ethicalabs/Research-Intent-Collab huggingface dataset:
Abolish! Against the Use of Risk Assessment Algorithms at Sentencing in the US Criminal Justice System

AbstractIn this article, I show why it is necessary to abolish the use of predictive algorithms in the US criminal justice system at sentencing. After presenting the functioning of these algorithms in their context of emergence, I offer three arguments to demonstrate why their abolition is imperative. First, I show that sentencing based on predictive algorithms induces a process of rewriting the temporality of the judged individual, flattening their life into a present inescapably doomed by its past. Second, I demonstrate that recursive processes, comprising predictive algorithms and the decisions based on their predictions, systematically suppress outliers and progressively transform reality to match predictions. In my third and final argument, I show that decisions made on the basis of predictive algorithms actively perform a biopolitical understanding of justice as management and modulation of risks. In such a framework, justice becomes a means to maintain a perverse social homeostasis that systematically exposes disenfranchised Black and Brown populations to risk.
Interstellar Turbulence, Cloud Formation and Pressure Balance

We discuss HD and MHD compressible turbulence as a cloud-forming and cloud-structuring mechanism in the ISM. Results from a numerical model of the turbulent ISM at large scales suggest that the phase-like appearance of the medium, the typical values of the densities and magnetic field strengths in the intercloud medium, as well as Larson's velocity dispersion-size scaling relation in clouds may be understood as consequences of the interstellar turbulence. However, the density-size relation appears to only hold for the densest simulated clouds, there existing a large population of small, low-density clouds, which, on the other hand, are hardest to observe. We then discuss several tests and implications of a fully dynamical picture of interstellar clouds. The results imply that clouds are transient, constantly being formed, distorted and disrupted by the turbulent velocity field, with a fraction of these fluctuations undergoing gravitational collapse. Simulated line profiles and estimated cloud lifetimes are consistent with observational data. In this scenario, we suggest it is quite unlikely that quasi-hydrostatic structures on any scale can form, and that the near pressure balance between clouds and the intercloud medium is an incidental consequence of the density field driven by the turbulence and in the presence of appropriate cooling, rather than a driving or confining mechanism.
Knowledge Reasoning with Graph Neural Networks.

Knowledge reasoning is the process of drawing conclusions from existing facts and rules, which requires a range of capabilities including but not limited to understanding concepts, applying logic, and calibrating or validating architecture based on existing knowledge. With the explosive growth of communication techniques and mobile devices, much of collective human knowledge resides on the Internet today, in unstructured and semi-structured forms such as text, tables, images, videos, etc. It is overwhelmingly difficult for human to navigate the gigantic Internet knowledge without the help of intelligent systems such as search engines and question answering systems. To serve various information needs, in this thesis, we develop methods to perform knowledge reasoning over both structured and unstructured data. This thesis attempts to answer the following research questions on the topic of knowledge reasoning: (1) How to perform multi-hop reasoning over knowledge graphs? How should we leverage graph neural networks to learn graph-aware representations efficiently? And, how to systematically handle the noise in human questions? (2) How to combine deep learning and symbolic reasoning in a consistent probabilistic framework? How to make the inference efficient and scalable for large-scale knowledge graphs? Can we strike a balance between the representation power and the simplicity of the model? (3) What is the reasoning pattern of graph neural networks for knowledge-aware QA tasks? Can those elaborately designed GNN modules really perform complex reasoning process? Are they under- or over-complicated? Can we design a much simpler yet effective model to achieve comparable performance? (4) How to build an open-domain question answering system that can reason over multiple retrieved documents? How to efficiently rank and filter the retrieved documents to reduce the noise for the downstream answer prediction module? How to propagate and assemble the information among multiple retrieved documents? (5) How to answer the ...
Introducing MELI: the Mandarin-English Language Interview Corpus

We introduce the Mandarin-English Language Interview (MELI) Corpus, an open-source resource of 29.8 hours of speech from 51 Mandarin-English bilingual speakers. MELI combines matched sessions in Mandarin and English with two speaking styles: read sentences and spontaneous interviews about language varieties, standardness, and learning experiences. Audio was recorded at 44.1 kHz (16-bit, stereo). Interviews were fully transcribed, force-aligned at word and phone levels, and anonymized. Descriptively, the Mandarin component totals ~14.7 hours (mean duration 17.3 minutes) and the English component ~15.1 hours (mean duration 17.8 minutes). We report token/type statistics for each language and document code-switching patterns (frequent in Mandarin sessions; more limited in English sessions). The corpus design supports within-/cross-speaker, within/cross-language acoustic comparison and links acoustics to speakers' stated language attitudes, enabling both quantitative and qualitative analyses. The MELI Corpus will be released with transcriptions, alignments, metadata, scans of labelled maps and documentation under a CC BY-NC 4.0 license.
Protecting the rights of minorities by appeal to a multicultural citizenship approach

