Learning to live together is the central concern of education everywhere in the world. Traditional sporting games provide interpersonal experiences that shape miniature communities charged with emotional meanings. The objective of this study was to analyze the ethnomotor features of TSG in three Catalan-speaking Autonomous Communities and to interpret them for constructing emotional communities. The study followed a phenomenological-interpretative paradigm. The identification of TSG was done by a hermeneutic methodological approach by using an exhaustive exploratory documentary research. We studied 503 (...) games collected in the Dictionary Català-Valencià-Balear de Alcover and Moll. Instruments and procedure: A database was built up with information about the internal and external logic of the games. The validity of the information was confirmed by means of a concordance test between the researchers. Data processing was carried out by means of classification trees, identifying the predictive variables of the types of TSG. Most of the TSGs were sociomotor games. The classification tree identified four explanatory variables. Three variables were internal traits, and one variable corresponded to external logic. Features of the TSG of the Catalan-speaking Autonomous Communities build original emotional communities. The ethnomotor regularities triggered emotional experiences associated with pleasure for living together ; domesticating of aggressiveness over opponents ; developing sustainability ; educating the competition ; and interpersonal well-being based on the community. (shrink)

Human Towers are one of the most representative traditional sporting games in Catalonia, recognized in 2010 as Intangible Cultural Heritage by the United Nations Organization for Education, Science and Culture. The objective of this research was to study the emotional states elicited by a representative performance of the colla de Castellers de Lleida. This research is based on an ethnographic case study, with mixed methods in which 17 key informants voluntarily participated. Participant observation was used; the data were recorded (...) in a field diary and oral sources. The content analysis was done using the Atlas.ti software. An SPSS database was also created. The statistical techniques were: Descriptive statistical techniques, cross tables with Pearson's Chi-square values. We also used a classification and regression trees to examine the predictive capacity of five independent variables of emotional states. The results reveal that the comments were mostly oriented toward well-being states, The internal cooperative logic of the Human Towers enhances the intense interpersonal relationships of socio-emotional well-being. (shrink)

Funding organizations around the world are adopting open science policies, resulting in a pressing need for open science programs. In response to the 2011 decadal survey, NASA sought to expand and accelerate omics research, releasing its GeneLab Strategic Plan in 2014. GeneLab is an open science data repository and analysis portal for spaceflight and space-relevant omics data. GeneLab’s output has been outstanding, but its full potential as a way to transform space biology has not yet been achieved. NASA (...) should pursue the development of GeneLab as an open science platorm in earnest. (shrink)

In many vertebrates, the enzymatic oxidation of dietary yellow carotenoids generates red keto‐carotenoids giving color to ornaments. The oxidase CYP2J19 is here a key effector. Its purported intracellular location suggests a shared biochemical pathway between trait expression and cell functioning. This might guarantee the reliability of red colorations as individual quality signals independent of production costs. We hypothesize that the ornament type (feathers vs. bare parts) and production costs (probably CYP2J19 activity compromising vital functions) could have promoted tissue‐specific gene relocation. (...) We review current avian tissue‐specific CYP2J19 expression data. Among the ten red‐billed species showing CYP2J19 bill expression, only one showed strong hepatic expression. Moreover, a phylogenetically‐controlled analysis of 25 red‐colored species shows that those producing red bare parts are less likely to have strong hepatic CYP2J19 expression than species with only red plumages. Thus, both production costs and shared pathways might have contributed to the evolution of red signals. (shrink)

Mass surveillance involves the collection and storage of vast amounts of information, such as DNA samples from the general population, or location data from cell phones towers, aerial surveillance, and other sources, to then be used when a future crime occurs. For example, DNA from a crime scene could be checked against the database to identify a suspect; location data could identify suspects who were at the scene of a crime. Mass surveillance implicates important privacy interests, but it (...) would surely reduce crime and therefore has been defended by those who reject “privacy at all costs.” I also reject “privacy at all costs.” However, while agreeing that privacy is a value that must be balanced against competing values, I argue that requiring everyone to provide a sample of their DNA or keeping track of everyone’s movements would limit the autonomy of vast numbers of people who there is no reason to suspect will pose a threat, and though such policies would make society safer, that is not worth the cost to individual autonomy. After explaining why individuals can have a substantial interest in privacy even if they are not guilty of a crime, by linking that interest to the value of individual autonomy, and drawing on a political theory of liberal pluralism to restrict what counts as a legitimate public interest that might justify mass surveillance, I articulate a method of balancing these competing interests that is more feasible than a utilitarian approach. (shrink)

Construction cost estimation is one of the essential processes in construction management. Project cost is a complex engineering problem due to various factors affecting the construction industry. Accurate cost estimation is important in construction management and significantly impacts project performance. Artificial intelligence models have been effectively implemented in construction management studies in recent years owing to their capability to deal with complex problems. In this research, extreme gradient boosting is developed as an advanced input selector algorithm and (...) coupled with three AI models, including random forest, artificial neural network, and support vector machine for cost estimation. Datasets were gathered based on a survey conducted on 90 building projects in Iraq. Statistical indicators and graphical methods were used to evaluate the developed models. Several input predictors were used, and XGBoost highlighted inflation as the most crucial parameter. The results indicated that the best prediction was attained by XGBoost-RF using six input parameters, with r-squared and the mean absolute percentage error equal to 0.87 and 0.25, respectively. The comparison results revealed that all AI models showed good prediction performance when applied to datasets affected by more than two parameters. The outcomes of this research revealed an optimistic strategy that can help decision makers select the influencing parameters in the early phases of project management. Also, developing a prediction model with high precision results can assist the project’s estimators in decreasing the errors in the cost estimation process. (shrink)

We applaud Dienes & Perner's efforts while raising some concerns regarding their assimilation of diverse data into a unifying framework. Some of the findings need not fit the framework they suggest. It is also not always clear what, above logico-semantic consistency, assimilation adds to the data that do fit their framework. These concerns are highlighted with reference to their arguments regarding the developmental data and the neuropsychological data, respectively.

