Hasil untuk "Social legislation"

Matthew Flynn, Timothy Obiso, Sam Newman

This paper introduces GELATO (Government, Executive, Legislative, and Treaty Ontology), a dataset of U.S. House and Senate bills from the 118th Congress annotated using a novel two-level named entity recognition ontology designed for U.S. legislative texts. We fine-tune transformer-based models (BERT, RoBERTa) of different architectures and sizes on this dataset for first-level prediction. We then use LLMs with optimized prompts to complete the second level prediction. The strong performance of RoBERTa and relatively weak performance of BERT models, as well as the application of LLMs as second-level predictors, support future research in legislative NER or downstream tasks using these model combinations as extraction tools.

Praveen Hoogar

BackgroundSouth Asia faces concentrated HIV epidemics rooted in legal and social marginalization of key populations. Laws criminalizing same-sex relations, sex work, and drug use, combined with gaps in anti-discrimination protections and funding constraints for civil society organizations, undermine progress toward the UNAIDS 95-95-95 targets. This review applies a rights-based approach (RBA) to compare national policies and outcomes across India, Nepal, Pakistan, and Sri Lanka, and offers actionable regional guidance.MethodsA comparative analysis was performed using a five-dimension RBA framework: legal decriminalization, anti-discrimination protections, service access, community participation, and HIV outcomes. Data were synthesized from national legal documents, UNAIDS and Global Fund reports, published research, and community organization perspectives. Comparative findings are presented in a cross-country table, and an RBA policy-outcome pathway diagram is used to visualize core mechanisms.ResultsIndia and Nepal have partially decriminalized same-sex conduct, while criminalization of sex work and drug use persists in all four countries. Pakistan’s progressive transgender rights legislation faces enforcement and political challenges; Sri Lanka retains colonial-era punitive statutes. Fragile enforcement, limited-service access, and structural health system stigma are common barriers. Where rights-based legal reforms have advanced, as in India and Nepal, higher diagnosis and treatment rates are seen. Four practical pillars—legal reform, health system transformation, funding equity, and regional collaboration—are proposed.ConclusionSustainable HIV epidemic control in South Asia depends on repealing punitive laws, enforcing anti-discrimination protections, and supporting community leadership. Rights-based governance not only drives epidemic control but advances dignity and equity.

Ashutosh Anshul, Gumpili Sai Pranav, Mohammad Zia Ur Rehman et al.

The recent coronavirus disease (Covid-19) has become a pandemic and has affected the entire globe. During the pandemic, we have observed a spike in cases related to mental health, such as anxiety, stress, and depression. Depression significantly influences most diseases worldwide, making it difficult to detect mental health conditions in people due to unawareness and unwillingness to consult a doctor. However, nowadays, people extensively use online social media platforms to express their emotions and thoughts. Hence, social media platforms are now becoming a large data source that can be utilized for detecting depression and mental illness. However, existing approaches often overlook data sparsity in tweets and the multimodal aspects of social media. In this paper, we propose a novel multimodal framework that combines textual, user-specific, and image analysis to detect depression among social media users. To provide enough context about the user's emotional state, we propose (i) an extrinsic feature by harnessing the URLs present in tweets and (ii) extracting textual content present in images posted in tweets. We also extract five sets of features belonging to different modalities to describe a user. Additionally, we introduce a Deep Learning model, the Visual Neural Network (VNN), to generate embeddings of user-posted images, which are used to create the visual feature vector for prediction. We contribute a curated Covid-19 dataset of depressed and non-depressed users for research purposes and demonstrate the effectiveness of our model in detecting depression during the Covid-19 outbreak. Our model outperforms existing state-of-the-art methods over a benchmark dataset by 2%-8% and produces promising results on the Covid-19 dataset. Our analysis highlights the impact of each modality and provides valuable insights into users' mental and emotional states.

Zvarych Olena I., Voloshyn Volodymyr V.

