ethicalabs/Research-Intent-Collab huggingface dataset:
Is Transparency Enough? An Examination of the Effect of the Extractive Industry Initiative (EITI) on Accountability, Corruption and Trust in Zambia

Extractive industry governance is a hot topic in both academic research and the public arena. The area that has been most heavily studied in the academic field is the resource curse, which documents the negative effects of dependence on resource-rents in resource-rich developing countries. The political strand of this literature argues that a strong dependence on resource-rents negatively impacts three governance outcomes: accountability, corruption and trust. Scholars argue that these governance issues can be improved if transparency is increased, which inspired the creation of the Extractive Industry Transparency Initiative (EITI). The EITI is a transnational non-governmental organisation launched in 2002, with the aim of improving accountability, corruption and trust in the extractive industry by increasing transparency in the sector. In order to be EITI-compliant, countries must make key documents and data from their extractive industry publicly available and form a multi-stakeholder group with members of civil society organisations (CSOs), extractive industry and government representatives to oversee reporting. Summary of ICTD Working Paper 175.
Physical Mechanism of a Solar Flare Based on the Accumulation of the Energy in the Magnetic Field of the Current Sheet in the Solar Corona

During a solar flare, the magnetic energy of ~1032 erg is released in a few dozens of minutes. The invariability of the magnetic field on the solar surface during flares proves the appearance of a flare in the corona. An analysis of the dynamics of the electron temperature of the solar atmosphere provides independent evidence of the coronal origin of the flare. The appearance of the flare in the corona is explained by the release of the energy accumulated in the magnetic field of the current sheet. To study the flare situation, numerical MHD simulation was performed for a real active region. The simulation results showed the appearance of a current sheet, which position coincides with the position of the observed source of thermal X-ray emission. A methodology for calculations in real time scale has been developed. Based on the mechanism of energy release in the current sheet, an electrodynamic model of a solar flare is proposed, which explains its main observed manifestations. Sources of hard X-ray emission appear due to deceleration in the lower dense layers of the solar atmosphere of electron beams accelerated in field-aligned currents. The acceleration of solar cosmic rays occurs in the current sheet by the electric field E = –V × B/c, and not in shock waves.
A Modelling Framework for Addressing the Synergies between Global Conventions through Land Use Changes: Carbon Sequestration, Biodiversity Conservation, Prevention of Land Degradation and Food Security in Agricultural and Forested Lands in Developing Countries

This paper proposed a methodological framework for the assessment of carbon stocks and the development and identification of land use, land use change and land management scenarios, whereby enhancing carbon sequestration synergistically increases biodiversity, the prevention of land degradation and food security through the increases in crop yields. The framework integrates satellite image interpretation, computer modelling tools (i.e. software customization of off-the-shelf soil organic matter turnover simulation models) and Geographical Information Systems (GIS). The framework addresses directly and indirectly the cross-cutting ecological concerns foci of major global conventions: climate change, biodiversity, the combat of desertification and food security. Their synergies are targeted by providing procedures for assessing and identifying simultaneously carbon sinks, potential increases in plant diversity, measures to prevent land degradation and enhancements in food security through crop yields, implicit in each land use change and land management scenario. The scenarios aim at providing 'win-win' options to decision makers through the framework's decision support tools. Issues concerning complex model parameterization and spatial representation were tackled through tight coupling soil carbon models to GIS via software customization. Results of applying the framework in the field in two developing countries indicate that reasonably accurate estimates of carbon sequestration can be obtained through modeling; and that alternative best soil organic matter management practices that arrest shifting 'slash-and-burn' cultivation and prevent burning and emissions, can be identified. Such options also result in increased crop yields and food security for an average family size in the area, while enhancing biodiversity and preventing land degradation. These options demonstrate that the judicious management of organic matter is central to greenhouse gas mitigation and the attainment of synergistic ecological benefits, which is the concern of global conventions. The framework is to be further developed through successive approximations and refinement in future, extending its applicability to other landscapes.
SUN: Stochastic UNsupervised Learning for Data Noise and Uncertainty Reduction

Unsupervised learning methods significantly benefit various practical applications by effectively identifying intrinsic patterns within unlabelled data. However, inherent data noise and uncertainties often compromise model reliability, result interpretability, and the overall effectiveness of unsupervised learning strategies, particularly in complex fields such as biomedical, engineering, and physics research. To address these critical challenges, this study proposes SUN (Stochastic UNsupervised learning), a novel approach that integrates probabilistic unsupervised techniques—specifically Gaussian Mixture Models—into the RUN-ICON unsupervised learning algorithm to achieve optimal clustering, systematically reduce data noise, and quantify inherent uncertainties. The SUN methodology strategically leverages probabilistic modelling for robust classification and detection tasks, explicitly targeting particle dispersion scenarios related to environmental pollution and airborne viral transmission, with implications for minimising public health risks. By combining advanced uncertainty quantification methods and innovative unsupervised denoising techniques, the proposed study aims to provide more reliable and interpretable insights than conventional methods while alleviating issues such as computational complexity and reproducibility that limit traditional mathematical modelling. This research contributes to enhanced trustworthiness and interpretability of unsupervised learning systems, offering a robust methodological framework for handling significant uncertainty in complex real-world data environments.
The Impact of Social Media on Adolescent Mental Health