Since the 2000s, European open data policies have given a strong boost to commercial meteorology by giving free access to weather observations and models produced by public organizations. This article examines the efforts and challenges met by a French company that developed an offer of weather services based on the commodification of both open weather data and local observations produced by low-cost stations used by farmers. However, the paper shows that such commercialization of stations’ data is (...) hampered both by their material friction with the weather infrastructure and by an economic friction related to data’s heterogeneous valuations. As solving the economic friction generated by data’s valuation is the priority of commercial meteorologists, they finally differentiate their offer using simulated weather data produced by computing models. Finally, the paper claims that the commercial process inherent to the use of this other type of data subordinates weather science to a logic of services: when designing a service for agriculture, the company considered that simulated data were more suited to digital farm advising services. In the end, it is the capacity of weather data to be integrated into private services and tools that valuate them as suited to guide farming practices. (shrink)

Since the twentieth century, it has been an era of rapid development of information technology; the scale of data is almost the growth rate of the blowout type; no matter what it is, a large number of enterprises or departments are increasing a large number of cost data. However, the current cost management model still remains in the traditional management method and lacks a smarter big data analysis method. In addition, there is a lot of (...) research on big data applications, and there are few e-commerce supply chains. Therefore, the research purpose of this study is to use big data technology to explore a series of practical operation methods for supply chain Cultural Communication Enterprises and summarize the operation mode of building SCC control by using big data technology. In terms of research methods, this study combined bibliographic review and empirical analysis, explored cost-based mobile e-commerce cost control related to big data information, used smart and digital analysis methods to thoroughly analyze CCE business issues from internal and external supply chains, established an e-commerce business supply chain cost control model based on big data technology and elaborated cost control procedures and measures. Finally, it summarized the research results and drew conclusions to provide a theoretical basis for promoting enterprises products products to reduce supply chain costs. The research in this study has achieved a breakthrough in the cost management and control of EE; it provides empirical guidance and theoretical reference for EE to adopt big data technology for cost command of supply chain, could help EE to reduce cost of supply chain management to gain higher profit margins, and promote e-commerce industry as a whole to the next level eventually. This study concluded that the use of big data technology for cost command can solve a series of problems effectively, such as the lack of systematic analysis of cost, the lack of contractual partners, the serious waste of sales links, and the policy errors of logistics links, and continuously improve the enterprise management level and the decline of comprehensive cost. The application mode of supply chain CCE enterprises using big data technology constructed in this study has universal applicability. (shrink)

Whether corporate strategic Environmental, Social, and Governance (ESG) disclosure can be effectively screened by external markets still needs more empirical support. Despite numerous studies confirming the positive impact of ESG, the issue of strategic ESG disclosure has yet to receive sufficient attention. This study examines the impact of ESG greenwashing on the cost of debt financing and stock returns using panel data of Chinese A-share listed corporates from 2012 to 2021. The study finds that external markets fail to (...) recognize ESG greenwashing in the short term, leading to a temporary reduction in the cost of debt financing and an increase in stock returns, but these effects are not lasting. Mechanism analysis shows that ESG greenwashing enhances corporate reputation and reduces the cost of debt financing through the reputation effect, stimulates investor sentiment, and improves stock returns through the sentiment effect. The study identifies management myopia, excessive power, financial distress, and information asymmetry as the main drivers. However, strong oversight by independent directors, involvement of Big Four audit firms, investor site visits, and high industry competition can mitigate these misleading effects. This research expands the understanding of the causes and economic consequences of corporate ESG greenwashing and provides empirical evidence for managing this phenomenon. (shrink)

Hunter-gatherer punishment involves costs and benefits to individuals and groups, but the costs do not necessarily fit with the assumptions made in models that consider punishment to be altruistic – which brings in the free-rider problem and the problem of second-order free-riders. In this commentary, I present foragers' capital punishment patterns ethnographically, in the interest of establishing whether such punishment is likely to be costly; and I suggest that in many cases abstentions from punishment that might be taken as defections (...) by free-riders are actually caused by social-structural considerations rather than being an effect of free-rider genes. This presentation of data supplements the ethnographic analysis provided by Guala. (shrink)

This paper discusses the practice of cost-benefit analyses of transportation infrastructure investment projects from the meta-theoretical perspective of critical realism. Such analyses are based on a number of untenable ontological assumptions about social value, human nature and the natural environment. In addition, main input data are based on transport modelling analyses based on a misleading `local ontology' among the model makers. The ontological misconceptions translate into erroneous epistemological assumptions about the possibility of precise predictions and the validity of (...) willingness-to-pay investigations. Accepting the ontological and epistemological assumptions of cost-benefit analysis involves an implicit acceptance of the ethical and political values favoured by these assumptions. Cost-benefit analyses of transportation investment projects tend to neglect long-term environmental consequences and needs among population groups with a low ability to pay. Instead of cost-benefit analyses, impact analyses evaluating the likely effects of project alternatives against a wide range of societal goals is recommended, with quantification and economic valorisation only for impact categories where this can be done in an ontologically and epistemologically defensible way. (shrink)