Demographic challenges and structural imbalances in Ukraine’s solidarity-based pension system underscore the need to develop alternative mechanisms for providing pensions to the population. The non-State pension insurance, as a component of a multi-tier pension architecture, requires conceptual reconsideration and modernization in line with European standards and national specifics. The aim of this study is to identify the key directions for transforming Ukraine’s non-State pension insurance system and to develop mechanisms for its optimization, ensuring long-term financial stability and social protection for citizens. The study is based on a comprehensive approach combining comparative analysis of global experience, statistical analysis of the development dynamics of the domestic market, and expert evaluation of regulatory initiatives. Priority directions for improvement have been identified, including: flexible models of accumulative insurance, diversification of pension fund investment instruments from a risk management perspective, enhancing the transparency of market participants, strengthening the corporate segment through the creation of incentivizing fiscal mechanisms, and digitalizing administration. The necessity of harmonizing national legislation with European Union directives on pension provision and implementing a deposit guarantee system has been substantiated. It is found that the systematic modernization of the non-State pension insurance requires synchronization of institutional, regulatory, and fiscal reforms, which will ensure the development of a competitive segment of the financial market and foster increased public trust in the non-State pension programs as a reliable tool for securing a decent standard of living in old age. The implementation of the proposed measures will provide a real opportunity to align the Ukrainian model of the non-State pension insurance with the best European practices and enhance its efficiency in the context of demographic transition.

Chengyi Liu, Jiahao Zhang, Shijie Wang et al.

With the prevalence of social networks on online platforms, social recommendation has become a vital technique for enhancing personalized recommendations. The effectiveness of social recommendations largely relies on the social homophily assumption, which presumes that individuals with social connections often share similar preferences. However, this foundational premise has been recently challenged due to the inherent complexity and noise present in real-world social networks. In this paper, we tackle the low social homophily challenge from an innovative generative perspective, directly generating optimal user social representations that maximize consistency with collaborative signals. Specifically, we propose the Score-based Generative Model for Social Recommendation (SGSR), which effectively adapts the Stochastic Differential Equation (SDE)-based diffusion models for social recommendations. To better fit the recommendation context, SGSR employs a joint curriculum training strategy to mitigate challenges related to missing supervision signals and leverages self-supervised learning techniques to align knowledge across social and collaborative domains. Extensive experiments on real-world datasets demonstrate the effectiveness of our approach in filtering redundant social information and improving recommendation performance.

Edoardo Allegrini, Edoardo Di Paolo, Marinella Petrocchi et al.

Social media platforms continue to struggle with the growing presence of social bots-automated accounts that can influence public opinion and facilitate the spread of disinformation. Over time, these social bots have advanced significantly, making them increasingly difficult to distinguish from genuine users. Recently, new groups of bots have emerged, utilizing Large Language Models to generate content for posting, further complicating detection efforts. This paper proposes a novel approach that uses algorithms to measure the similarity between DNA strings, commonly used in biological contexts, to classify social users as bots or not. Our approach begins by clustering social media users into distinct macro species based on the similarities (and differences) observed in their timelines. These macro species are subsequently classified as either bots or genuine users, using a novel metric we developed that evaluates their behavioral characteristics in a way that mirrors biological comparison methods. This study extends beyond past approaches that focus solely on identical behaviors via analyses of the accounts' timelines. By incorporating new metrics, our approach systematically classifies non-trivial accounts into appropriate categories, effectively peeling back layers to reveal non-obvious species.

Rhett Hanscom, Tamara Silbergleit Lehman, Qin Lv et al.

Social media platforms have evolved rapidly in modernity without strong regulation. One clear obstacle faced by current users is that of toxicity. Toxicity on social media manifests through a number of forms, including harassment, negativity, misinformation or other means of divisiveness. In this paper, we characterize literature surrounding toxicity, formalize a definition of toxicity, propose a novel cycle of internet extremism, list current approaches to toxicity detection, outline future directions to minimize toxicity in future social media endeavors, and identify current gaps in research space. We present a novel perspective of the negative impacts of social media platforms and fill a gap in literature to help improve the future of social media platforms.

Iman Sinha, Alipta Bhattacharya, Sabari Bhattacharya et al.

Introduction: End stage diseases warrant organ transplantation as the ultimate life saving treatment modality. The purpose of this study was to evaluate and assess the level of knowledge, attitude and perception pertaining to various technical, legal and social aspects of the topic of organ donation, including the role of ‘Transplant coordinator’, among college students of nursing and allied paramedical courses in a tertiary care hospital in West Bengal. Materials and methods: The study was carried out in nursing and paramedical students of a tertiary care hospital in West Bengal. It was based on a questionnaire which sought information on the background knowledge about organ donation, knowledge about legislative provisions and organizational set up governing the procedures of organ donation in India and individual and impersonal attitudes and perceptions about the subject. Results: The study results show that most of the participants had a preliminary acquaintance with the concept of organ donation. The source of information for our participants were largely from social media (36%), television (23%). Lacunae were noted regarding the concept of living organ donation regarding the knowledge regarding ‘Brain death’ and the procedure of its evaluation, 33% of our respondents answered correctly. Mere 19.6 % of our subjects were aware of the existence of a legislation regarding organ donation in our country. Role of family members’ consent was found to be more important than individual consent for pledging organ donation.41 % subjects had some incomplete knowledge about the role of transplant coordinators in organ donation. The study brings out the inadequate knowledge persisting even among the nursing and paramedical students about the complete role of a transplant coordinator. Conclusion: Knowledge about technical and legal aspects of organ donation is inadequate among the subjects. Social media can act as a powerful tool for awareness generation among the masses. There is grossly inadequate knowledge about the proper role of transplant coordinator. Given the opportunity of proper training, the nursing and paramedical students can be encouraged to take up the role of a transplant coordinator of the institute and serve their role in the whole process efficiently.

