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.

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)

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)

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)

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)

Fundamental terms in the field of ecology are ambiguous, with multiple meanings associated with them. While this could lead to confusion, discord, or even tests that violate core assumptions of a given theory or model, this ambiguity could also be a feature that allows for new knowledge creation through the interconnected nature of concepts. We approached this debate from a quantitative perspective, and investigated the cost of ambiguity related to definitions of ecological units in ecology related to the general (...) term “community.” We did a meta-analysis of tests associated with two bodies of literature, Hubbell’s unified neutral theory of biodiversity and biogeography and Diamond’s assembly rules, that rely on a specific ecological unit that assumes that species are existing within a local area and that they have overlapping resource needs. We predicted that if ambiguous terminology is widespread, then researchers will have tested them with many different ecological units, that in addition some of these ecological units will violate the core assumptions of the theory, and finally that the overall level of support for a theory will be stronger if appropriate ecological units were used. We found that indeed multiple different ecological units were used in the literature to test both theories, with 65 percent appropriate ecological units for neutral theory tests, and only 6 percent for assembly rule tests. Finally, there was some evidence that the support for a theory depended on whether appropriate ecological units were used for neutral tests, but there was not enough data for the assembly rule tests. These results thus show that ambiguous terminology in ecology is having measurable effects on research and is not of solely philosophical concern. We advocate that authors be explicit in their writing and outline core assumptions of theories, that researchers apply these consistently in their tests, and that readers be attentive to what is written and cognizant of their potential biases. (shrink)

Since the solution to many public health problems depends on research, it is critical for the progress and well-being for the patients that we can trust the scientific literature. Misconduct and poor laboratory practice in science threatens the scientific progress, leads to loss of productivity and increased healthcare costs, and endangers lives of patients. Data duplication may represent one of challenges related to these problems. In order to estimate the frequency of data duplication in life science literature, a (...) systematic screen through 120 original scientific articles published in three different cancer related journals [journal impact factor 20] was completed. The study revealed a surprisingly high proportion of articles containing data duplication. For the IF 20 journals, 25 % of the articles were found to contain data duplications. The IF 5–10 journal showed a comparable proportion. The proportion of articles containing duplicated data was comparable between the three journals and no significant correlation to journal IF was found. The editorial offices representing the journals included in this study and the individual authors of the detected articles were contacted to clarify the individual cases. The editorial offices did not reply and only 1 out of 29 cases were apparently clarified by the authors, although no supporting data was supplied. This study questions the reliability of life science literature, it illustrates that data duplications are widespread and independent of journal impact factor and call for a reform of the current peer review and retraction process of scientific publishing. (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)

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)

Taking support from ego-depletion theory, this study examines ego depletion as a mechanism that explains how employees’ organizational citizenship behavior leads to antagonistic consequences, i.e., service sabotage. Employees’ positive psychological capital is considered a moderator. PROCESS macro was used to test all the hypotheses using time-lagged, dyadic data collected from 420 employees and their 112 their supervisors associated with the service industry in China. This study finds that employees’ exhibition of OCB is positively linked to ego depletion, which in (...) turn drives service sabotage behavior. Furthermore, employees’ PsyCap weakens the effect of OCB on employees’ ego depletion. This study highlights the dark side of OCB, the mechanism through which it causes adverse effects, and the moderating effect of PsyCap. It also provides insights to the organizations for managing service sector employees to effectively interact with customers. (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)

Adequate Citation of data sets is crucial to the encouragement of data sharing, to the integrity and cost-effectiveness of science and to easy access to the work of others. The citation behavior of social scientists who have published based on shared data was examined and found to be inconsistent with important ideals of science. Insights gained from the social sciences, where data sharing is somewhat customary, suggest policies and incentives that would foster adequate citation by (...) secondary users, and greater openness and sharing in other disciplines. (shrink)

This study examines whether penalties issued to Chinese listed companies by securities regulators for violations of corporate law affect the cost of debt, and the moderating role of corporate social responsibility fulfillment on this relationship. Our sample consists of firms listed on Shanghai and Shenzhen stock exchanges from 2011 to 2017 and the data are collected from the announcements of China Securities Regulatory Commission. The findings are as follows: punishment announcements by regulatory authorities increase the cost of (...) debt; and the effect of punishment announcements on the cost of debt is partially offset by prior CSR performance. These findings are shown to be robust. The reputation insurance effect of CSR is more pronounced in state-owned enterprises and in an institutional environment with low marketization, a weak legal environment, and low information transparency. The findings support the reputation insurance hypothesis of CSR and employ the cost of debt as a governance mechanism. (shrink)