Kerr coined the term ‘HARKing’ to refer to the practice of ‘hypothesizing after the results are known’. This questionable research practice has received increased attention in recent years because it is thought to have contributed to low replication rates in science. The present article discusses the concept of HARKing from a philosophical standpoint and then undertakes a critical review of Kerr’s twelve potential costs of HARKing. It is argued that these potential costs are either misconceived, misattributed to HARKing, lacking evidence, (...) or that they do not take into account pre- and post-publication peer review and public availability to research materials and data. It is concluded that it is premature to conclude that HARKing has led to low replication rates. (shrink)

This book uses an incidence approach to look at the economic repercussions of birth defects. The authors investigate eighteen of the most clinically significant birth defects affecting 35,000 newborns each year in our country. Their assessments suggest that the annual cost of these eighteen birth defects, together, is more than eight billion dollars . The authors describe in detail their methodology and data sources while providing thorough accounts of each of the eighteen birth defects. Waitzman, Scheffler, and Romano (...) break new ground by using reports from the California Birth Defects Monitoring Program in order to provide cost estimates. They illustrate to the reader how cost estimates of specific birth defects can be used to justify prevention interventions and strategies. In chapter seven, they provide an important example, showing cost-benefit analysis of a program of folate supplementation of food to prevent neutral tube defects. Contents: List of Tables; Preface; Acknowledgements; Introduction; The Application of Cost-of-Illness Methodology To Birth Defects; The Direct Medical Costs of Birth Defects; Nonmedical Direct Costs of Birth Defects: Developmental Services and Special Education; The Indirect Costs of Birth Defects; Premature Mortality and Heightened Morbidity; An Assessment of Total Costs and Policy Implications; Description of Birth Defects; Description of Major Data Sources; Index. (shrink)

Many transgender people need specific medical services to affirm their gender. Gender-affirming health care services may include mental health support, hormone therapy, and reconstructive surgeries. Scant information is available about the utilization or costs of these services among transgender people, which hinders the ability of insurance regulators, health plans, and other health care organizations to plan and budget for the health care needs of this population and to ensure that transgender people can access medically necessary gender-affirming care. This study used (...) almost three decades of commercial insurance claims from a proprietary database containing data on more than 200 million people to identify temporal trends in the provision of gender-affirming hormone therapy and surgeries and to quantify the costs of these services. (shrink)

As big data techniques become widespread in journalism, both as the subject of reporting and as newsgathering tools, the ethics of data science must inform and be informed by media ethics. This article explores emerging problems in ethical research using big data techniques. It does so using the duty-based framework advanced by W.D. Ross, who has significantly influenced both research science and media ethics. A successful framework must provide stability and flexibility. Without stability, ethical precommitments will vanish (...) as technology rapidly shifts costs. Without flexibility, traditional approaches will rapidly become obsolete in the face of technological change. The article concludes that Ross's duty-based approach both provides stability in the face of rapid technological change and flexibility to innovate to achieve the original purpose of basic ethical principles. (shrink)

Medical research data is sensitive personal data that needs to be protected from unauthorized access and unintentional disclosure. In a research setting, sharing of data within the scientific community is necessary in order to make progress and maximize scientific benefits derived from valuable and costly data. At the same time, convincingly protecting the privacy of people participating in medical research is a prerequisite for maintaining trust and willingness to share. In this commentary, we will address this (...) issue and the pitfalls involved in the context of the PEP project1 that provides the infrastructure for the Personalized Parkinson’s Project,2 a large cohort study on Parkinson’s disease from Radboud University Medical Center, in cooperation with Verily life Sciences, an Alphabet subsidiary. (shrink)

Electroencephalography (EEG) neurofeedback is a type of biofeedback that purportedly teaches users how to control their brainwaves. Although neurofeedback is currently offered by thousands of providers worldwide, its provision is contested, as its effectiveness beyond a placebo effect is unproven. While scholars have voiced numerous ethical concerns about neurofeedback—regarding opportunity cost, physical and psychological harms, financial cost, and informed consent—to date these concerns have remained theoretical. This pilot study aimed to provide insights on whether these issues were supported (...) by empirical data from the experiences of neurofeedback users. Semi-structured telephone interviews were conducted with individuals who had used EEG neurofeedback for themselves and/or for a child. The majority of respondents (N = 36) were female (75%), white (92%), and of higher socioeconomic status relative to the U.S. population. Among adult users (n = 33), most (78.8%) resorted to neurofeedback after having tried other therapies, and were satisfied with the treatment (81.8%). The majority paid for neurofeedback out-of-pocket (72.7%) and considered it to be good value for money (84.8%). More than half (57.6%) considered neurofeedback to be a scientifically well-established therapy. However, of those, 78.9% were using neurofeedback for indications not adequately supported by scientific evidence. Concerns regarding opportunity cost, physical and psychological harms, and financial cost are not substantiated by our findings. Our results partially support concerns regarding insufficient understanding of limitations. This study underlines the disconnect between some of the theoretical concerns raised by scholars regarding the use of non-validated therapies and the lived experiences of users. (shrink)

