In a series of ten preregistered experiments (N=2043), we investigate the effect of outcome valence on judgments of probability, negligence, and culpability – a phenomenon sometimes labelled moral (and legal) luck. We found that harmful outcomes, when contrasted with neutral outcomes, lead to increased perceived probability of harm ex post, and consequently to increased attribution of negligence and culpability. Rather than simply postulating a hindsight bias (as is common), we employ a variety of empirical means to demonstrate that (...) the outcome-driven asymmetry across perceived probabilities constitutes a systematic cognitive distortion. We then explore three distinct strategies to alleviate the hindsight bias and its downstream effects on mens rea and culpability ascriptions. Not all are successful, but at least some prove promising. They should, we argue, be taken into consideration in criminal jurisprudence, where distortions due to the hindsight bias are likely considerable and deeply disconcerting. (shrink)

Abstract: Lotteries have long been a source of fascination and intrigue, offering the tantalizing prospect of unexpected fortunes. In this research paper, we delve into the world of lottery predictions, employing cutting-edge AI techniques to unlock the secrets of lottery outcomes. Our dataset, obtained from Kaggle, comprises historical lottery draws, and our goal is to develop predictive models that can anticipate future winning numbers. This study explores the use of deep learning and time series analysis to achieve this elusive (...) feat. Through rigorous experimentation and data-driven approaches, we seek to determine the viability of AI in the realm of lottery predictions. Our findings reveal both the promise and limitations of AI in this context, shedding light on the complexities of lottery data and the potential need for quantum computing as a last resort. (shrink)

Coastal environments are widely recognized as valuable public health resources and therapeutic landscapes. However, limited research has examined how specific coastal interactions that foster close connections with nature influence health outcomes. This study investigates the relationship between the frequency of engaging in high-nature-interaction coastal activities―e.g., beach walking, wildlife spotting, water sports, mountain biking, spending time on the beach, beach sports, watching the sunset, seagoing, and shell collecting― and health outcomes among visitors to the Belgian coast. Using a dataset (...) of 1,939 responses, we analyze how the frequencies of these activities over the past year are associated with self-reported mental and general health. Grounded in the Granular Interaction Thinking Theory (GITT) and employing Bayesian GITT Framework analytics, the study identifies distinct patterns in these associations. While frequent engagement in activities, e.g., beach walking and beach sports, is positively linked to both mental and general health, spending time on the beach and shell collecting are unexpectedly associated with negative health outcomes. Watching the sunset is negatively associated with general health, while mountain biking and water sports show negative associations with mental health. In contrast, wildlife spotting exhibits a positive association with mental well-being. These findings highlight the complex interplay of environmental factors, visitor perceptions, and biophysical-psychological interactions in shaping health outcomes. The study emphasizes the need for targeted coastal management strategies to enhance the therapeutic benefits of blue spaces and calls for further research to elucidate the mechanisms underlying these associations. (shrink)

Egalitarianism seeks equality, which can be divided into two types: equality of process and equality of outcome. However, equality of outcome has been criticized for neglecting responsibility and failing to maximize utility. While pre-Qin Confucianism did not directly address these criticisms, its philosophical ideas can be used to respond to them. Confucius’ idea of equality of outcome can be seen in several texts, such as his comparison of poverty and inequality, his different treatment of Zi Hua’s mother, and his opinion (...) on Yuan Si’s high salary. Confucius believed in maintaining emotional desires in the middle way, which can address the criticism of neglecting responsibility. The Confucians between Confucius and Mencius emphasized “equal distribution” and “equal governance”, which embody the idea of equality of outcome. The emphasis on “employ people at the appropriate times” can also address the question of how to maximize the utility of equality of outcome. Mencius’ distinction between “those who rule” and “those who are ruled” and the concept of “equal field” reflect his idea of equality of outcome. In response to the levelling-down objection raised by Parfit, Mencius could potentially offer a presuppositional critique. Mencius believed that a gentleman would actively choose benevolence and accept the consequences, suggesting that equality of outcome does not ignore responsibility. Xunzi’s statement that “total equality is not order” is not contradictory to equality of outcome, as it emphasizes the importance of division of labour and cooperation among groups. Xunzi acknowledged the existence of a certain level of inequality between rich and poor, considering equality as more of a guiding principle rather than an absolute standard. The philosophical concept of equality, as proposed by pre-Qin Confucianism, provides a response to the criticisms directed towards equality of outcome. 平等主义所追求的平等可分为两种：过程公正和结果均等。相较于过程公正，结果均等遭受的更多的是批评：忽视责任、无法实现最大效用。虽然先秦儒家没有直面也不可能直面这些批评，但其哲学可用来应对这些挑战。 孔子区别贫和不均、对子华母亲态度的前后变化和对原思高俸禄的看法等多处文本，体现了结果均等思想。孔子提倡情感欲望保持中道，这有助于回应忽视责任的批评。孔孟间儒者所强调的分均、政均和平政，体现了结果均等思 想。强调“使民以时”，可以帮助回应结果均等实现最大效用何以可能的问题。孟子区分“治人者”和“治于人者”以及“均井田”等做法体现了结果均等。面对帕菲特的拉平反驳，可以设想孟子会给出前提批判。孟子相信，君 子会主动选择仁并承担后果，这同样说明结果均等并不忽视责任。荀子的“维齐非齐”不违背结果均等，因为它重视的是群体分工合作。荀子允许一定程度的贫富不平等，是因为他更多地把平等视为方向性原则。 先秦儒家的平等思想有助于回应结果均等所遭受到的批评。. (shrink)

In this paper, I examine why moral exemplars are useful and even necessary in moral education despite several critiques from researchers and educators. To support my point, I review recent AI research demonstrating that exemplar-based learning is superior to rule-based learning in model performance in training neural networks, such as large language models. I particularly focus on why education aiming at promoting the development of multifaceted moral functioning can be done effectively by using exemplars, which is similar to exemplar-based learning (...) in AI model training. Furthermore, I discuss the potential limitations and issues related to exemplar-applied moral education with findings from recent studies in AI research raising concerns about model biases and toxic outcomes. I attempt to propose ways to address the concerns regarding employing moral exemplars as well. As remedies, I suggest that autonomy-supporting deliberative and reflective learning processes should be utilized. Furthermore, based on the discussion, I examine how macroscopic socio-cultural aspects influence the effectiveness of exemplar-applied moral education. Suggestions for moral educators and future directions for research in moral education are briefly discussed. (shrink)