The widespread use of social media and the changing patterns in adolescent mental health issues has sparked a multifaceted debate around the influence of social media on teenage mental health. The world of virtual socialisation being a unique and very recent problem in human history, the evidence base is continuously evolving. We examined the literature in the last five years, anchoring the evidence on a balanced theoretical frame work, to understand the nuances of this complex relationship. There is a significant influence of social media use on adolescents in general, determined by their unique developmental vulnerabilities and heavily influenced by the sociocultural aspects and type and duration of social media use. The sheer infinite nature of the virtual world and removal of traditional barriers to socialisation has exposed the youth to influences that were hitherto unknown. We found strong evidence in literature to support the amplification of negative emotions in adolescence, contributing to the rapidly increasing incidence of teenage depression and anxiety and even suicidal tendencies. However there is also good evidence to support the positive effects of social media on adolescents, especially so in certain groups and communities. Moreover the evidence is likely to change as we are becoming more digitally resilient and safer practices and regulations continue to evolve and this is an important space to watch for future researchers and practitioners.
The EU's Racial Equality Directive and the Evolution of Discourse in the Field of the Fight against Discrimination. a Comparison between France, the UK and Spain

This paper assesses the extent of the convergence of public policies purporting to combat racial discriminations in Europe by focusing on the cases of France, the UK and Spain. It shows that the influence of ‘national models’ remains powerful even when the implementation of a common policy instrument such as a European directive is at stake - in this instance the Racial Equality Directive of 29 June, 2000. Having outlined the reasons for focusing on this directive, we propose a synthesis of sociological and political science studies on the subject and present our comparative methodological approach in detail. We focus on the language employed to present the discrimination problem in all three countries under study. We first examine the French case and retrace the progressive evolution of the rhetoric used, from an emphasis on the fight against racism to equal opportunities and the promotion of diversity. Having thus observed the medium-term impact of national socio-political dynamics on a European frame of reference for action, we introduce a comparison with Spain and the UK, relying on documents produced by European institutions.
The Independence of Prosecutors: Cornerstone of the Rule of Law and Precondition for the Overall Independence of a Judicial System

AbstractIt is clear that in the current crisis of the Rule of Law, that in recent years harvested a systematic weakening of the independence of the judiciary in Europe (and its sheer disappearance in Turkey, Hungary and Poland), what is endangered are the rights and freedoms of citizens.
Health Insurance Coverage and Access to Care Among Older Immigrants: Evidence from the National Health Interview Survey, 2020 to 2023

Health insurance coverage is essential to improving preventative health services and decreasing financial burdens for older immigrants; however, disparities remain among different insurance kinds. This study analyzes the influence of private, public, and uninsured coverage on healthcare access and financial vulnerability among elderly immigrants in the United States, a population disproportionately impacted by socioeconomic and administrative obstacles. This cross-sectional study used data from the National Health Interview Survey (NHIS) covering 2020 to 2023 sourced from IPUMS, focusing on foreign-born persons aged 60 years and older. Weighted logistic regression models and propensity score adjustments were used to assess the associations between insurance type (private, Medicare, Medicaid, or uninsured) and 3 outcomes: access to regular care, financial strain, and unmet need due to cost. Analyses addressed age, sex, education, and economic status as confounding through using survey weights and complex design alterations. Results indicate that people with private insurance had significantly higher chances of having an ongoing source of care (OR = 1.54, 95% CI = 0.98-2.42) and decreased odds of having unmet healthcare demands (OR = 0.59, 95% CI = 0.39-0.90) compared to the uninsured population. Medicare coverage had a positive association with regular medical treatment (OR = 2.21, 95% CI = 1.34-3.64). No significant correlations have been identified between insurance type and financial strain. Gender and age variations persisted, with women showing somewhat reduced odds of receiving regular care. The findings demonstrate that health insurance coverage improves access to preventive care however does not eliminate financial stress among senior immigrants. Policy efforts must enhance fair coverage, address obstacles to Medicaid and Medicare access, and integrate culturally appropriate care for aging immigrant populations.
ACHIEVING SUSTAINABLE FOOD SECURITY IN EBONYI STATE THROUGH URBAN AGRICULTURE