Rehabilitation for disabled children requires long-term programmeswhich are expensive to the family. This study aimed to estimate the costincurred by caregivers’ children with disabilities from Pahang, Terengganu andKelantan participating in Community-Based Rehabilitation and cost of seeking alternative rehabilitation. Costanalysis using the Activity-Based Costing method was used to estimatetwelve-months’ expenditure in 2014 institutional year on 297 caregivers ofchildren with disability, aged 0 to 18 years who attended CBR. Data werecollected using a self-administered costing questionnaire and presentedin median. Results showed (...) that the median direct and indirect costs,excluding medications and alternative care were nearly four times as highin Home-Based compared to Centre-Based vs. RM608. Both groups of caregivers spent a significant amount ofresources on alternative rehabilitation. The high costs incurred for alternativerehabilitation is a major economic burden to the family. (shrink)

Spurred by a confluence of factors, most notably the decreasing cost of high-throughput technologies and advances in information technologies, a number of population research initiatives have emerged in recent years. These include large-scale, internationally collaborative genomic projects and biobanks, the latter of which can be defined as an organized collection of human biological material and associated data stored for one or more research purposes. Biobanks are a key emerging research infrastructure, and those established as prospective research resources comprising (...) biospecimens and data from many participants are viewed as particularly promising drivers of biomedical progress. Such biobanks, particularly those publicly funded and set up to promote the public interest, have expanded across the globe in recent years. (shrink)

The diversity in agronomic practices being used by sugarcane producers in Brazil determines differences in economic performance and cost structure. The purpose of this study is to evaluate the cost of six systems of agronomic practices using fixed or variable rates for soil amendment, fertilizer, and defensive applications and assess the profitability of these systems at three scales of sugarcane production. We then describe the data sample related to the 2019–2020 harvest season and collected from fifty-five sugarcane (...) producers in the central-south region of Brazil. Thereafter, using a quantitative approach, a cost analysis was performed, and the cumulative frequency of the net revenue for the three scales of production (small, medium, and large), was calculated using a Monte Carlo simulation. The cost analysis indicated that fertilizer had the highest cost considering the agronomic practices adopted at the three scales of production analyzed. The cumulative frequency analysis results from the Monte Carlo simulation showed the highest net revenue per hectare for medium sugarcane producers. In addition, the presence of economies of scale was not confirmed because the lowest cost was found in small-scale sugarcane producers and the highest net revenue was obtained by medium-scale sugarcane producers. (shrink)

The objective of this study was to address the paradox of citizenship cost by hypothesizing an indirect rather than a direct effect of altruistic citizenship behavior (ACB) on employee work–family conflict (WFC) through coworker support (CWS). Data were gathered in a three-wave longitudinal survey of employees from private commercial banks (N= 318). A multiple linear autoregressive longitudinal mediation model was analyzed with partial least squares structural equation modeling (PLS-SEM). The results indicate that rather than directly, ACB affects indirectly (...) employee WFC through CWS. This indirect effect is negative, which reflects that the costs of citizenship behavior are paradoxical. The present study contributes to the ongoing debate on the positive and negative outcomes of employee citizenship behavior by providing empirical evidence on the beneficial rather than harmful effect of performing such behavior. For organizational managers, promoting a culture of CWS by encouraging altruistic behaviors can be a most viable strategy to reduce WFC among their employees. The study discusses its limitations and provides future research directions. (shrink)

The first few years of the 21st century were characterised by a progressive loss of privacy. Two phenomena converged to give rise to the data economy: the realisation that data trails from users interacting with technology could be used to develop personalised advertising, and a concern for security that led authorities to use such personal data for the purposes of intelligence and policing. In contrast to the early days of the data economy and internet surveillance, the (...) last few years have witnessed a rising concern for privacy. As bad data practices have come to light, citizens are starting to understand the real cost of using online digital technologies. Two events stamped 2018 as a landmark year for privacy: the Cambridge Analytica scandal, and the implementation of the European Union’s General Data Protection Regulation (GDPR). The former showed the extent to which personal data has been shared without data subjects’ knowledge and consent and many times for unacceptable purposes, such as swaying elections. The latter inaugurated the beginning of robust data protection regulation in the digital age. Getting privacy right is one of the biggest challenges of this new decade of the 21st century. The past year has shown that there is still much work to be done on privacy to tame the darkest aspects of the data economy. As data scandals continue to emerge, questions abound as to how to interpret and enforce regulation, how to design new and better laws, how to complement regulation with better ethics, and how to find technical solutions to data problems. The aim of the research project Data, Privacy, and the Individual is to contribute to a better understanding of the ethics of privacy and of differential privacy. The outcomes of the project are seven research papers on privacy, a survey, and this final report, which summarises each research paper, and goes on to offer a set of reflections and recommendations to implement best practices regarding privacy. (shrink)

Using U.S. Department of Justice data on state-level political corruption, we find that, consistent with the Harmful Corruption Environment Hypothesis (HCEH), firms situated in states with higher levels of corruption incur higher costs of equity (CoEs). These results are robust for additional controls, propensity score matching, use of instrumental variables, exogenous shocks, and alternate measures for main dependent and primary independent research variables. Our study extends the stream of literature that investigates the influence of local ethical or trust factors (...) on CoE and complements works by El Ghoul and colleagues and Gupta and colleagues. (shrink)

In China, Buddhism and Taoism are two major religions. Using a sample of 10,363 firm-year observations from the Chinese stock market for the period of 2001–2010, I provide strong and robust evidence that religion (i.e., Buddhism and Taoism on the whole) is significantly negatively associated with owner-manager agency costs. In particular, using firm-level religion data measured by the number of religious sites within a radius of certain distance around a listed firm’s registered address, I find that religion is significantly (...) negatively (positively) associated with expense ratio (asset utilization ratio), the positive (reverse) proxy for owner-manager agency costs. This finding is consistent with the following view: religiosity has remarkable effects on the way how an individual thinks and behaves, and thereof can curb managers from unethical business practices. Moreover, my findings suggest that the negative association between religion and owner-manager agency costs is attenuated for firms with strong external monitoring mechanisms such as higher Marketization and high-quality auditors. Furthermore, after separating Buddhism from Taoism, my finding indicates that above conclusions are only available for Buddhism, suggesting that different religions may have asymmetric influence on owner-manager agency costs. Above results are robust to various measures of religiosity and a variety of robustness checks. (shrink)