Previous research has assessed school facilities, administrative expenditures and curriculum and their relative contributions to students’ cognitive learning outcomes. This suggested the need to investigate further how these predictors may impact students’ affective and psychomotor outcomes. The current research studied the combined and relative prediction of school facilities, administrative expenses and curriculum on students’ overall cognitive, affective and psychomotor learning outcomes in public secondary schools. A cross-sectional research design was employed in this study, involving 87 school administrators (...) and a randomly selected group of 915 senior secondary class II (SS2) students. For data collection, we utilised the School Inputs Questionnaire (SIQ) and Educational Outcomes Questionnaire (EOQ), both developed by the researchers and validated through expert assessments, including content validity, Exploratory Factor Analysis (EFA) for dimensionality, Confirmatory Factor Analysis (CFA) for goodness of fit, and reliability using Cronbach's alpha. The results of these assessments demonstrated acceptable outcomes aligned with international standards. Hierarchical regression analysis was conducted to analyse the collected data. The findings indicated that enhancing the provision of quality school facilities, administrative expenses, and school curricula improved students' overall cognitive, affective, and psychomotor learning outcomes. Specifically, administrative expenses and school curriculum had significant predictive power for students’ overall cognitive, affective, and psychomotor learning outcomes. However, while school facilities significantly predicted students' overall, affective, and psychomotor dimensions, they did not significantly predict the cognitive dimension. These findings offer valuable insights for policymakers and educators aiming to enhance the educational quality in public secondary schools. (shrink)

United Nations’ Sustainable Development Goals 4 Quality Education has highlighted major challenges for all nations to ensure inclusive and equitable quality access to education, facilities for children, and young adults. The SDG4 is even more important for developing nations as receiving proper education or vocational training, especially in science and technology, means a foundational step in improving other aspects of their citizens’ lives. However, the extant scientific literature about STEM education still lacks focus on developing countries, even more so in (...) the rural area. Using a dataset of 4967 observations of junior high school students from a rural area in a transition economy, the article employs the Bayesian approach to identify the interaction between gender, socioeconomic status, and students’ STEM academic achievements. The results report gender has little association with STEM academic achievements; however, female students (αa_Sex[2] = 2.83) appear to have achieved better results than their male counterparts (αa_Sex[1] = 2.68). Families with better economic status, parents with a high level of education (βb(EduMot) = 0.07), or non-manual jobs (αa_SexPJ[4] = 3.25) are found to be correlated with better study results. On the contrary, students with zero (βb(OnlyChi) = -0.14) or more than two siblings (βb(NumberofChi) = -0.01) are correlated with lower study results compared to those with only one sibling. These results imply the importance of providing women with opportunities for better education. Policymakers should also consider maintaining family size so the parents can provide their resources to each child equally. (shrink)

Educational institutions strive to produce graduates who are competent and competitive both domestically and globally. This graduate tracer study investigated the employment outcomes of graduates from the College of Teacher Education (CTE) and Graduate School (GS) Programs from SY 2016-2022. Data collection methods included Google forms, surveys, and phone calls. Of the 2846 CTE graduates, 2491 (87.75%) were traced, and of the 659 GS graduates, 550 (83.45%) were traced. Findings revealed that CTE graduates were predominantly single females aged (...) 24 or younger, who typically began working as permanent teachers at the Department of Education (DepEd) 2-3 years post-graduation, earning a base salary of P15,000–25,000. They generally served in these roles for 4-6 years. Conversely, GS alumni were primarily married men in their 30s, employed in permanent supervisory or managerial roles at DepEd, with monthly earnings between P25,000 and P50,000. Graduates reported that their university degrees were economically relevant and provided significant financial advantages. CTE graduates indicated that job satisfaction was more influenced by workplace interactions and environment than salary. The study suggests enhancing the use of social media to encourage graduate participation in tracer studies and recommends ongoing professional development for faculty to improve educational programs and prepare graduates with highly employable skills. Addressing job satisfaction disparities may require targeted interventions to improve educational programs, expand career development opportunities, and foster supportive work cultures tailored to each graduating class's needs. (shrink)

The issue of leadership styles used by school heads and the academic performance of students has recently attracted the attention of the general public and people are exerting energies into research to find its courses and effects. Nkoranza-North district is selected as a result of the fact that the researcher works there and the districts also have two senior high schools for the study. Primarily, the study was to find out the courses and impact of leadership styles on teaching and (...) learning outcomes in the Nkoranza-North district. The study covered a sample size of sixty (60) people comprises of Headmasters, selected teachers and selected students of the two. The researcher employed the descriptive method, while interview schedule and questionnaire were used to gather the information. Frequency and percentage were used to analyse the data. The study also looks at the various leadership styles employed by leaders some of which are Autocratic, Democratic and Laissez-faire. The findings of the study are discussed, conclusion draw and recommendations made. (shrink)

Chronic Kidney Disease (CKD) is a significant global health issue, often leading to kidney failure and requiring costly medical treatments such as dialysis or transplants. Early detection of CKD is essential for timely intervention and improved patient outcomes. This project aims to develop a machine learning-based predictive model for diagnosing CKD at an early stage. By utilizing a range of clinical features such as age, blood pressure, blood sugar, and other relevant biomarkers, we employ machine learning algorithms, including Decision (...) Trees, Random Forests, and Support Vector Machines (SVM), to predict the likelihood of a patient developing CKD. The dataset used in this study includes medical records of patients with various kidney conditions, and preprocessing techniques such as normalization and missing data handling are applied to ensure the model’s robustness. The performance of the model is evaluated using metrics such as accuracy, precision, recall, and F1-score to ensure reliable predictions. This approach not only aims to improve diagnostic accuracy but also provides a data-driven solution to assist healthcare professionals in making informed decisions. The outcome of this project can contribute to better management of CKD, ultimately helping to reduce the burden on healthcare systems and improving patient care. (shrink)

The present study examines how online instruction during the COVID pandemic impacted learning and performs a partial replication of a study by Hahn et al. (2012), which compared students’ testing outcomes of the Major Field Test in Business (MFTB) and the Comprehensive Business Exam (CBE). Our results find that online instruction during the 2020-2021 pandemic isolation period had no significant impact on pre- and post-COVID testing outcomes for either exam. It was further found that the question set employed (...) by the CBE exam appears to have changed from the pre- to the post-COVID testing timeframes, making this exam questionable for assurance of learning purposes when compared to prior year results. (shrink)