This study investigated achieving sustainable food security in Ebonyi State through urban agriculture. A descriptive survey design was adopted for the study. The population of the study was 300 urban farmers across the state, comprising of 150 males and 150females and this population formed the sample size for the study. Some concepts were clarified. A 3 in-1 instrument titled sustainable food security through urban agriculture (SFSTUAQ) was used for data collection. Three research questions and three hypotheses guided the study. The research questions were answered using mean rating t-test. The findings of the study revealed that there was a high level of awareness and participation among urban farmers due to encouragement from government. It was therefore recommended that co-opting urban farmers into co-operative societies will help immensely in reducing urban poverty.
BETWEEN THE SURVEILLANCE DUTY AND THE RIGHT TO PRIVACY OF CHILD AND ADOLESCENT

O reconhecimento do menor como sujeito de direito e o perfil funcional da família em favor do bem estar e do desenvolvimento da autonomia e personalidade dos seus membros provocaram alterações no instituto do poder familiar, em que os pais colecionam posições jurídicas. Com o avançar do desenvolvimento da criança, sua capacidade de realizar escolhas livres e responsáveis se amplia. A considerar a privacidade e intimidade das crianças e adolescentes questiona-se acerca de eventual conflito com o dever de cuidado e vigilância inerente ao poder familiar. O texto indaga sobre eventual direito à privacidade e intimidade do menor em face dos pais, averiguando a sua conciliação com os deveres da autoridade parental. A premissa central que se adota é a de que a intromissão na intimidade somente se justifica no melhor interesse do menor.
Probabilistic Time Series Forecasting with Implicit Quantile Networks

Here, we propose a general method for probabilistic time series forecasting. We combine an autoregressive recurrent neural network to model temporal dynamics with Implicit Quantile Networks to learn a large class of distributions over a time-series target. When compared to other probabilistic neural forecasting models on real- and simulated data, our approach is favorable in terms of point-wise prediction accuracy as well as on estimating the underlying temporal distribution.
X-Ray Polarization of the Black Hole X-Ray Binary 4U 1630–47 Challenges the Standard Thin Accretion Disk Scenario

Abstract                A large energy-dependent X-ray polarization degree is detected by the Imaging X-ray Polarimetry Explorer (IXPE) in the high-soft emission state of the black hole X-ray binary 4U 1630–47. The highly significant detection (at ≈50σ confidence level) of an unexpectedly high polarization, rising from ∼6% at 2 keV to ∼10% at 8 keV, cannot be easily reconciled with standard models of thin accretion disks. In this work, we compare the predictions of different theoretical models with the IXPE data and conclude that the observed polarization properties are compatible with a scenario in which matter accretes onto the black hole through a thin disk covered by a partially ionized atmosphere flowing away at mildly relativistic velocities.
Difference between special relativistic gravitational theory and general relativity: Weak field limit

In the case of weak fields, we compare the gravitational fields and the dynamical equation of a particle deduced from special relativistic gravitational theory with the corresponding results deduced from general relativity. Then both gravitational theories can be tested by experiments.
Privacy-Preserving Text Summarization through Differentially Private Federated Learning with Transformer Models

Abstract         As the need for safe and effective information processing grows, text summarization has become a crucial Natural Language Processing (NLP) application field. In this paper, the new Transformer based privacy-preserving summarisation system is presented. It combines popular transformer models, such as Sequence-to-Sequence, Text-to-Text Transfer Transformer (T5), Bidirectional and Auto-Regressive Transformers (BART), Multilingual BART, and Pre-training with Extracted Gap sentences for Abstractive Summarisation (Pegasus), in a differentially private federated learning setting. Through the architecture, privacy risks are reduced, and collaborative model training is made possible by guaranteeing that raw text data stays localized among decentralized clients. Extensive experiments are carried out on the CNN/DailyMail and XSum datasets, using both extractive and abstractive summarisation paradigms. The findings show that Pegasus regularly outperforms other assessment measures (BLEU-4 at 32.0 and ROUGE-L at 44.1) outperforming other models by 14.43% and 11.78% on average, compared to the BART and mBART models in a federated environment. Performance patterns throughout communication cycles demonstrate the effectiveness of the FedAvg aggregation strategy, as the quality of the model gradually improves. This study compares the computational efficiency, generalizability, and complexity of the model under circumstances that preserve privacy. The results aid in the creation of intelligent summarisation systems that strike a compromise between language quality, scalability, and privacy; these systems may find use in cross-border information systems, healthcare, and the legal sector.
&lt;div&gt;  Biometric Self-Ownership in Generative Artificial Intelligence&amp;nbsp; &lt;/div&gt; &lt;div&gt;  A Normative Policy Proposal on Identity Protection at the Point of Content Creation &lt;/div&gt;