Healthcare professionals decide wisely about personalized medicine, treatment plans, and resource allocation by utilizing big data analytics and machine learning. To guarantee that algorithmic recommendations are impartial and fair, however, ethical issues relating to prejudice and data privacy must be taken into account. Big data analytics and machine learning have a great potential to disrupt healthcare, and as these technologies continue to evolve, new opportunities to reform healthcare and enhance patient outcomes may arise. In order to investigate (...) the patient’s outcomes with empirical evidence, this research was conducted using an online survey to incorporate healthcare professionals, patient’s reviews, and clinical staff. The data were analyzed using SmartPLS 4.0 to predict the structural model. The findings revealed a direct impact as positive influence of using machine learning on healthcare performance and patient outcomes through big data analytics. Moreover, it is evident that this can lead to personalized treatment plans, early interventions, and improved patient outcomes. Additionally, big data analytics can help healthcare providers optimize resource allocation, improve operational efficiency, and reduce costs. The impact of big data analytics on patient outcome and healthcare performance is expected to continue to grow, making it an important area for investment and research. (shrink)

Since the release of OpenAI's ChatGPT, the world has entered a race to develop more capable and powerful AI, including artificial general intelligence (AGI). The development is constrained by the dependency of AI on the model, quality, and quantity of training data, making the AI training process highly costly in terms of resources and environmental consequences. Thus, improving the effectiveness and efficiency of the AI training process is essential, especially when the Earth is approaching the climate tipping points and (...) planetary boundaries. It is evident that AI can function better when trained to mimic certain human mental processes. Based on insights from quantum mechanics and the informational entropy-based notion of value, we suggest AI developers can enhance the AI training processes' effectiveness and efficiency by creating and implementing parameter systems that are capable of effectively assigning probabilities to informational quanta. Such systems can help reduce entropy within the system, which lowers the energy required for data storage and processing while decreasing the likelihood of information loss during training. Successfully applying the concept of information entropy-based value in AI development will be crucial for advancing generative AI and achieving AGI in a sustainable manner. (shrink)

Progress in medicine and the subsequent extension of health coverage has meant that health expenditure has increased sharply in Western countries. In the United States, this rise was precipitated in the 1980s, compounded by an increase in drug consumption which prompted the government to re-examine its financial support to care delivery, most notably in hospital care and emergencies services. In California for example, 50 emergency service providers were closed between 1990 and 2000, and nine in 1999–2000 alone. In that State, (...) only 355 hospitals (out of 568) have maintained emergency services departments (Darves, WebMB, 2001). Reforming hospital Emergency Department (ED) operations requires caution not only because the media pay a lot of attention to ED operations, but also because it raises ethical issues: this became more apparent with the enactment of the EMTALA which stipulates that federally funded hospitals are required to give emergency aid in order to “stabilize” a patient suffering from an “emergency medical condition” before discharging or transferring that patient to another facility. While in essence the law aims to preserve patient access to care, physicians assert that the EMTALA leads to more patients seeking care for non-urgent conditions in EDs (GAO, Report to Congressional Committees, 2001), leading to overcrowding, delayed care for patients with true emergency needs, and forcing hospitals to divert ambulances to other facilities resulting in further delays in urgent care. Also, fewer physicians are willing to be on-call in emergency departments because the EMTALA law requires on-call physicians to provide uncompensated care. Thus there is a need to find a balance between appropriate care to be provided to ED patients, and low costs since uncompensated care is not covered by state or federal funds. This concerns, first and foremost, hospitals that provide a greater amount of uncompensated care (e.g. hospitals serving communities with a higher population of illegal immigrants). Looking at the intrinsic causes of high ED costs, the paper first explains why costs of care provided in EDs are high, and look at a major cause of high ED costs: overcrowding and ED users’ characteristics. This is followed by a discussion on a much-debated factor: the use of EDs for non-emergency conditions, a practice which has often been accused of disproportionately raising costs. We look at various mechanisms used either to divert or prevent the patient from using ED: these include triage services; and the role of HMOs in the ED chain of care: though the US government has increasingly relied on Managed Care organizations to contain costs (e.g. Medicaid and Medicare Managed Care), do HMOs make a difference when it comes to ED costs? Of particular interest is the family physician acting as a gatekeeper, and the legislation that was enacted to protect those who bypass the referral system. We then look at the other end of the ED chain (i.e. the recipient): the financial responsibility of ED users has increased. Alternative providers such as walk-in clinics are increasingly common. EDs also attempt to reengineer their operations to curb costs. While the data are mostly applicable to a private health care system (e.g. the US), the article, using a critical assessment of the existing literature, has implications for other EDs generally, wherever they operate, since every ED faces similar funding problems. (shrink)