There are a few government in the world which have a united culture. Generally, one culture as an official and dominant culture is supported by the central government and recognized. Such an approach results the discontent of other cultural groups. Different groups who are in such a situation, often claim their rights by human rights literature or minority rights. A number of theorists have proposed an “equal citizen” theory to solve this problem. The other ones also, have provided a solution to claim the rights of cultural groups and minority by presentation the theory of a “different citizenship’’ or “multicultural citizenship’’ and sometimes ‘’tended multicultural’’ in the area of minority rights and citizen rights. Among these theories, the theories of thinkers such as Will Kymlicka and Irish Marion Yang are significant. .Qur’anic verses and Islamic law sources have special rules hereof, and they seem to confirm the approach of a different citizen with equal citizen. This article seeks to challenge the classical theories of citizenship rights on the basis of "equal citizen" and on the basis of the theory of "multicultural citizenship" and "different citizens" of the abovementioned scholars and a number of Qur’anic verses and affected by the aforementioned theory, provides a new framework for claiming minority rights and solving their problems in countries with mosaics of ethnic, national, cultural and different identities. And seeks to provide a model that is consistent with and compatible with multicultural countries to peaceful living with admission of different the other one.
A MODEL-INDEPENDENT METHODOLOGY FOR A ROOT CAUSE ANALYSIS SYSTEM : A STUDY INVESTIGATING INTERPRETABLE MACHINE LEARNING METHODS

Today, companies like Volvo GTO experience a vast increase in data and the ability toprocess it. This makes it possible to utilize machine learning models to construct a rootcause analysis system in order to predict, explain and prevent defects. However, thereexists a trade-off between model performance and explanation capability, both of whichare essential to such system.This thesis aims to, with the use of machine learning models, inspect the relationshipbetween sensor data from the painting process and the texture defectorange peel. Theaim is also to evaluate the consistency of different explanation methods.After the data was preprocessed, and new features were engineered, e.g. adjustments,three machine learning models were trained and tested. In order to explain a linearmodel, one can use its coefficients. In the case of a tree-based model, MDI is a commonglobal explanation method. SHAP is a state-of-the-art model-independent method thatcan explain a model globally and locally. These three methods were compared in orderto evaluate the consistency of their explanations. If SHAP would be consistent with theothers on a global level, it can be argued that SHAP can be used locally in an root causeanalysis.The study showed that the coefficients and MDI were consistent with SHAP as theoverall correlation between them were high and because they tended to weight thefeatures in a similar way. From this conclusion, a root cause analysis algorithm wasdeveloped with SHAP as a local explanation method. Finally, it cannot be concludedthat there is a relationship between the sensor data andorange peel, as the adjustments ofthe process were the most impactful features.
The Global Fund: Anti-Corruption, Transparency and Accountability

Abstract         Background: The Global Fund to Fight AIDS, Malaria and Tuberculosis has been a key international organization in improving the health of those affected by the three big diseases. It was created during a time of health crisis and did not have the necessary anti-corruption, transparency, and accountability (ACTA) structures in place to prevent fraud and corruption in its grants, which resulted in misuse of funds by grant recipients and loss of donor confidence in 2011. Almost one decade later, this paper seeks to describe the ACTA mechanisms within the Global Fund and their results. Results: At the highest level, the Board of Directors has restructured the Global Fund’s governing committees in 2011 and in 2016 to its current Audit and Finance, Ethics and Governance, and Strategy Committees. This has helped to delineate committee mandates and to strengthen the Board’s oversight and direction on operations. In addition, the Global Fund has adopted a rigorous risk management framework and has worked risk mitigation into all aspects of functioning. An Ethics and Integrity Framework was adopted in 2014 and an Ethics Office was established in 2016, resulting in increased conflict of interest disclosures and greater ethics considerations within the Global Fund. The Office of the Inspector General of the Global Fund has been effective in performing internal and external audits and investigations on fraud and corruption, suggesting changes to mitigate future risks, and implementing novel initiatives, such as the I Speak Out Now! campaign to encourage whistleblowing and to educate on signs of fraud and corruption. Finally, the “eyes and ears” of the Global Fund, the Local Fund Agents, have been involved in exposing fraud and corruption during the implementation of Global Fund grants. These mechanisms have reduced grant-related risks and procurement fraud in particular. Conclusions: Over the past decade, the Global Fund has developed a number of ACTA mechanisms. It will be critical that the Global Fund continues to monitor and evaluate how effective these mechanisms are and to make changes, when and where needed.
Learning from interpreting transitions in explainable deep learning for biometrics