Sophie Robin-Olivier

(Series Information) European Papers - A Journal on Law and Integration, 2023 8(3), 1213-1220 | European Forum Insight of 22 January 2024 | (Table of Contents) I. Introduction. - II. La distinction entre le droit de la non-discrimination et la législation sociale de l’Union. - III. L’identification d’une catégorie des travailleurs indépendants bénéficiant du droit de la non-discrimination. - IV. Un rapprochement du régime du travail des travailleurs indépendants et salariés. - V. Conclusion | (Abstract) From an EU social law perspective, the decision of the Court of justice in J.K. appears prima facie to be a step forward in the construction of a universal labour law regime. However, the case strictly limits the progress towards an assimilation of the situation of employees and self-employed, in EU social law. First, by distinguishing EU anti-discrimination law and social legislation, only the former being extended to self-employed. Second, by limiting the category of self-employed who can benefit from anti-discrimination law. The case nonetheless suggests that a universal labour law regime can be constructed by using basic notions of labour law for the regulation of other types of contractual relationships than employment contracts.

Minje Choi, David Jurgens, Daniel M. Romero

Individuals experiencing unexpected distressing events, shocks, often rely on their social network for support. While prior work has shown how social networks respond to shocks, these studies usually treat all ties equally, despite differences in the support provided by different social relationships. Here, we conduct a computational analysis on Twitter that examines how responses to online shocks differ by the relationship type of a user dyad. We introduce a new dataset of over 13K instances of individuals' self-reporting shock events on Twitter and construct networks of relationship-labeled dyadic interactions around these events. By examining behaviors across 110K replies to shocked users in a pseudo-causal analysis, we demonstrate relationship-specific patterns in response levels and topic shifts. We also show that while well-established social dimensions of closeness such as tie strength and structural embeddedness contribute to shock responsiveness, the degree of impact is highly dependent on relationship and shock types. Our findings indicate that social relationships contain highly distinctive characteristics in network interactions and that relationship-specific behaviors in online shock responses are unique from those of offline settings.

Tanvir Islam, Anika Rahman Joyita, Md. Golam Rabiul Alam et al.

The traditional dietary recommendation systems are basically nutrition or health-aware where the human feelings on food are ignored. Human affects vary when it comes to food cravings, and not all foods are appealing in all moods. A questionnaire-based and preference-aware meal recommendation system can be a solution. However, automated recognition of social affects on different foods and planning the menu considering nutritional demand and social-affect has some significant benefits of the questionnaire-based and preference-aware meal recommendations. A patient with severe illness, a person in a coma, or patients with locked-in syndrome and amyotrophic lateral sclerosis (ALS) cannot express their meal preferences. Therefore, the proposed framework includes a social-affective computing module to recognize the affects of different meals where the person's affect is detected using electroencephalography signals. EEG allows to capture the brain signals and analyze them to anticipate affective toward a food. In this study, we have used a 14-channel wireless Emotive Epoc+ to measure affectivity for different food items. A hierarchical ensemble method is applied to predict affectivity upon multiple feature extraction methods and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is used to generate a food list based on the predicted affectivity. In addition to the meal recommendation, an automated menu planning approach is also proposed considering a person's energy intake requirement, affectivity, and nutritional values of the different menus. The bin-packing algorithm is used for the personalized menu planning of breakfast, lunch, dinner, and snacks. The experimental findings reveal that the suggested affective computing, meal recommendation, and menu planning algorithms perform well across a variety of assessment parameters.

Kavita Thakur, Gracia Sohkhlet, Sudeep David et al.