Though full of promise, Big Data research success is often contingent on access to the newest, most advanced, and often expensive hardware systems and the expertise needed to build and implement such systems. As a result, the accessibility of the growing number of Big Data-capable technology solutions has often been the preserve of business analytics. Pay as you store/process services like Amazon Web Services have opened up possibilities for smaller scale Big Data projects. There is high demand (...) for this type of research in the digital humanities and digital sociology, for example. However, scholars are increasingly finding themselves at a disadvantage as available data sets of interest continue to grow in size and complexity. Without a large amount of funding or the ability to form interdisciplinary partnerships, only a select few find themselves in the position to successfully engage Big Data. This article identifies several notable and popular Big Data technologies typically implemented using large and extremely powerful cloud-based systems and investigates the feasibility and utility of development of Big Data analytics systems implemented using low-cost commodity hardware in basic and easily maintainable configurations for use within academic social research. Through our investigation and experimental case study, we found that not only are solutions like Cloudera’s Hadoop feasible, but that they can also enable robust, deep, and fruitful research outcomes in a variety of use-case scenarios across the disciplines. (shrink)

This paper draws lessons from the COVID-19 pandemic for the relationship between data-driven decision making and global development. The lessons are that users should keep in mind the shifting value of data during a crisis, and the pitfalls its use can create; predictions carry costs in terms of inertia, overreaction and herding behaviour; data can be devalued by digital and data deluges; lack of interoperability and difficulty reusing data will limit value from data; (...) class='Hi'>data deprivation, digital gaps and digital divides are not just a by-product of unequal global development, but will magnify the unequal impacts of a global crisis, and will be magnified in turn by global crises; having more data and even better data analytical techniques, such as artificial intelligence, does not guarantee that development outcomes will improve; decentralised data gathering and use can help to build trust – particularly important for coordination of behaviour. (shrink)

The costs of agricultural inputs added to those of labor represent almost a third of the total cost of Brazilian sugarcane production. This study analyzes the behavior of the price per ton of sugarcane in Brazil, relating it to the main production costs of this cultivation. Twelve price indicators from January 2015 to December 2020 were evaluated. First, the data were adjusted to a multiple linear regression model to identify the significant variables on variation in the price per (...) ton of sugarcane. Then, the Monte Carlo simulation was used to measure the level of certainty of occurrence of these variables, and forecasts were obtained from the adjustment of ARIMA models. The results showed the influence of the costs of diesel oil, two agricultural pesticides, and daily laborers on the price of sugarcane, besides an increasing trend of its, providing relevant short-term projections for decision-making about investments in the agribusiness sector. (shrink)

Intensified and extensive data production and data storage are characteristics of contemporary western societies. Health data sharing is increasing with the growth of Information and Communication Technology platforms devoted to the collection of personal health and genomic data. However, the sensitive and personal nature of health data poses ethical challenges when data is disclosed and shared even if for scientific research purposes. With this in mind, the Science and Values Working Group of the (...) class='Hi'>COST Action CHIP ME ‘Citizen's Health through public-private Initiatives: Public health, Market and Ethical perspectives’ identified six core values they considered to be essential for the ethical sharing of health data using ICT platforms. We believe that using this ethical framework will promote respectful scientific practices in order to maintain individuals’ trust in research. We use these values to analyse five ICT platforms and explore how emerging data sharing platforms are reconfiguring the data sharing experience from a range of perspectives. We discuss which types of values, rights and responsibilities they entail and enshrine within their philosophy or outlook on what it means to share personal health information. Through this discussion we address issues of the design and the development process of personal health data and patient-oriented infrastructures, as well as new forms of technologically-mediated empowerment. (shrink)

As we move our social institutions from paper and ink based operations to the electronic medium, we invisibly create a type of surveillance society, a panopticon society. It is not the traditional surveillance society in which government officials follow citizens around because they are concerned about threats to the political order. Instead it is piecemeal surveillance by public and private organizations. Piecemeal though it is, It creates the potential for the old kind of surveillance on an even grander scale. The (...) panopticon is the prison environment described by Foucault in which prison cells are arranged in a large circle with the side facing the inside of the circle open to view. The guard tower is placed in the middle of the circle so that guards can see everything that goes on in every cell. When we contemplate all the electronic data that is now gathered about each of us as we move through our everyday lives --- intelligent highway systems, consumer transactions, traffic patterns on the internet, medical records, financial records, and so on --- there seems little doubt that we are moving into a panopticon. The social issues that arise from this are too numerous to detail here, but data retention is an important part of it. In the paper-and-ink world, documents are filed, files are boxed, boxes are put away or thrown away. The capacity for data retrieval and manipulation is, thereby, limited by the sheer difficulty and cost of storing, finding, searching, and manipulating large numbers of paper files. This inconvenience functions as a mechanism whereby the system forgets past information, not unlike the way we ourselves forget. However, the story is very different in the digital world; digital information is easy to store, easy to search and manipulate, and inexpensive to keep over extensive periods of time. Digitalized information systems tend, therefore, to collect extensive ancillary information and to retain this information indefinitely. Such lack of forgetfulness is likely to hamper the ability of individuals to shed their past, and start over with a clean slate. Concerns about data retention were expressed in the early literature on the social impact of computing, but for the most part the issue has dropped from sight. Rarely, has the social good of discarding accumulated personal data been addressed. In this paper, we want to make the case by examining diverse cases in which retention of information by either business or governmental institutions hinders the ability of individuals to start over or to act autonomously. We hope our argument for the good of forgetfulness will challenge the standard framework in which such issues have traditionally been debated. The privacy debate exemplifies the traditional framework insofar as it has been characterized as involving an inherent tension between, on the one hand, the needs of organizations and institutions for more accurate and efficient information systems so as to further their goals and, on the other hand, the desire of individuals to have information about them kept private. Regan argues against this framing of the privacy issue in favor of one that recognizes the social importance of personal privacy. We will examine the non-forgetfulness of information systems as a problem threatening not just individual interests but social good as well. Cryptography is often cited as the technology that will give us privacy and mediate against surveillance. One of the uses of cryptography, encryption, will allow us, some hope, to create confidentiality and relationships of trust that will facilitate many of the social arrangements we now have and perhaps make them even more secure than they are now. Electronic cash, for example, could be created in such a form that it would have the anonymity associated now with hard cash Others are less optimistic of the potential for cryptography to re-create relationships of trust in the new medium. One important point that already seems clear is that even if encryption technology will protect the confidentiality and integrity of electronic transactions and data, it will NOT stop the observation of traffic patterns on networks. This seems an important distinction to put on the table. Our patterns of communication will continue to be available, no matter what is encrypted, and an amazing amount of information can be gleaned from this data. In a sense, it means content integrity but no anonymity. This will indubitably impact how we interact and with whom we interact. (shrink)