Generative artificial intelligence systems increasingly enable the creation of highly realistic representations of identifiable human beings. While these systems offer significant creative and technological opportunities, they also introduce a structural risk: the non-consensual use of biometric identifiers such as facial images, voice patterns, and recognizable human likenesses. Existing legal frameworks largely address such risks only after harm has occurred, relying on post-hoc enforcement mechanisms rather than preventive design constraints. This paper advances the principle of Biometric Self-Ownership as a normative boundary for generative AI systems. It argues that individuals should be permitted to generate AI-based content using only their own verified biometric data, unless explicit, verifiable, and revocable consent has been provided by the data subject. The proposal deliberately focuses on regulation at the moment of content generation, rather than downstream liability. The paper adopts a policy-oriented and rights-based approach rather than a technical or empirical one. It demonstrates that a verification-based restriction is technically feasible, legally coherent with existing data protection and human rights frameworks, and compatible with creative freedom. The objective is not to restrict innovation, but to establish a clear ethical and legal boundary around the use of human identity in generative AI systems.
Testing Accretion Disk Theory in Black Hole X‐Ray Binaries

15 pages, emulateapj, ApJ, in press
Reformulating computational social science with citizen social science: the case of a community-based mental health care research

Abstract                   Computational social science is being scrutinised and some concerns have been expressed with regards to the lack of transparency and inclusivity in some of the researches. However, how computational social science can be reformulated to adopt participatory and inclusive practices? And, furthermore, which aspects shall be carefully considered to make possible this reformulation? We present a practical case that addresses the challenge of collectively studying social interactions within community-based mental health care. This study is done by revisiting and revising social science methods such as social dilemmas and game theory and by incorporating the use of digital interfaces to run experiments in-the-field. The research can be framed within the emergent citizen social science or social citizen science where shared practices are still lacking. We have identified five key steps of the research process to be considered to introduce participatory and inclusive practices: research framing, research design, experimental spaces, data sources, and actionable knowledge. Social dilemmas and game theory methods and protocols need to be reconsidered as an experiential activity that enables participants to self-reflect. Co-design dynamics and the building of a working group outside the academia are important to initiate socially robust knowledge co-production. Research results should support evidence-based policies and collective actions put forward by the civil society. The inclusion of underserved groups is discussed as a way forward to new avenues of computational social science jointly with intricate ethical aspects. Finally, the paper also provides some reflections to explore the particularities of a further enhancement of social dimensions in citizen science.
Is adding charcoal to soil a good method for CO2 sequestration? - Modeling a spatially homogeneous soil

Carbon sequestration is the process of capture and long-term storage of atmospheric carbon dioxide (CO2) with the aim to avoid dangerous climate change. In this paper, we propose a simple mathematical model (a coupled system of nonlinear ODEs) to capture some of the dynamical effects produced by adding charcoal to fertile soils. The main goal is to understand to which extent charcoal is able to lock up carbon in soils. Our results are preliminary in the sense that we do not solve the CO2 sequestration problem. Instead, we do set up a flexible modeling framework in which the interaction between charcoal and soil can be tackled by means of mathematical tools.   We show that our model is well-posed and has interesting large-time behaviour. Depending on the reference parameter range (e.g. type of soil) and chosen time scale, numerical simulations suggest that adding charcoal typically postpones the release of CO2.
Representation of Caste Discrimination and Untouchability in Dulal's Gahugoro Africā

This paper presents Dalits as Africans in the poem Gahugoro Africā. Dalits are primarily artisans who engage in various tasks such as crafting temple idols, cobbling shoes, ploughing fields, sweeping the streets, and playing musical instruments like the lyre and tum-tum. They utilize their skills and perform the duties expected of them. However, they get fewer wage and they are hated, humiliated, discriminated, exploited and traumatized in the society by the upper caste people and the nation even in this 21st century. Therefore, the purpose of this paper was to illustrate the presence of caste discrimination and untouchability as depicted by the researcher. The research is significant due to its focus on the inhuman treatment and miserable existence of Dalits in the same society. The exploration of diverse cultures and cultural practices is valuable to academia. The research was conducted using a library-based qualitative approach, utilizing relevant texts and sources to analyze the representation of caste discrimination and untouchability in Dulāl's poem. The researcher has implemented cultural studies perspective and the ideas of Stuart Hall as main and other theorists’ ideas as supporting tools for theoretical parameters. The data were collected by text information, description and record keeping. The researcher finds that as a poet, Dulāl seriously raises question that how Dalits are considered untouchables and distanced them by the so called touchable in Nepali society. Dalits present everywhere so, the speaker strictly demands freedom from every type of shackles of discrimination and untouchability. Freedom from such evil practice is inevitable for Dalits in human civilization. So, it is the representative voice of Dalits in general.