Introduction: Stroke is one of the leading causes of death and disability in India and rehabilitation therapy is underdeveloped. Neurorehabilitation is a program that caters to people who have disabilities to help them attain and maintain optimal performance. The majority of people with disabilities are economically underprivileged and have trouble getting access to basic health care (including rehabilitation). Physiotherapists also face limitations in providing services to stroke survivors and this study is to identify those challenges. Objective: The objective of this study is to identify the limitations faced by physiotherapists during stroke rehabilitation. Material and Method: In November 2022, a focus group discussion was held with a sample size of 12 physiotherapy residents from neurorehabilitation and community rehabilitation working in a tertiary hospital. After consent was taken, audiovideography was recorded, transcripted, and documented. Data were thoroughly transcribed, and thematic analysis and characteristics were established. Results: After extraction of codes and themes, the following results were found. General categories of themes are lack of awareness on stroke and physiotherapy, infrastructure, financial constraints, family dynamic, social health, amotivation and mental health, collaboration limitations, problems in-home services, and the impact of COVID-19 pandemic on rehabilitation. Recommendations given by the participants were creating a stroke community, availability of more insurance companies to support and provide relief for financial stress, early education and awareness on stroke from school level, active participation of caregivers and family members to assist the patient in home-based therapy, and availability of NGOs that cater specifically to physiotherapy. Conclusion: It was concluded that neurorehabilitation in India needs to attend to the given categories. Policymakers must be aware of the financial and social issues that stroke survivors experience and enact legislation that will decrease mental and financial stress.

Seda Yurtcanlı Duymaz

Along with other causes of migration, earthquakes have displaced millions of people worldwide over the last few decades, forcing them to move to other settlements within the country. As an "earthquake country", Turkey, where approximately 70% of its territory is located in the seismic zone, has faced a variety of environmentally forced migration that refers to a variety of demographic movements like evacuation, flight, displacement, resettlement, as well as forced migration. Disasters and disaster-related forced migrations as an aspect of survival anxiety have severe and irreversible consequences for the existence of physical security, human dignity, health, livelihoods, shelter, and social, economic, and cultural structures and processes of societies or their subunits. Therefore, disasters and disaster-induced migration, which can be defined as a process of significant vulnerability, are considered widespread and severe threats to the enjoyment and realisation of fundamental rights. Earthquake-related forced migration phenomenon is a widespread and high-risk factor, and this risk corresponds to a closer and more destructive possibility for the province of Istanbul. Therefore becomes vital to take preventive measures to mitigate the possible destructive effects as well as to eliminate the risks as much as possible. This study aims to determine whether relevant legislation is adequate to provide an effective and sufficient protection mechanism for environmental displacement that may occur in Istanbul after a significant earthquake for the purpose of “building resilience in crisis” in the view of international standards. Thus, it also emphasises the importance of the human rights approach and legal mechanisms in establishing resilience during crises. This study has been prepared by content analysing the disaster and emergency preparedness plans, policy texts, and relevant legal and regulatory provisions related to understanding and managing the earthquake-induced migration scenario in Istanbul.

Faranak Mahzari, Batool Pakzad, hasan alipour et al.

In the issue of immigrants, the existing laws are mainly influenced by public opinion, political discussions, monitoring and security feedback regarding the arrangement of the responsible institutions. In this article, with a descriptive and analytical view, the approach of the legal system in the social prevention of immigrants' delinquency is discussed with reference to international and domestic laws, the principles of prevention and the attitude of the host society, and in the policy discourse in the country, considering the existing challenges, this result It can be said that the current laws are mainly security-oriented, discriminatory and ignoring a large number of immigrants who live in the country illegally, and unfortunately, the reflection of public opinion is also in the continuation of such an attitude. While in this area, the establishment of strategic laws and It is necessary to draw a far-reaching policy from the human dimension and human rights and an in-depth, non-discrimination and threat-oriented approach in organizing the affairs of immigrants, both legal and illegal, in the social sphere, with a differentiated, coherent and codified policy in order to attach the issues Incident and new, taking into account the alien component, but being human, both in the legislation and in the use of preventive tools, with the coordination of related institutions and organizations, to enlighten the minds of the society, to prevent the decision making, and to protect the country's security, to succeed in reducing and eradicating the delinquency of immigrants in P Achieved social recognition.

Susana Mourão, Sara Pinheiro, Maria Manuela Mendes et al.