We highlight how Corporate Social Responsibility can be strategically used against the negative perception from earnings management. Using international data, we analyse the effect of CSR and EM on the cost of capital and corporate reputation. Results confirm that CSR strategy is positively valued by investors and other stakeholders. Contrary to EM, CSR has a positive effect on corporate reputation and lowers the cost of capital. In addition, we also find that the favourable effect of CSR on (...) cost of capital is consistently more intense in firms that show signs of EM indicating that the market does not identify when CSR practices are used as a strategy to mask EM. We also demonstrate how institutional factors influence the above relationship. (shrink)

During the “age of austerity” the UK government has progressively limited free health services for “overseas visitors” on the grounds of fairness and frugality. This is despite the fact that the cost of the additional bureaucracy required by the new system and the public health consequences are expected to exceed the sums saved. In this article I explore the interaction between the discourses of austerity and xenophobia as they relate to migrants’ access to healthcare. By examining the available (...) class='Hi'>data and adjudicating various moral arguments, I cast doubt on the claim that the current charging regulations are cost-effective and fair. I instead contend that if the UK is concerned with running a health service that is economically-sustainable and morally-defensible, it is critical that migrants are welcomed, both as staff and as patients. I conclude by arguing that xenophobia has precipitated changes to the health service which do not qualify as “austerity” in the way that is claimed, but rather deliberately produce a “hostile environment” for migrants, despite this very likely generating economic losses. (shrink)

For decades, healthcare has relied on data-driven algorithms to guide clinical practice. Recent advances in machine learning have opened up new possibilities in the field, enabling detailed analyse...

This chapter addresses the morality of two types of national security electronic surveillance (SIGINT) programs: the analysis of communication “metadata” and dragnet searches for keywords in electronic communication. The chapter develops a standard for assessing coercive government action based on respect for the autonomy of inhabitants of liberal states and argues that both types of SIGINT can potentially meet this standard. That said, the collection of metadata creates opportunities for abuse of power, and so judgments about the trustworthiness and competence (...) of the government engaging in the collection must be made in order to decide whether metadata collection is justified in a particular state. Further, the moral standard proposed has a reflexive element justifying adversary states’ intelligence collection against one another. Therefore, high-tech forms of SIGINT can only be justified at the cost of justifying cruder versions of signals intelligence collection practiced by a state’s less-advanced adversaries. (shrink)

This research explores the harmful effects of negative workplace gossip (NWG) on targets and organizations, including its impacts on helping behavior and knowledge hiding. The mediating role of guanxi closeness and the moderating role of need for affiliation are also examined. The study, based on conservation of resources theory, collected data from 526 employees in the hospitality industry in China, using a three-wave survey design. Hierarchical multiple regression analysis was employed to test the hypotheses. The empirical results showed that (...) NWG was a strong predictor of reduced helping behavior and increased knowledge hiding; and that guanxi closeness mediated both the negative relationship between NWG and helping behavior, and the positive relationship between NWG and knowledge hiding. Additionally, need for affiliation was shown to act as a moderator between NWG and guanxi closeness: high need for affiliation amplified the negative impact of NWG on guanxi closeness, and then further affected employees’ helping behavior and knowledge hiding. This study therefore offers an important new perspective for interpreting the detrimental effects of negative gossip in organizations, providing not just theoretical advances but practical ways in which managers can proactively reduce these impacts. (shrink)

The objective of this research is to investigate the effects of corporate governance scores and environmental, social, and governance scores (ESG) on firms’ cost of capital in emerging countries. The sample consists of 800 firm-year observations collected from Thomson Reuters. We analyze the data using panel-corrected standard errors (PCSE) regressions, which correct for heteroskedasticity issues and contemporaneous errors in the data. When moderated with emerging market variable, our findings indicate that in the financial sector, corporate governance and (...) ESG score is negatively associated with cost of capital. Nonetheless, in the nonfinancial sector, no evidence is found on the effect of corporate governance and ESG on cost of capital. Our findings indicate that emerging countries, different institutional, ownership, and legal structural has an effect on corporate governance and ESG implementation. (shrink)