This study assessed students’ perception of teachers’ effectiveness and learning outcomes in mathematics and economics in secondary schools of Cross River State, Nigeria. Two null hypotheses were formulated to direct the study. The factorial research design was adopted for the study. Cluster and purposive sampling techniques were however employed in selecting a sample of 1,800 students from the three education zones in Cross River State. “Students’ Perception of Teachers Effectiveness Questionnaire (SPTEQ)”, Mathematics Achievement Test (MAT), and Economics Achievement Test (...) (EAT) were used as instruments for data collection. Reliability estimates of .86, .91, and .81 were obtained for the three instruments using Cronbach alpha. Collected data were analysed using descriptive statistics while the research question was answered and the null hypothesis tested using Pearson Correlation matrix and multiple regression analyses (where applicable), with the aid of Minitab v18. Findings revealed amongst others that, there is a significant composite influence of students’ perception of teachers’ motivational skills, teaching methods, relationship with students, and communication level on learning outcomes in Mathematics (F = 142.46, p < .05) and Economics (F = 150.31, p < .05) respectively. It was recommended amongst others that secondary school teachers should adopt motivational techniques such as praises, rewards, and smiles, in strengthening the interest of learners during mathematics and Economics lessons. Keywords:. (shrink)

Learner-centered approaches have emerged as the fundamental pillar of effective pedagogy in the rapidly evolving landscape of 21st century education. This paradigm shift places the learner at the heart of the educational process, recognizing their diverse needs and aspirations. Consequently, the achievements of learners have become crucial indicators of institutional success. While extensive research has focused on student affairs and services, limited attention has been given to understanding the impact of administration on realizing the objectives of these support systems. This (...) study aims to investigate the relationship between the administration of learner-centered academic support systems and the attainment of desired outcomes in student affairs and services within higher education institutions in the Philippines. Utilizing a non-experimental correlational quantitative research design, a sample of three hundred fifty university students from various academic disciplines was randomly selected as participants. The findings demonstrate a strong positive correlation between the administration of learner-centered academic support systems and the achievement of desired outcomes in student affairs and services. As a result, the null hypothesis was rejected based on statistical analysis employing Pearson Correlation (r). These findings highlight the significant impact that learner-centered academic support system administration has on the realization of objectives in student affairs and services within the contemporary higher educational setting. To ensure sustained best practices in student development, it is imperative for the administration to foster collaboration with internal stakeholders and external partners. Recognizing that students are the focal point of instruction, their performance serves as a reflection of the institution’s commitment to providing quality education. By aligning administrative efforts with the evolving needs of students, institutions can enhance student affairs and services and create an optimal learning environment in the 21st century. (shrink)

The tracer study for the Bachelor of Science in Business Administration (BSBA) degree with Business Economics (BE), Financial Management (FM), Human Resource Management (HRM), and Marketing Management (MM) of the School of Business Administration (SBA) tracks and gathers information about the career outcomes and experiences of graduates of the degree program. This study focuses on determining the employment opportunities pursued by the graduates of 2018–2022, as well as exploring the influence their education from the SBA of San Isidro (...) College (SIC) has had on their careers. Through this tracer study, valuable insight has been gained into the effectiveness of the SBA's BSBA program offered by SIC and its graduates' overall success and impact in the job market. The lack of respondents in the BE major suggests a need to revisit and modify the curriculum and marketing efforts to generate more interest among potential students. The FM, HRM, and MM major should be capitalized and sustained to maintain the positive momentum. The study's findings show a mix of employment outcomes for graduates, with opportunities for both early career growth and long-term employment. The program equips graduates with a diverse skillset for various job levels and industries. Most graduates find employment within the province, implying effectiveness in equipping them with the necessary skills. However, the distribution of salaries suggests potential issues with the job market or degree value, requiring further investigation. The program has successfully developed graduates with communication, human relations, and entrepreneurial skills but may need improvement in marketing management, problem-solving, and critical thinking. The study concludes that graduates have higher communication skills but lower problem-solving and critical thinking skills, emphasizing the need for curriculum modifications and additional support to improve overall skills. (shrink)

This research employs the Bayesian network modeling approach, and the Markov chain Monte Carlo technique, to learn about the role of lies and violence in teachings of major religions, using a unique dataset extracted from long-standing Vietnamese folktales. The results indicate that, although lying and violent acts augur negative consequences for those who commit them, their associations with core religious values diverge in the final outcome for the folktale characters. Lying that serves a religious mission of either Confucianism or Taoism (...) (but not Buddhism) brings a positive outcome to a character (βT_and_Lie_O= 2.23; βC_and_Lie_O= 1.47; βT_and_Lie_O= 2.23). A violent act committed to serving Buddhist missions results in a happy ending for the committer (βB_and_Viol_O= 2.55). What is highlighted here is a glaring double standard in the interpretation and practice of the three teachings: the very virtuous outcomes being preached, whether that be compassion and meditation in Buddhism, societal order in Confucianism, or natural harmony in Taoism, appear to accommodate two universal vices—violence in Buddhism and lying in the latter two. These findings contribute to a host of studies aimed at making sense of contradictory human behaviors, adding the role of religious teachings in addition to cognition in belief maintenance and motivated reasoning in discounting counterargument. (shrink)

Racial disparities in health outcomes have recently become a flashpoint in the debate about the value of race as a biological concept. What role, if any, race has in the etiology of disease is a philosophically and scientifically contested topic. In this article, I expand on the insights of the new mechanistic philosophy of science to defend a mechanism discovery approach to investigating epidemiological racial disparities. The mechanism discovery approach has explanatory virtues lacking in the populational approach typically employed (...) in the study of race and biomedicine. The explanatory constraints that form an integral part of the new mechanistic approach enable mechanism discovery to avoid the epistemic and normative shortcomings of the populational approach. The methodology of mechanism discovery can fruitfully be extended to the treatment and reversal of epidemiological racial disparities. (shrink)

This paper employs some outcomes (for the most part due to David Lewis) of the contemporary debate on the metaphysics of dispositions to evaluate those dispositional analyses of meaning that make use of the concept of a disposition in ideal conditions. The first section of the paper explains why one may find appealing the notion of an ideal-condition dispositional analysis of meaning and argues that Saul Kripke’s well-known argument against such analyses is wanting. The second section focuses on Lewis’ (...) work in the metaphysics of dispositions in order to call attention to some intuitions about the nature of dispositions that we all seem to share. In particular, I stress the role of what I call "Actuality Constraint". The third section of the paper maintains that the Actuality Constraint can be used to show that the dispositions with which ideal-condition dispositional analyses identify my meaning addition by "+" do not exist (in so doing, I develop a suggestion put forward by Paul Boghossian). This immediately implies that ideal-condition dispositional analyses of meaning cannot work. The last section discusses a possible objection to my argument. The point of the objection is that the argument depends on an illicit assumption. I show (1) that, in fact, the assumption in question is far from illicit and (2) that even without this assumption it is possible to argue that the dispositions with which ideal-condition dispositional analyses identify my meaning addition by "+" do not exist. (shrink)