The COVID-19 pandemic forced the Portuguese government to declare various lockdowns between 2020 and 2022. The first State of Emergency was enforced in March 2020, in which face-to-face classroom teaching was repeatedly interrupted. At that time, families were expected to provide the necessary supplies for digital learning, with some support from the government, municipalities, civil society, and local institutions. Nevertheless, many families already lived under precarious conditions before the pandemic, and so the lockdown measures increased their vulnerability, with a probable impact on student school attendance and conditions enabling academic success. Since Ciganos/Roma are part of this vulnerable population, we intend to explore how the COVID-19 pandemic impacts the school pathways of these students, namely in secondary education, where they represent a minority group. The data are derived from a variety of qualitative sources collected during research carried out in the two Metropolitan Areas in Portugal. The COVID-19 pandemic affected the youngsters’ access to classes and their motivation to attend school, and opens the discussion about how because of the government’s universal measures, by failing to consider social diversity, in particular Ciganos/Roma Ciganos/Roma families, this pandemic crisis may disproportionally affect the education of their children and youth. The findings highlight, firstly, that these impacts continue to be rendered invisible and naturalized in the public sphere and, secondly, that the measures and legislation underlying the pandemic effects continue not to include Ciganos in policymaking processes.

Hiroki Sayama

Social fragmentation transition is a transition of social states between many disconnected communities with distinct opinions and a well-connected single network with homogeneous opinions. This is a timely research topic with high relevance to various current societal issues. We had previously studied this problem using numerical simulations of adaptive social network models and found that two individual behavioral traits, homophily and attention to novelty, had the most statistically significant impact on the outcomes of social network evolution. However, our previous study was limited in terms of the range of parameter values examined, and possible interactions between multiple behavioral traits were largely ignored. In this study, we conducted a substantially larger-scale parameter sweep numerical experiment of the same model with expanded parameter ranges by an order of magnitude in each parameter dimension, resulting in a total of 116,640 simulation runs. To capture nontrivial interactions among behavioral parameters, we modeled and visualized the dependence of outcome measures on the model parameters using artificial neural networks. Results show that, while the competition between homophily and attention to novelty is still the primary determinant of social fragmentation, another transition plane emerges when individuals have strong social conformity behavior, which was not previously known. This implies that social fragmentation transition can also occur in the homophily-social conformity trade-off, the two behavioral traits that have very similar microscopic individual-level effects but produce very different macroscopic collective-level outcomes, illustrating the nontrivial macroscopic dynamics of complex collective systems.

Tatiana S. Soloveva

Introduction. International experience shows that social innovation is an important tool for regional development, although this type of innovation is a relatively new phenomenon for Russia. On the basis of the research conducted, the article analyzes the conditions for the implementation of social innovation which has a significant potential to meet the challenges of territorial development. Materials and Methods. Based on materials from open sources, as well as on an expert survey conducted by the Vologda Research Center of the Russian Academy of Sciences with the direct participation of the author, the conditions for the implementation of social innovation prevailing in the constituent entities of the Northwestern Federal District of the Russian Federation were analyzed in the context of legal, infrastructural, economic, and socio-cultural components. Using the results of the expert survey, a quantitative assessment of the level of development of the conditions for the implementation of social innovation was given. The main barriers preventing the reproduction of social innovation within the territory under consideration were revealed. Results. The study has revealed that in the regions of the Northwestern Federal District the conditions for the implementation of social innovation are at the stage of active development: infrastructure and legislation are being formed; financial, tax and property support is being provided; educational programs are being implemented. The study has also shown that there are a number of problematic aspects associated with the underdevelopment of the regulatory framework, with the lack of Centers for innovation in the social sphere in a number of constituent entities, with the limited availability of some financial instruments, with low social and innovative activity of people, etc. Discussion and Conclusion. The results obtained are supported by other studies, which substantiates the need for policy adjustment towards improving the relevant regulatory framework, economic conditions, infrastructure, and socio-cultural environment. The research materials can be used by regional authorities when making managerial decisions to support social innovation; they can also be useful for further studies within the framework of the issues under consideration.

Jina Park, Ick Hoon Jin, Minjeong Jeon

How social networks influence human behavior has been an interesting topic in applied research. Existing methods often utilized scale-level behavioral data to estimate the influence of a social network on human behavior. This study proposes a novel approach to studying social influence that utilizes item-level behavioral measures. Under the latent space modeling framework, we integrate the two interaction maps for respondents' social network data and item-level behavior measures. The interaction map visualizes the association between the latent homophily of the respondents and their behaviors measured at the item level in a low-dimensional latent space, revealing the potential, differential social influence effects across specific behaviors measured at the item level. We also measure overall social influence as the impact of the interaction map configuration contributed by the social network data on the behavior data. The performance and properties of the proposed approach are evaluated via simulation studies. We apply the proposed model to an empirical dataset to demonstrate how the students' friendship network influences their participation in school activities.