Máster Universitario en Métodos Formales en Ingeniería Informática
FROM DATA MINING AND KNOWLEDGE DISCOVERY TO BIG DATA ANALYTICS AND KNOWLEDGE EXTRACTION FOR APPLICATIONS IN SCIENCE

“Data mining” for “knowledge discovery in databases” and associated computational operations first introduced in the mid-1990 s can no longer cope with the analytical issues relating to the so-called “big data”. The recent buzzword big data refers to large volumes of diverse, dynamic, complex, longitudinal and/or distributed data generated from instruments, sensors, Internet transactions, email, video, click streams, noisy, structured/unstructured and/or all other digital sources available today and in the future at speeds and on scales never seen before in human history. The big data also being described using 3 Vs, volume, variety and velocity (with an additional 4th V for “veracity” and more recently with a 5th V for “value”), requires a set of new technologies, such as high performance computing i.e., exascale, architectures (distributed or grid), algorithms (for data clustering and generating association rules), programming languages, automated and scalable software tools, to uncover hidden patterns, unknown correlations and other useful information lately referred to as “actionable knowledge” or “data products” from the massive volumes of complex raw data. In view of the above facts, the paper gives an introduction to the synergistic challenges in “data-intensive” science and “exascale” computing for resolving “big data analytics” and “data science” issues in four main disciplines namely, computer science, computational science, statistics and mathematics. For the realisation of vital identified foundational aspects of an effective cyber infrastructure, basic problems need to be addressed adequately in the respective disciplines and are outlined. Finally, the paper looks at five scientific research projects that are urgently in need of high performance computing; this is in contrast to the earlier situations where private business enterprises were the drivers of better modern and faster technologies
Design and feasibility of smartphone-based digital phenotyping for long-term mental health monitoring in adolescents

Assessment of psychiatric symptoms relies on subjective self-report, which can be unreliable. Digital phenotyping collects data from smartphones to provide near-continuous behavioral monitoring. It can be used to provide objective information about an individual’s mental state to improve clinical decision-making for both diagnosis and prognostication. The goal of this study was to evaluate the feasibility and acceptability of smartphone-based digital phenotyping for long-term mental health monitoring in adolescents with bipolar disorder and typically developing peers. Participants (aged 14–19) with bipolar disorder (BD) or with no mental health diagnoses were recruited for an 18-month observational study. Participants installed the Beiwe digital phenotyping app on their phones to collect passive data from their smartphone sensors and thrice-weekly surveys. Participants and caregivers were interviewed monthly to assess changes in the participant’s mental health. Analyses focused on 48 participants who had completed participation. Average age at baseline was 15.85 years old (SD = 1.37). Approximately half (54%) identified as female, and 54% identified with a minoritized racial/ethnic background. Completion rates across data types were high, with 99% (826/835) of clinical interviews completed, 89% of passive data collected (22,233/25,029), and 47% (4,945/10,448) of thrice-weekly surveys submitted. The proportion of days passive data were collected was consistent over time for both groups; the clinical interview and active survey completion decreased over the study course. Results of this study suggest digital phenotyping has significant potential as a method of long-term mental health monitoring in adolescents. In contrast to traditional methods, including interview and self-report, it is lower burden and provides more complete data over time. A necessary next step is to determine how well the digital data capture changes in mental health to determine the clinical utility of this approach.
Specific Measures of Quality of Life in Patients with Multimorbidity in Primary Healthcare: A Systematic Review on Patient-Reported Outcome Measures&rsquo; Adequacy of Measurement

Anne M&oslash;ller, Kristine Henderson Bissenbakker, Anne Beiter Arreskov, John Brodersen Research Unit for General Practice and Section of General Practice, Department of Public Health, University of Copenhagen, Copenhagen, DenmarkCorrespondence: Anne M&oslash;ller &Oslash;ster Farimagsgade 5, K&oslash;benhavn DK-1353, DenmarkTel +45 35327171Email amoeller@sund.ku.dkPurpose: The aim of this study is to search systematically for Patient Reported Outcome Measures (PROMs) used among patients with multimorbidity. Furthermore, the aim is to evaluate the adequacy and validity of the PROMs identified.Design and setting: This systematic review follows the PRISMA guidelines. To assess the adequacy and validity of the identified PROMs the COSMIN Risk of Bias Checklist is used, more specifically a validation of the development, content validity, structural validity, and internal consistency of the PROMs.Results: Four PROMs were identified in the primary search, and one was found from references. The sixth PROM was published after the primary search. None of the identified PROMs were aimed specifically at measuring the quality of life in patients with multimorbidity. According to the checklist, the development process and content validity were rated &ldquo;adequate&rdquo; in only one measure and &ldquo;invalid&rdquo;/&ldquo;doubtful&rdquo;/&ldquo;inadequate&rdquo; in the rest of the measures. The structural validity of the measures was rated &ldquo;adequate&rdquo; in four measures and &ldquo;very good&rdquo; in one. Regarding the internal consistency, two measures were rated doubtful and three &ldquo;very good&rdquo;. None of the six PROMs reported analyses about invariant measurement. The COSMIN Risk of Bias Checklist proved easy to use; however, there are some concerns in the rating of bias, that are discussed further.Conclusion: All six PROMs developed for patients with multimorbidity identified possessed inadequacy in their measurement properties. Therefore, the aim for the future is to develop a valid and adequate measure of the quality of life among patients with multimorbidity.Keywords: comorbidity, burden of treatment, burden of disease, validity, psychometric properties
Decolonization and the Right to Self-Determination