Abstract: Colon cancer is a prevalent and life-threatening disease, necessitating accurate and timely diagnosis for effective treatment and improved patient outcomes. This research paper presents the development of a knowledge-based system for diagnosing colon cancer using the CLIPS language. Knowledge-based systems offer the potential to assist healthcare professionals in making informed diagnoses by leveraging expert knowledge and reasoning mechanisms. The methodology involves acquiring and structuring medical knowledge specific to colon cancer, followed by the implementation of a knowledge- based system (...) using CLIPS. The system's design integrates relevant medical databases and employs advanced reasoning mechanisms to facilitate accurate diagnosis. Evaluation results demonstrate the system's effectiveness, with high accuracy and sensitivity rates compared to existing methods. The findings highlight the potential of knowledge-based systems in improving clinical practice and patient care. The research contributes to the growing field of medical informatics by demonstrating the feasibility and effectiveness of CLIPS-based knowledge systems for colon cancer diagnosis. Future research can focus on enhancing system performance and expanding its scope to encompass other types of cancer diagnoses. (shrink)

Abstract: The sinking of the RMS Titanic in 1912 remains a poignant historical event that continues to captivate our collective imagination. In this research paper, we delve into the realm of data-driven analysis by applying Artificial Neural Networks (ANNs) to predict the chances of survival for passengers aboard the Titanic. Our study leverages a comprehensive dataset encompassing passenger information, demographics, and cabin class, providing a unique opportunity to explore the complex interplay of factors influencing survival outcomes. Our ANN-based predictive (...) model achieved an accuracy rate of 78%, shedding light on the underlying patterns within the data. However, this paper underscores the multifaceted nature of survival prediction and acknowledges several challenges. These include missing data imputation, feature engineering, and the inherent noise within historical datasets. We further discuss the importance of model evaluation metrics, showcasing not only accuracy but also precision, recall, and F1-score as essential indicators of predictive performance. The research paper meticulously outlines the architecture of the ANN model, emphasizing the key hyperparameters, activation functions, and regularization techniques employed in model development. Additionally, we address ethical considerations related to data handling and potential biases within the dataset. While our achieved accuracy is a notable achievement, this study emphasizes the importance of interpreting the results with due caution. It underscores the need for a holistic perspective that considers the practical implications of false positives and false negatives, especially in the context of a disaster scenario. In conclusion, this research contributes to our understanding of survival prediction in historical events like the Titanic disaster using modern machine learning techniques. It calls for further exploration and refinement of predictive models, with a focus on enhancing the interpretability and generalizability of such models to real-world applications. (shrink)

In this paper, we propose a new hybrid neutrosophic multi criteria decision making (MCDM) framework that employs a collection of neutrosophic analytical network process (ANP), and order preference by similarity to ideal solution (TOPSIS) under bipolar neutrosophic numbers. The MCDM framework is applied for chief executive officer (CEO) selection in a case study at the Elsewedy Electric Group, Egypt. The proposed approach allows us to assemble individual evaluations of the decision makers and therefore perform accurate personnel selection. The outcomes (...) of the proposed method are compared with those of the related works such as weight sum model (WSM), weight product model (WPM), analytical hierarchy process (AHP), multiobjective optimization based on simple ratio analysis (MOORA) and ANP methods to prove and validate the results. (shrink)

The republican case for workplace democracy is presented and defended from two alternative means of ensuring freedom from arbitrary interference in the firm—namely, the right to freely exit the firm and workplace regulation. This paper shows, respectively, that costless exit is neither possible nor desirable in either perfect or imperfect labor markets, and that managerial discretion is both desirable and inevitable due to the incompleteness of employment contracts and labor legislation. The paper then shows that WD is necessary, from (...) a republican standpoint, if workers’ interests are to be adequately tracked in the exercise of managerial authority. Three important objections are finally addressed— that WD is redundant, that it is unnecessary provided that litigation and unionism can produce similar outcomes, and that it falls short of ensuring republican freedom compared to self-employment. (shrink)

This research employs the Bayesian network modeling approach, and the Markov chain Monte Carlo technique, to learn about the role of lies and violence in teachings of major religions, using a unique dataset extracted from long-standing Vietnamese folktales. The results indicate that, although lying and violent acts augur negative consequences for those who commit them, their associations with core religious values diverge in the outcome for the folktale characters. Lying that serves a religious mission of either Confucianism or Taoism (but (...) not Buddhism) brings a positive outcome to a character. A violent act committed to serving Buddhist mission results in a happy ending for the committer. (shrink)

Background: The feeding modalities used in school meal programs—such as breakfast, lunch, dinner, snacks, and take-home rations—are influenced by various factors, including supply chain constraints and technical challenges in food distribution. The methods of supply sourcing, whether through domestic or foreign food reserves via in-kind donations or purchases, play a critical role in shaping the feeding options provided. Aim: This study aims to examine the association between supply-sourcing strategies, i.e., domestic and foreign in-kind donations and national-international purchases, with the feeding (...) modalities applied in school meal programs. Methods: The Bayesian Mindsponge Framework, combining the reasoning strengths of Mindsponge Theory and inference advantages of Bayesian analysis, was employed on a dataset of government representatives who manage large-scale school meal programs across 126 countries. Results: The findings revealed that sourcing supplies through in-kind donations from neighboring or distant countries showed a highly reliable negative association with the feeding modalities of school meal programs, while those from the national bodies showed an ambiguous relationship. The purchasing methods—whether domestic or foreign—tended to exhibit positive associations with feeding modalities, though these associations were only weakly reliable. Conclusions: The findings reveal substantial rooms to improve the effectiveness of supply purchasing strategies in enhancing school meal program feeding modalities. Further research is needed to examine the impact of sourcing supplies through domestic in-kind donations on feeding outcomes. Additionally, developing strategic plans to optimize the use of in-kind donations from international organizations is strongly recommended to avoid its negative consequences and further enhance program effectiveness. (shrink)

This study critically examines the efficacy of Agile project management frameworks within the context of Business Process Outsourcing (BPO) in Cebu I.T. Park, Philippines. Employing a descriptivecorrelational research design, it gathers insights from 30 participants, comprising rank-and-file employees and management personnel, to evaluate client satisfaction, Agile framework effectiveness, project success metrics, client-provider communication, and continuous improvement practices. The study aims to explore disparities in perceptions between these groups and their implications for Agile adoption. Findings reveal notable differences in how Agile (...) frameworks are perceived and practiced. Rank-and-file employees generally rate Agile practices more favorably, highlighting moderate implementation in areas like client satisfaction and project success metrics. Conversely, management personnel express reservations, rating several indicators as less practiced, particularly in communication and Agile framework effectiveness. These disparities underscore a disconnect between leadership and frontline staff, which hinders consistent implementation and alignment with organizational goals. However, management personnel recognize the importance of continuous improvement, providing a foundation for bridging these gaps. The study recommends targeted training programs, enhanced communication strategies, and the establishment of clear success metrics to align perspectives and foster a culture of collaboration. Incorporating customer feedback loops and iterative development cycles is also emphasized to enhance client satisfaction and adaptability. By addressing these challenges, organizations can optimize Agile adoption, improve project outcomes, and achieve greater efficiency and client satisfaction. The findings contribute to the ongoing discourse on Agile frameworks, offering actionable insights for their effective implementation in dynamic business environments. (shrink)