Nur Handayani, Johar Amir, Juanda Juanda

ABSTRAK: Penelitian ini berfokus pada kajian linguistik forensik yang membahas mengenai Kasus Hoaks Pandemi Covid-19 yang beredar di media sosial. Adapun tujuan penelitian ini mendeskripsikan kategori kasus hoaks Covid-19 dan menganalisis karakteristik kebahasaan pada kasus kejahatan berbahasa yakni kasus hoaks dimasa pandemi Covid-19. Data dalam penelitian ini didapatkan melalui laman resmi kementrian komunikasi dan informatika (kemenkominfo). Teknik pengumpulan data dilakukan dengan teknik dokumentasi, teknik baca, teknik catat. Proses analisis data dalam mendeskripsikan kategori hoaks pandemi Covid-19 dengan mengidentifikasi data berdasarkan pemahaman teori kasus hoaks dan memahami hukum sesuai peraturan perundang-undangan. Sedangkan dalam proses menganalisis karakteristik kebahasaan pada kasus hoaks pandemi Covid-19 dengan menggunakan pendekatan semantik, sintaksis dan teori konteks Halliday. Hasil dalam penelitian ini terdapat dua bentuk kategori kasus hoaks mengenai pandemi Covid-19 yang banyak beredar di sosial media, yakni kasus hoaks berjenis misinformasi dan kasus hoaks berjenis disinformasi. Hasil analisis karakteristik kebahasaan yang menjadi penanda kebohongan berupa 1) penggunaan kosa-kata atau diksi 2) bentuk kalimat pada teks kasus hoaks 3) analisis konteks berisi fakta serta tujuan pelaku. KATA KUNCI: Covid-19; hoaks; linguistik forensik.   THE CASE OF THE COVID-19 PANDEMIC HOAX: AN OVERVIEW OF FORENSIC LINGUISTICS  ABSTRACT: This research focused on forensic Linguistic Review which discussed about hoax case of Covid-19 pandemic circulated in social media. The purpose of this research is to describe the category of Covid-19 hoaxes and to analyze the linguistics’ characteristic of language wickedness’ case which is hoax case of Covid-19 pandemic. The date in this research was gained by the official website of the Ministry of Communications and Informatics. The techniques of data collection were documentation technique, reading technique, and notepad technique. The process of data analysis to describe the category of Covid-19 hoaxes were data identification based on theoretical comprehension of hoax cases and legislation-based-law comprehension. Meanwhile, in processes of linguistics’ characteristic analysis on the hoax case of Covid-19 pandemic were semantics approach, syntax and Halliday context theory. The result of this research found that there are two categories on hoax case of Covid-19 pandemic which were circulating in social media, namely hoax cases caused by misinformation and hoax cases caused by disinformation. The linguistics’ characteristic that became the sign of lies are 1) the using of vocabulary and diction; 2) the sentence structure in the hoax case text; 3) the context analysis which includes the fact and the goals of the perpetrators. KEYWORDS: Covid-19; forensic linguistics, hoax.

Jorge Luis Silva González, Sandys Menoya Zayas

Los estudios relacionados con la equidad de género en el ámbito de las relaciones laborales son de trascendental importancia a escala global. En tal sentido, el presente estudio ofrece una valoración sobre la protección jurídica del derecho de la trabajadora a la maternidad en las formas de gestión de la economía cubana, teniendo en cuenta el Principio constitucional de igualdad y no discriminación que debe regir para todas las mujeres con independencia de su vínculo laboral. Para ello, con el empleo de los métodos histórico-jurídico, jurídico-doctrinal y el de comparación jurídica, se sistematizan los referentes doctrinales, históricos y jurídicos del derecho a la maternidad, y se analiza desde la perspectiva de la equidad su estado actual en los regímenes especiales de seguridad social, correspondientes. Studies related to gender equality in the field of labor relations are of transcendental importance on a global scale. In this sense, this study offers an assessment of the legal protection of the worker's right to motherhood in the forms of management of the Cuban economy, taking into account the constitutional principle of equality and non-discrimination that must govern for all women. Regardless of your employment relationship. For this, with the use of the historical-legal, legal-doctrinal and legal comparison methods, the doctrinal, historical and legal references of the right to maternity are systematized, and its current status in the Corresponding special social security regimes. Available from: https://doi.org/10.35295/osls.iisl/0000-0000-0000-1184