the world we live in and made even more visible the inequalities among nations, the fragility of democratic political systems and, particularly in some latitudes, the precariousness of human lives under political systems blind to questions related to human rights. In fact, precariousness has been a hallmark in the history of Latin American countries since the so-called “discovery” by Euro-pean conquerors. Specifically in Brazil, under the rule of the Portuguese imperial state, the colonial government consolidated its power by establishing laws of forced labor for indigenous peoples and by the deployment of slave traffic policies that lasted for four centuries. The western colonial legacy in terms of hierarchies of gender, race, and ethnicity outlasts to this day, perpetuating marginalizations, prejudices, violence, and death. This means that the universals of European modernity such as the concept of state, democracy, progress, rationality, and universal citizenship have become tokens of a privileged parcel of the white population. To some extent, the colonization process in Brazil is still going on, producing brutality and destruction in ways unknown to modern Europe. As a comparatist, I believe that the challenges of the present allow us to rethink our intellectual work in terms of discovering new angles to approach questions related to belongingness as well as to examine differences and raise the issue of who has no right to live a livable life, in political and symbolical terms. Such a question demands rethinking our relation to the other as other so then we can meet the other. This move is aligned with a comparatist ethos, that is, a dialogical reasoning oriented towards the other, with respect to differences and with recognition of diversity.

A. Mattoo, N. Rocha, M. Ruta

Deep trade agreements (DTAs) cover not just trade but additional policy areas, such as the international flows of investment and labor, and the protection of intellectual property rights and the environment. Their goal is integration beyond trade, or deep integration. DTA rules influence how countries transact, invest, work, and, ultimately, develop. The rules and commitments in DTAs should be informed by evidence and shaped by development priorities rather than international power or domestic politics. An impediment to this goal is that data and analysis on trade agreements have not captured the new dimensions of integration. Little effort has been made to identify the content and consequences of DTAs. This Handbook takes a step towards filling this gap in our understanding of international economic law and policy. It presents detailed data and analysis on the content of the policy areas most frequently covered in DTAs, focusing on the stated objectives, substantive commitments, and other aspects such as transparency, procedures, and enforcement. Each chapter, authored by lead experts in their respective fields, explains in detail the methodology used to collect the information and provides a first look at the evidence by policy area.