Throughout Iran and various countries, the recent calls of the “Zan, Zendegi, Azadi” (in Persian), “Jin, Jiyan, Azadi” (in Kurdish), or “Woman, Life, Freedom” (in English) movement call for change to acknowledge the importance of women. While these feminist protests and demonstrations have been met with brutality, systematic oppression, and internet blackouts within Iran, they have captured significant social media attention and coverage outside the country, especially among the Iranian diaspora and various international organizations. This article, grounded in feminist urban (...) theories of the Global South, analyzes the digital feminist placemaking movement in Iran. As the first counter‐revolution led by women, the movement utilizes digital art, graffiti, and protest movements to embody women’s solidarity groups and sympathy rallies. Our analysis employs various digital research methods, including social media scrutiny and the study of protest illustrations. Analyzing the digital feminist placemaking in Iran will enable us to compare the commonalities, differences, challenges, and opportunities between the minorities and majorities in the world’s countries. The outcomes of this research can help international organizations such as Amnesty International and the United Nations Agency for Gender Equality and Women’s Empowerment (UN Women), as well as policymakers, institutions, academics, and NGOs, to highlight the various ways in which broader public participation could be encouraged in the process of digital feminist insurgent placemaking. (shrink)

Patients with serious illnesses or injuries may decide to quit their medical treatment if they think paying the fees will put their families into destitution. Without treatment, it is likely that fatal outcomes will soon follow. We call this phenomenon “near-suicide”. This study attempted to explore this phenomenon by examining how the seriousness of the patient’s illness or injury and the subjective evaluation of the patient’s and family’s financial situation after paying treatment fees affect the final decision on the (...) treatment process. Bayesian Mindsponge Framework (BMF) analytics were employed to analyze a dataset of 1042 Vietnamese patients. We found that the more serious the illnesses or injuries of patients were, the more likely they were to choose to quit treatment if they perceived that paying the treatment fees heavily affected their families’ financial status. Particularly, only one in four patients with the most serious health issues who thought that continuing the treatment would push themselves and their families into destitution would decide to continue the treatment. Considering the information-filtering mechanism using subjective cost–benefit judgments, these patients likely chose the financial well-being and future of their family members over their individual suffering and inevitable death. Our study also demonstrates that mindsponge-based reasoning and BMF analytics can be effective in designing and processing health data for studying extreme psychosocial phenomena. Moreover, we suggest that policymakers implement and adjust their policies (e.g., health insurance) following scientific evidence to mitigate patients’ likelihood of making “near-suicide” decisions and improve social equality in the healthcare system. (shrink)

A growing amount of media is paid for by its consumers through their very consumption of it. Typically, this new media is web-based and paid for by advertising. It includes the services offered by Facebook, Instagram, Snapchat, and YouTube. We offer an ethical assessment of the attention economy, the market where attention is exchanged for new media. We argue that the assessment has ethical implications for how the attention economy should be regulated. To conduct the assessment, we employ two heuristics (...) for evaluating markets. One is the “harm” criterion, which relates to whether the market tends to engender extremely harmful outcomes for individuals or society as a whole. The other is the “agency” criterion, which relates not to the outcomes of the market, but rather, to whether it somehow reflects or has its source in weakened agency. We argue that the attention economy animates concerns with respect to both criteria and that new media should be subject to the same sort of regulation as other harmful, addictive products. (shrink)

Abstract: The integration of Artificial Intelligence (AI) into medical imaging marks a transformative advancement in healthcare, significantly enhancing diagnostic accuracy, efficiency, and patient outcomes. This paper delves into the application of AI technologies in medical image analysis, with a particular focus on techniques such as convolutional neural networks (CNNs) and deep learning models. We examine how these technologies are employed across various imaging modalities, including X-rays, MRIs, and CT scans, to improve disease detection, image segmentation, and diagnostic support. Furthermore, (...) the paper discusses the challenges associated with AI-driven medical imaging, such as data quality, model interpretability, and ethical considerations. By analyzing recent advancements and real-world case studies, this paper offers insights into the current landscape of AI in medical imaging and explores its potential future directions. The findings underscore the ongoing evolution of AI technologies and their pivotal role in advancing medical diagnostics and treatment strategies. (shrink)

This research project utilized advanced computer algorithms to predict the outcomes of Premier League soccer matches. The dataset containing match data and odds from seasons was processed to handle missing information, select features and reduce complexity using Principal Component Analysis. To address imbalances, in the target variable Synthetic Minority Over sampling Technique (SMOTE) was employed. Various machine learning models such as RandomForest, DecisionTree, SVM, XGBoost and LightGBM were evaluated.

The present study aimed to examine how to improve the effectiveness of moral exemplar-applied interventions based on the pillars of the Self-Determination Theory (SDT) framework, autonomy, competence, and relatedness. Past research has mainly focused on the relatedness and attainability of moral exemplars for predicting motivation outcomes. The data for this study consisted of synthesized data sets from previous studies examining the motivational impacts of distinct moral exemplars and intervention methods. The main syntheses for these data sets used Multilevel Modeling (...) (MLM) focusing on relatability, attainability, and intervention methods, corresponding to relatedness, competence, and autonomy in the SDT, respectively, as predictors. In general, there was a significant interaction effect between the attainability or relatability, and the intervention method. Autonomous instruction methods, which support autonomy, were demonstrated to boost motivational outcomes. Implications from this study support the employment of SDT to examine the use of moral exemplars in moral education and were consistent with previous exemplar studies. (shrink)

Abstract: This research delves into the utilization of Artificial Neural Networks (ANNs) as a powerful tool for predicting the overall ratings of books by leveraging a diverse set of attributes. To achieve this, we employ a comprehensive dataset sourced from Goodreads, enabling us to thoroughly examine the intricate connections between the different attributes of books and the ratings they receive from readers. In our investigation, we meticulously scrutinize how attributes such as genre, author, page count, publication year, and reader reviews (...) influence a book's overall rating. Through rigorous analysis and experimentation, we construct an advanced ANN model tailored for predictive analysis in the realm of book ratings. The outcomes of our study reveal the remarkable potential of ANNs in this domain. The ANN model exhibits an impressive level of accuracy when it comes to forecasting book ratings, underlining the efficacy and promise of artificial neural networks in enhancing our understanding and prediction of book evaluations. This research opens up new avenues for leveraging machine learning techniques to gain deeper insights into the dynamics of book ratings and reader preferences. (shrink)