Self-determination has been defined as the right of people to freely determine their political status and pursue their economic, social, and cultural development. During decolonization, the right aimed towards the establishment of the self-government for the peoples – inhabitants of nonself-governed colonial territories. Over the last half century, the process of decolonization resulted in a successful attainment of formal sovereignty for the former colonies. However, the liberation movements reached self-determination externally but failed to reach it internally. Since the process of decolonization is formally over, there is a change in a right holder and the mode for practicing self-determination. Except for an aggregate population – people within the state that can practice an external form of self – determination, as a process internal self-determination can be granted to different subnational groups. The ones that reached external self-determination should accept legal norms that grant forms of internal self-determination.
Teaching Paper: Glossary of Corporate Social Responsibility and Ethical Business Terms

This Teaching Paper presents a glossary of 28 key terms in Corporate Social Responsibility (CSR), sustainability, ethics, and governance. Definitions are written in clear academic language with practical notes that connect theory to real-world application. By consolidating terms such as accountability, triple bottom line, materiality assessment, blockchain, and impact investing, the paper provides a foundational reference for both scholars and practitioners. It strengthens conceptual clarity, supports consistent communication across stakeholders, and enhances effective decision-making in CSR practice.
Can forced marriage fall under a crime against humanity (CAH) listed under Article 7 (1) of the Rome statute of the International Criminal Court (ICC)?

This thesis analyses the legal characterisation of forced marriage at the ICC and asks can forced marriage fall under a CAH listed under Article 7 (1) of the Rome Statute. Chapter 1 of this thesis will begin with a consideration of the definition of forced marriage. Documentation and evidence which was available to the Preparatory Commission of the ICC with respect to the prevalence of forced marriage in conflict zones will be considered. The purpose, to determine whether there was any intention by the drafters of the Rome Statute to include forced marriage as a CAH under Article 7 (1) of the Rome Statute. Chapter 2 will identify the elements of a CAH and the elements of the CAH of an ‘other inhumane act’. An assessment of the elements of a CAH should enable the author to determine the elements required to prosecute forced marriage as a CAH at the ICC. Chapter 3 will consider the role of prosecutorial discretion in the legal characterisation of forced marriage at the ICC. Finally, the author will conclude by answering can forced marriage can fall under a CAH listed under Article 7 (1) of the Rome Statute.
CSI-COP Policy Brief 2: Standardising Cookie Notices and Privacy Policies to Improve Compliance of the General Data Protection Regulation (GDPR).

This second CSI-COP policy brief makes two recommendations arising from the evidence in the engagement of citizen scientists in collaboration with the project researchers. Investigating the general data protection regulation (GDPR), specifically as it relates to transparency of cookie notices and privacy policies in collecting personal data through informed consent from websites and apps, shows that compliance is not followed completely. From website and app investigations, and evidence here provided from one EU funded project website, CSI-COP recommends that EU requires its funded projects to a) follow guidelines to extract unnecessary third-party tracking embedded in website, and Android app, development environments, and b) accept standardised cookie notices and privacy policies.
Business Ethics And Corporate Social Responsibility In The Indian Economy: A Commentary

The effects of globalization and its impact on the transition from the industrial to the digital era are explored. Although the behaviour of business organizations has always had a profound worldwide impact, with the decline of the nation state economic power has, for the first time, eroded political power. Simultaneously, the undergoing revolution in contemporary information and communication technologies has significantly empowered the customer. Responding to enhanced customer awareness and sensitivity to business and social responsibility issues -coupled with consumers’ increasing ability to react- companies in the digital age may be expected to develop even stronger cultures of corporate social responsibility, proactively seeking to increasingly honour their moral obligations to society in the 21st century. The paper addresses the concepts of business ethics and corporate social responsibility in the old vis-à-vis the Indian economy.. The implications of the findings are crucial to support policy makers in organizations to consider the relationship between the two concepts as building blocks in their strategic initiative.