Property rights of personal data have been advocated for some time. From the perspective of economics of law some argued that they could lower transaction costs for contracts involving personal data. This may be the case, but new transaction costs are introduced by propertization and the issue has not been settled. In this paper, I focus on a different and potentially more important aspect. In the actual situation, data collectors externalize costs and internalize benefits. An ownership regime (...) that enables every citizen to hold a personal data account, like a bank account, and that gives people ownership rights over secondary use of personal data could correct these misallocations. I hope to shed new light on the normative implications of the issue by offering normative justifications for property rights of personal data (Sections 2–4). Secondly, I present fundamental goals and building blocks of a property regime of personal data (Section 5) and, thirdly, I illustrate how income from personal data ownership could for instance contribute to financing pensions under proper regulation (Section 6). (shrink)

Data on birth order and parent-offspring relations for 1,601 adolescents participating in the National Longitudinal Study of Adolescent Health were used to test hypotheses about the role of adolescent suicidal behavior in parent-offspring conflict. Among adolescents highly dissatisfied with their mothers, the odds that middleborns would make at least one suicide attempt was 23% that of first- and lastborns (p<.001), but their odds of receiving medical treatment for their attempts was 8.5 times greater than the odds for first- and (...) lastborns (p=.032). The results are tentatively interpreted as supporting the hypothesis that adolescents use suicide attempts to leverage investment from their parents. (shrink)

The quality and quantity of training data are crucial to the performance of a deep-learning-based brain-computer interface system. However, it is not practical to record EEG data over several long calibration sessions. A promising time- and cost-efficient solution is artificial data generation or data augmentation. Here, we proposed a DA method for the motor imagery EEG signal called brain-area-recombination. For the BAR, each sample was first separated into two ones by left/right brain channels, and the (...) artificial samples were generated by recombining the half-samples. We then designed two schemas corresponding to the single- and multi-subject scenarios. Extensive experiments using the classifier of EEGnet were conducted on two public datasets under various training set sizes. In both schemas, the BAR method can make the EEGnet have a better performance of classification. To make a comparative investigation, we selected two common DA methods, and the BAR method beat them. Further, using the proposed BAR for augmentation, EEGnet achieved up to 8.3% improvement than a typical decoding algorithm CSP-SVM, note that both the models were trained on the augmented dataset. This study shows that BAR usage can significantly improve the classification ability of deep learning to MI-EEG signals. To a certain extent, it may promote the development of deep learning technology in the field of BCI. (shrink)

The inferences that can be drawn from Izard’s article are unclear. Izard (2010) suggests that his data raise questions concerning inconsistencies, confusion, and costs in emotion research. I suggest that his data do not speak to the issues of confusion and costs, and that the choice of distinguished scientists may have been inappropriate to meet the goals of Izard’s study. Of course, questions concerning the efficiency of research in emotion studies are interesting. I describe more appropriate ways of (...) addressing such issues. (shrink)

Scientific knowledge production is currently affected by the dissemination of data on an unprecedented scale. Technologies for the automated production and sharing of vast amounts of data have changed the way in which data are handled and interpreted in several scientific domains, most notably molecular biology and biomedicine. In these fields, the activity of data gathering has become increasingly technology-driven, with machines such as next generation genome sequencers and mass spectrometers generating billions of data points (...) within hours, and with little need for human supervision. Given the relative ease and low costs with which datasets can be produced (that is, once a laboratory has been able to afford .. (shrink)

The relatively recent increase in empirical research conducted in business ethics has been accompanied by a growing literature which addresses its present shortcomings and continuing challenges. Particular attention has been focused on the difficulties of obtaining valid and reliable primary data. However, little or no attention has been paid to the use of secondary data. The aim of this paper is to stimulate the interest of business ethics researchers in using secondary data, either as a substitute or (...) complement for primary data, bearing in mind both the benefits and shortcomings of doing so. It is suggested that secondary data not only offer advantages in terms of cost and effort, as conventionally described in research methods books, but also that in certain cases their use may overcome some of the difficulties that particularly afflict business ethics researchers in the gathering of primary data. In order to help business ethicists respond to this call for greater consideration of the potential offered by secondary data, the wide variety of forms that such data may take is indicated and a number of themes regarding their use discussed. (shrink)