This article is a critique of the ethical justification model that John Rawls employs in his defense of a liberal conception of justice. Rawls is famous for two things: his attempt to ground morality in rationality and his conception of justice as fairness. His work has been resounding on both fronts, the first constituting the justificatory framework for the second. Yet from the beginning, the outcome has been more doctrinaire than the method should have allowed with design details promising objectivity. (...) This article goes to that beginning, or to a reasonable proxy for it anyway, in the “Outline of a Decision Procedure for Ethics” (1951), with the aim of exposing and examining the discrepancy where it originates. The goal is not to prey on the earliest version of an initiative later undergoing revision but to identify and investigate the inception of a systematic bias that is retained rather than revised in subsequent iterations. The conclusion is that the decision procedure comes across as too objective to favor a liberal conception of justice over competing alternatives and too universal to identify, produce, or support specific moral principles informing a normative ethical system. (shrink)

Prisoners, those who probably engaged in criminal activities, might possess different perceptions and notions of moral foundations than non-prisoners. Thus, assessing such foundations among the population without testing the validity of the measure may produce biased outcomes. To address the potential methodological issue, we examined the validity of the measurement model for moral foundations among prisoners and community members, i.e., non-prisoners. We conducted the measurement invariance test and measurement alignment to test whether the model was consistently valid across the (...) groups. We also employed the differential item functioning test to examine whether item responses were not biased between the different populations. Results demonstrated significant measurement non-invariance and differential item functioning. However, measurement alignment could address the non-invariance issue. Between-group comparisons of moral foundations were consistent with findings from prior research after performing the alignment. (shrink)

Together we can achieve things that we could never do on our own. In fact, there are sheer endless opportunities for producing morally desirable outcomes together with others. Unsurprisingly, scholars have been finding the idea of collective moral obligations intriguing. Yet, there is little agreement among scholars on the nature of such obligations and on the extent to which their existence might force us to adjust existing theories of moral obligation. What interests me in this paper is the perspective (...) of the moral deliberating agent who faces a collective action problem, i.e. the type of reasoning she employs when deciding how to act. I hope to show that agents have collective obligations precisely when they are required to employ ‘we-reasoning’, a type of reasoning that differs from I-mode, best response reasoning, as I shall explain below. More precisely, two (or more) individual agents have a collective moral obligation to do x if x is an option for action that is only collectively available (more on that later) and each has sufficient reason to rank x highest out of the options available to them. (shrink)

Common mental health disorders are rising globally, creating a strain on public healthcare systems. This has led to a renewed interest in the role that digital technologies may have for improving mental health outcomes. One result of this interest is the development and use of artificial intelligence for assessing, diagnosing, and treating mental health issues, which we refer to as ‘digital psychiatry’. This article focuses on the increasing use of digital psychiatry outside of clinical settings, in the following sectors: (...) education, employment, financial services, social media, and the digital well-being industry. We analyse the ethical risks of deploying digital psychiatry in these sectors, emphasising key problems and opportunities for public health, and offer recommendations for protecting and promoting public health and well-being in information societies. (shrink)

Continued urbanization, along with anthropogenic global warming, has and will increase land surface temperature and air temperature anomalies in urban areas when compared to their rural surroundings, leading to Urban Heat Islands (UHI). UHI poses environmental and health risks, affecting both psychological and physiological aspects of human health. Thus, using a deep learning approach that considers morphological variables, this study predicts UHI intensity in 69 European cities from 2007 to 2021 and projects UHI impacts for 2050 and 2080. The research (...) employs Artificial Neural Networks, Deep Neural Networks, and Gated Recurrent Units, combining high-resolution 3D urban models with environmental data to analyze UHI trends. The results indicate strong associations between urban form, weather patterns, and UHI intensity, highlighting the need for customized urban planning and policy measures to reduce UHI impacts and foster sustainable urban settings. This research enhances understanding of UHI dynamics and serves as a valuable tool for urban planners and policymakers to address the challenges of climate change, urbanization, and air pollution, ultimately aiding in the improvement of health outcomes and building energy consumption. Moreover, the methodology effectively demonstrates the ability of the GRU to link its scores with UHI projections, offering crucial insights into potential health impacts. (shrink)

Breast cancer remains a significant health concern worldwide, necessitating the development of effective diagnostic tools. In this study, we employ a neural network-based approach to analyze the Wisconsin Breast Cancer dataset, sourced from Kaggle, comprising 570 samples and 30 features. Our proposed model features six layers (1 input, 1 hidden, 1 output), and through rigorous training and validation, we achieve a remarkable accuracy rate of 99.57% and an average error of 0.000170 as shown in the image below. Furthermore, our investigation (...) identifies the most influential features in breast cancer diagnosis, shedding light on the key determinants of malignancy. Notably, we find that factors such as fractal dimension_se, symmetry worst, compactness_worst, symmetry_se, and smoothness_se play pivotal roles in distinguishing between benign and malignant cases. This research contributes to the ongoing efforts to enhance breast cancer diagnosis, providing valuable insights into feature importance and showcasing the potential of neural networks in medical applications. Our findings have implications for improving early detection and treatment strategies, ultimately contributing to improved patient outcomes. (shrink)

Climate change assessments rely upon scenarios of socioeconomic developments to conceptualize alternative outcomes for global greenhouse gas emissions. These are used in conjunction with climate models to make projections of future climate. Specifically, the estimations of greenhouse gas emissions based on socioeconomic scenarios constrain climate models in their outcomes of temperatures, precipitation, etc. Traditionally, the fundamental logic of the socioeconomic scenarios—that is, the logic that makes them plausible—is developed and prioritized using methods that are very subjective. This introduces (...) a fundamental challenge for climate change assessment: The veracity of projections of future climate currently rests on subjective ground. We elaborate on these subjective aspects of scenarios in climate change research. We then consider an alternative method for developing scenarios, a systems dynamics approach called ‘Cross-Impact Balance’ (CIB) analysis. We discuss notions of ‘objective’ and ‘objectivity’ as criteria for distinguishing appropriate scenario methods for climate change research. We distinguish seven distinct meanings of ‘objective,’ and demonstrate that CIB analysis is more objective than traditional subjective approaches. However, we also consider criticisms concerning which of the seven meanings of ‘objective’ are appropriate for scenario work. Finally, we arrive at conclusions regarding which meanings of ‘objective’ and ‘objectivity’ are relevant for climate change research. Because scientific assessments uncover knowledge relevant to the responses of a real, independently existing climate system, this requires scenario methodologies employed in such studies to also uphold the seven meanings of ‘objective’ and ‘objectivity.’. (shrink)

Abstract: Heart attacks, or myocardial infarctions, are a leading cause of mortality worldwide. Early prediction and accurate analysis of potential risk factors play a crucial role in preventing heart attacks and improving patient outcomes. In this study, we conduct a comprehensive review of datasets related to heart attack analysis and prediction. We begin by examining the various types of datasets available for heart attack research, encompassing clinical, demographic, and physiological data. These datasets originate from diverse sources, including hospitals, research (...) institutions, and public health agencies. Our analysis aims to identify common features, data quality, and potential biases in these datasets. Next, we explore the predictive modeling techniques employed in heart attack prediction. Machine learning algorithms, such as decision trees, support vector machines, and deep neural networks, have gained prominence in predicting heart attacks. We discuss the strengths and limitations of these methods and highlight recent advancements in predictive modeling. Furthermore, we delve into the critical risk factors associated with heart attacks. Factors such as age, gender, hypertension, diabetes, and cholesterol levels are examined for their significance in predicting cardiac events. We also investigate the role of lifestyle factors, including smoking, diet, and physical activity, in heart attack risk assessment. Additionally, this review addresses the importance of data preprocessing and feature engineering in improving prediction accuracy. Feature selection methods, missing data handling, and data scaling techniques are discussed to enhance the robustness of heart attack prediction models. In conclusion, this comprehensive dataset review provides valuable insights into the state of heart attack analysis and prediction. It serves as a resource for researchers and healthcare professionals seeking to better understand the datasets available for heart attack research and the methods employed for accurate prediction. Ultimately, our efforts in dataset analysis and predictive modeling contribute to the advancement of preventive cardiology and the reduction of heart attack-related morbidity and mortality. (shrink)

There are a number of important links and similarities between public health and safety. In this extended essay, Gregg D. Caruso defends and expands his public health-quarantine model, which is a non-retributive alternative for addressing criminal behavior that draws on the public health framework and prioritizes prevention and social justice. In developing his account, he explores the relationship between public health and safety, focusing on how social inequalities and systemic injustices affect health outcomes and crime rates, how poverty affects (...) brain development, how offenders often have pre-existing medical conditions (especially mental health issues), how involvement in the criminal justice system itself can lead to or worsen health and cognitive problems, how treatment and rehabilitation methods can best be employed to reduce recidivism and reintegrate offenders back into society, and how a public health approach could be successfully applied within the criminal justice system. Caruso's approach draws on research from the health sciences, social sciences, public policy, law, psychiatry, medical ethics, neuroscience, and philosophy, and he delivers a set of ethically defensible and practically workable proposals for implementing the public health-quarantine model. The essay begins by discussing recent empirical findings in psychology, neuroscience, and the social sciences that provide us with an increased understanding of the social and neurological determinants of health and criminal behavior. It then turns to Caruso's public health-quarantine model and argues that the model provides the most justified, humane, and effective approach for addressing criminal behavior. Caruso concludes by proposing a capability approach to social justice grounded in six key features of human well-being. He argues that we cannot successfully address concerns over public health and safety without simultaneously addressing issues of social justice—including the social determinants of health (SDH) and the social determinants of criminal behavior (SDCB)—and he recommends eight general policy proposals consistent with his model. (shrink)

According to the Market Failures Approach to business ethics, beyond-compliance duties can be derived by employing the same rationale and arguments that justify state regulation of economic conduct. Very roughly the idea is that managers have a duty to behave as if they were complying with an ideal regulatory regime ensuring Pareto-optimal market outcomes. Proponents of the approach argue that managers have a professional duty not to undermine the institutional setting that defines their role, namely the competitive market. This (...) answer is inadequate, however, for it is the hierarchical firm, rather than the competitive market, that defines the role of corporate managers and shapes their professional obligations. Thus, if the obligations that the market failures approach generates are to apply to managers, they must do so in an indirect way. I suggest that the obligations the market failures approach generates directly apply to shareholders. Managers, in turn, inherit these obligations as part of their duties as loyal agents. (shrink)

Air pollution is a considerable environmental stressor for urban residents in developing countries. Perceived health risks of air pollution might induce migration intention among inhabitants. The current study employed the Bayesian Mindsponge Framework (BMF) to investigate the rationale behind the domestic and international migration intentions among 475 inhabitants in Hanoi, Vietnam – one of the most polluted capital cities worldwide. We found that people perceiving more impacts of air pollution in their daily life are more likely to have migration intention. (...) The effect of perceived air pollution impact on international migration intention is stronger than that of domestic migration. Acknowledging a family member’s air pollution-induced sickness moderated the association between perceived air pollution impact and domestic migration intention, while the personal experience of air pollution-induced sickness did not. In contrast, the moderation effect of personal experience of sickness became significant in the international migration circumstance, but the effect of information about a family member’s sickness was trivial. The findings suggest that urban inhabitants’ consideration of air pollution averting strategies reflects some characteristics of Homo Oeconomicus. Additionally, the individual’s socio-economic decision is seemingly insignificant on a social scale. Still, through environmental stressors as catalysts, such decisions might result in considerable social outcomes (e.g., internal migration and emigration). (shrink)

This capstone is centered around the development of an efficient electronic property inventory system tailored for school assets, driven by the overarching objective of resource optimization to ensure equitable access to vital materials for all learners. The methodology follows the “ISSO” framework (Ignite, Strategize, Systematize, Operationalize), complemented by a Logical Framework. The project employs a homegrown digitalized system constructed through a waterfall model approach, which undergoes alpha and beta testing. The study’s analysis utilizes a t-Test to evaluate its impact. The (...) outcomes reveal that real-time property monitoring significantly enhances custodianship, while digitalization yields improvements in reliability, efficiency, and usability, effectively overhauling the conventional inventory process. The electronic system fosters stakeholder engagement, supporting communication, budget allocation, and audits. Comparative testing demonstrates clear advantages over traditional manual methods. In conclusion, this study underscores the merits of a refined electronic property inventory system. Notably, the research suggests a need for careful consideration of process complexities in outsourcing decisions and showcases the swift, precise, and transparent accounting provided by e-AIMSS deployments, thereby nurturing transparency and public confidence. This innovative approach holds promise for broader application within the realm of e-government processes. (shrink)

What is required for an action to promote the satisfaction of a desire? We reject extant answers and propose an alternative. Our account differs from competing answers in two ways: first, it is contrastive, in that actions promote the satisfaction of desires only as contrasted with other possible actions. Second, it employs a notion of expected fit between desire and world, defined as the weighted sum of the fit between the desire and the world in all possible outcomes, where (...) each weight is given by the probability of the agent’s obtaining the relevant outcome. According to our proposal, then, an action promotes a desire when the expected fit for the desire given that the agent performs the action is greater than the expected fit of the desire given that the agent performs the contrasting action. We highlight this account’s attractive features and explain how it improves on its competitors. (shrink)