U.S. law imposes strict recording and reporting requirements on all entities that manufacture and distribute controlled substances. As a result, the prescription opioid crisis has unfolded in a data-saturated environment. This article asks why the systematic documentation of opioid transactions failed to prevent or mitigate the crisis. Drawing on a recently disclosed trove of 1.4 million internal records from Mallinckrodt Pharmaceuticals, a leading manufacturer of prescription opioids, we highlight a phenomenon we propose to call data diversion, whereby (...) class='Hi'>data ostensibly generated or collected for the purpose of regulating the distribution of controlled substances were repurposed by the industry for the opposite aim of increasing sales at all costs. Systematic data diversion, we argue, contributed substantially to the scale of drug diversion seen with opioids and should become a focus of policy intervention. (shrink)

The debate over environmental, health, and safety regulation has reached a new crescendo in the 104th Congress. So impassioned is the debate on occasion, and so high the feelings, that even the tools of regulatory analysis have become part of the combat.To some, the term cost-benefit analysis, for example, is virtually a swearword, a nefarious tool used by big business to undermine regulations aimed at benefiting the people at large. To others, it is the mechanism for achieving more effective (...) regulation at less cost.This new book on the subject of reforming regulation is aimed at increasing the light and turning down the heat. It consists of an introduction and nine chapters written by scientists, public policy analysts, and economists on various aspects of regulation and regulatory analysis.The book advances the latest knowledge and evidence on risk analysis, cost-benefit analysis, and related techniques for improving regulation--all based on experience and data accumulated over the quarter century since regulation in the areas of environment, health, and safety became a major player on the governmental stage. The strengths and limitations of those analytical tools are an important part of the portrait that is painted, but a common thesis is that, properly used, the tools can be helpful in getting better regulatory results. (shrink)

BackgroundMulti-centre studies generally cost more than single-centre studies because of larger sample sizes and the need for multiple ethical approvals. Multi-centre studies include clinical trials, clinical quality registries, observational studies and implementation studies. We examined the costs of two large Australian multi-centre studies in obtaining ethical and site-specific approvals.MethodsWe collected data on staff time spent on approvals and expressed the overall cost as a percent of the total budget.ResultsThe total costs of gaining approval were 38 % of (...) the budget for a study of 50 centres (mean cost AUD $6960 per site) and 2 % for a study of 11 centres (mean cost AUD $2300 per site). Seventy-five and 90 % of time was spent on repeated tasks, respectively, and many time-consuming tasks, such as reformatting documents, did nothing to improve the study design or participant safety.ConclusionsImprovements have been made to the ethical approval application system, but more gains could be made without increasing risks of harm to research participants. We propose that ethical review bodies and individual sites publish statistics on how long they take to process approvals which could then be nationally benchmarked. (shrink)

Clicks, comments, transactions, and physical movements are being increasingly recorded and analyzed by Big Data processors who use this information to trace the sentiment and activities of markets and voters. While the benefits of Big Data have received considerable attention, it is the potential social costs of practices associated with Big Data that are of interest to us in this paper. Prior research has investigated the impact of Big Data on individual privacy rights, however, there is (...) also growing recognition of its capacity to be mobilized for surveillance purposes. Our paper delineates the underlying issues of privacy and surveillance and presents them as in tension with one another. We postulate that efforts at controlling Big Data may create a trade-off of risks rather than an overall improvement in data protection. We explore this idea in relation to the principles of the European Union’s General Data Protection Regulation as it arguably embodies the new ‘gold standard’ of cyber-laws. We posit that safeguards advocated by the law, anonymization and pseudonymization, while representing effective counter measures to privacy concerns, also incentivize the use, collection, and trade of behavioral and other forms of de-identified data. We consider the legal status of these ownerless forms of data, arguing that data protection techniques such as anonymization and pseudonymization raise significant concerns over the ownership of behavioral data and its potential use in the large-scale modification of activities and choices made both on and offline. (shrink)

This book addresses a range of relevant theoretical issues, including the possibility of an interpersonally comparable measure of well-being, or “utility” metric; the moral value of equality, and how that bears on the form of the social welfare function; social choice under uncertainty; and the possibility of integrating considerations of individual choice and responsibility into the social-welfare-function framework. This book also deals with issues of implementation, and explores how survey data and other sources of evidence might be used to (...) calibrate both a utility metric and a social welfare function, and whether distributive goals are ever best pursued through regulation rather than the tax system. In working through this range of theoretical and practical issues, the book draws from a wide variety of literatures, including philosophical scholarship on equality, responsibility, the nature of well-being, and personal identity over time; the social choice literature within economics; applied economic literatures concerning the measurement of inequality and poverty; legal and policy-analysis scholarship on cost-benefit analysis, environmental justice, and the choice between regulation and taxation; and the burgeoning field of “happiness studies”. (shrink)

This essay details the resurgence of wellness program as employed by large corporations with the aim of reducing healthcare costs. The essay narrows in on a discussion of how Big Data collection practices are being utilized in wellness programs and the potential negative impact on the worker in regards to privacy and employment discrimination. The essay offers an ethical framework to be adopted by wellness program vendors in order to conduct wellness programs that would achieve cost-saving goals without (...) undue burdens on the worker. The essay also offers some innovative approaches to wellness that may well better serve the goals of healthcare cost reduction. (shrink)

In this paper data from a Tanzanian horticultural population are used to assess whether mother’s kin network size predicts several measures of children’s health and well-being, and whether any kin effects are modified by household socioeconomic status. This hypothesis is further tested with a questionnaire on maternal attitudes towards kin. Results show small associations between measures of maternal kin network size and child mortality and children’s growth performance. Together these results suggest that kin positively influence child health, but the (...) effects are small and it is unlikely that the high prevalence of undernutrition observed in this setting is influenced by the availability of kin. (shrink)