As more objections have been raised against grant peer-review for being costly and time-consuming, the legitimate question arises whether machine learning algorithms could help assess the epistemic efficiency of the proposed projects. As a case study, we investigated whether project efficiency in high energy physics can be algorithmically predicted based on the data from the proposal. To analyze the potential of algorithmic prediction in HEP, we conducted a study on data about the structure and outcomes of HEP experiments with (...) the goal of predicting their efficiency. In the first step, we assessed the project efficiency using Data Envelopment Analysis of 67 experiments conducted in the HEP laboratory Fermilab. In the second step, we employed predictive algorithms to detect which team structures maximize the epistemic performance of an expert group. For this purpose, we used the efficiency scores obtained by DEA and applied predictive algorithms – lasso and ridge linear regression, neural network, and gradient boosted trees – on them. The results of the predictive analyses show moderately high accuracy, indicating that they can be beneficial as one of the steps in grant review. Still, their applicability in practice should be approached with caution. Some of the limitations of the algorithmic approach are the unreliability of citation patterns, unobservable variables that influence scientific success, and the potential predictability of the model. (shrink)

It is natural to think that there is a tight connection between whether someone is responsible for some outcome and whether it is appropriate to hold her accountable for that outcome. And this natural thought naturally extends to health: if someone is responsible for her health, then, all else being equal, she is accountable for it. Given this, some have thought that responsibility for health has an important role to play in distributing the benefits and burdens of healthcare. But there (...) is a reason for caution. That health is influenced by social, economic, and environmental factors is a matter of consensus. And some have argued that in light of these social determinants of health, individuals are not typically responsible for their health, rendering inappropriate policies that employ a responsibility‐for‐health criterion. This debate implicates a number of overlapping concepts and questions that are often difficult to pull apart. And I worry that those who maintain that social determinants undermine responsibility for health have latched on to the wrong target. The social determinants of health are relevant to such policies, but, I argue, not by globally undermining responsibility. Rather, social determinants are sometimes responsibility‐undermining, sometimes responsibility‐preserving, and often relevant to whether we should hold individuals accountable for their health regardless of their responsibility. This calls for a more nuanced appraisal of the ways in which the social determinants of health are relevant to such policies. And here I attempt to provide one. (shrink)

US Senate is considering legislation designed to immunize small businesses from lawsuits brought by customers alleging to have been infected with COVID-19 while on the premises. The legislation seeks to subsidize reopening small businesses by reducing their vulnerability to liability. I argue that the legislation produces worse public health outcomes than existing liability regimes, obliterates claims to redress supported by corrective justice, and unfairly burdens victims by forcing them to become de facto insurers of their injurers. In the US, (...) where health insurance is inextricably linked with employment, and during the pandemic with the consequent loss of employment, the legislation is cruel in addition to being ineffective, unjust, unfair and inappropriate. Since I first uploaded this manuscript to Philpapers, Senate Republicans have in fact introduced specific legislation that is marginally different than the one I discuss in the manuscript. Instead of offering blanket immunity, the current Republican proposal offers a series of substantial barriers both to filing lawsuits and to securing a successful verdict at trial. I discuss these as an addendum to the main paper. In short, though the changes impact some features of my argument, they do not alter any of the conclusions. The current proposal produces worse public health outcomes than would existing tort regime; it leaves the vast majority of those with legitimate claims to repair in corrective justice without a remedy, when providing the opportunity to secure a remedy for wrongs is in large measure, the essential nature of tort liability. Worse still, it continues to render victims the de facto insurers of those who have wronged them; it imposes the burden of spreading risks on victims who are considerably less efficient risk spreaders than are businesses and hospitals; it constitutes an inappropriate response to the challenge it seeks to address, i.e. subsidizing various sectors of the economy by reducing their overall costs; and given the fact that in the US health insurance is too closely linked to employment, it shifts the costs of the pandemic to those who are most at risk of losing their health insurance, rendering the proposal cruel in addition to inefficient, unjust, unfair and inappropriate. For those interested, I am considering a short op-ed piece assessing the particular legislative proposal. If I follow through I will let the readership know where that can be found. (shrink)

Race is one of the most common variables in the social sciences, used to draw correlations between racial groups and numerous other important variables such as education, healthcare outcomes, aptitude tests, wealth, employment and so forth. But where concern with race once reflected the view that races were biologically real, many, if not most, contemporary social scientists have abandoned the idea that racial categories demarcate substantial, intrinsic biological differences between people. This, in turn, raises an important question about (...) the significance of race in those social sciences: if there is no biological basis of race, why are racial categories useful to social scientists? More specifically, in virtue of what are racial categories a successful basis of informative, important social scientific generalizations? 2 We’ll call this social science’s race puzzle. (shrink)

Wayne Martin and colleagues argue that decisions about patients’ best interests must sometimes take into account the interests of others Doctors often find themselves in circumstances where they must make decisions on behalf of an incapacitated patient. As a matter of both ethics and law, such decisions must be taken in the best interests of the patient, but uncertainty remains about what is meant by best interests, especially in relation to the interests of others. Should the interests of others enter (...) into a determination of the patient’s best interests? We believe that they should and argue against a recent trend to focus solely on the patient. It only takes a moment’s reflection to appreciate that the interests of one person are often wrapped up with the interests of others. A patient has an interest in recovering from her illness, but so do her family, employer, care providers, etc. Sometimes these various interests can be independently specified, but in other cases they are inextricably intertwined. Suppose that I am a single parent whose overriding interest is to ensure the wellbeing of my children. In that case the proper specification of my best interest is a function of theirs; I simply cannot determine the one without considering the other. This can create an ethical problem in medical decision making. In circumstances where medical staff must make a decision in the best interests of an incapacitated patient, to what extent can or should they take account of the interests of other people whose lives are affected by the outcome? These ethical issues have taken on a concrete legal shape in the UK with the implementation of the Mental Capacity Act 2005, which specifies that, “An act done, or decision made, under this Act for or on behalf of a person who lacks capacity …. (shrink)

The notion of repression as active forgetfulness already found in Nietzsche and systematised by Freud and his successors is employed in a distinctive manner by Merleau-Ponty in Phenomenology of Perception. By showing how we appropriate our environment towards outcomes and respond to other people, he contends, we can unearth hidden modes of operative intentionality. Two such modes are the motor intentional projection of action and the anonymous intercorporeality that includes touching and being touched. Each of these is an aspect (...) of a past that was never a present. Merleau-Ponty does have something to say about pasts that were once present and that linger on in human life. Yet he shows little interest in the unconsciousness of psychoanalysis for its own sake. Psychoanalytic accounts of repression are assimilated into his theory of the body itself, serving merely as means for illustrating the latter. I suggest that this move follows on a conception of an integrated existent whose past acquisitions are remarkably enabling and untroubling. (shrink)