On many important aspects of the economic life of the rural population there is little that can be said. The complaint about the lack of secure data regarding the rural population of the ancient world has often been repeated, and there is no reason to restate the remarks about the lack of interest in the ancient sources for this topic. There is a danger, however, that absence of information may lead to an over-simplified picture of what actually happened. It (...) is generally assumed that 80 or 90% of the ancient population was engaged in agriculture and that, conversely, only a small part of the population was engaged in non-agricultural work. Ancient historians have a tendency to treat the various sectors in the economy—commercial farming, subsistence farming, industries, and services —as strictly detached from each others. This is too simplistic a picture. We should not underestimate the importance of the employment of various economic strategies by the ancient farming population. This means that a peasant might also have been from time to time a charcoal maker, muleteer, or textile worker. If so, then agriculture and the non-agricultural sectors were indissolubly connected. (shrink)

The World Health Organization defined COVID-19 as a pandemic on March 11, due to the spread of the new SARS-CoV-2 coronavirus in all continents. Italy had already witnessed a very fast spread that brought the Government to place the entire country under quarantine on March 11, reaching more than 30,700 fatalities in 2 months. We hypothesized that the pandemic and related compulsory quarantine would lead to an increase of anxiety state and protective behaviors to avoid infections. We aimed to investigate (...) whether protective behaviors might have been enhanced or limited by anxiety and emotional reactions to previous experience of stressful conditions. We collected data from 618 Italian participants, by means of an online survey. Participants were asked to rate their level of worry for the pandemic, and to complete two questionnaires measuring the anxiety level: the state-trait anxiety inventory and the Pre-traumatic stress reaction checklist. Finally, the respondents were also asked to report about their compliance with protective behaviors suggested to avoid the spread of the virus. Results show that respondents with higher levels of worry reported higher levels of anxiety and pre-traumatic reactions, with positive correlations among the three measurements, and that higher frequency of the three protective behaviors were put in place by respondents with higher levels of worry. Moreover, regression analysis showed that worry for COVID-19 was most predicted by age, anxiety levels, and Pre-traumatic stress. These results could be interpreted in an evolutionary framework, in which the level of worry leads persons to become more cautious maximizing long-term survival at the cost of short-term dysregulation. (shrink)

Data analytics and data-driven approaches in Machine Learning are now among the most hailed computing technologies in many industrial domains. One major application is predictive analytics, which is used to predict sensitive attributes, future behavior, or cost, risk and utility functions associated with target groups or individuals based on large sets of behavioral and usage data. This paper stresses the severe ethical and data protection implications of predictive analytics if it is used to predict sensitive (...) information about single individuals or treat individuals differently based on the data many unrelated individuals provided. To tackle these concerns in an applied ethics, first, the paper introduces the concept of “predictive privacy” to formulate an ethical principle protecting individuals and groups against differential treatment based on Machine Learning and Big Data analytics. Secondly, it analyses the typical data processing cycle of predictive systems to provide a step-by-step discussion of ethical implications, locating occurrences of predictive privacy violations. Thirdly, the paper sheds light on what is qualitatively new in the way predictive analytics challenges ethical principles such as human dignity and the (liberal) notion of individual privacy. These new challenges arise when predictive systems transform statistical inferences, which provide knowledge about the cohort of training data donors, into individual predictions, thereby crossing what I call the “prediction gap”. Finally, the paper summarizes that data protection in the age of predictive analytics is a collective matter as we face situations where an individual’s (or group’s) privacy is violated using dataotherindividuals provide about themselves, possibly even anonymously. (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)

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)

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)

Although the majority of young children now spend time in nonparental child care, we know relatively little about who provides this care and how its costs are distributed among parents, government, and other family members. In this article we use data from a survey of New York City families with children younger than six to estimate the contribution of parental expenditures, government assistance, and the market value of “donated” caregiving time by family, friends, and relatives. We conclude that uncompensated (...) caregivers provide a substantial share of child care that is “invisible” in conventional economic measures. (shrink)

BackgroundThe amount and value of researchers’ peer review work is critical for academia and journal publishing. However, this labor is under-recognized, its magnitude is unknown, and alternative ways of organizing peer review labor are rarely considered.MethodsUsing publicly available data, we provide an estimate of researchers’ time and the salary-based contribution to the journal peer review system.ResultsWe found that the total time reviewers globally worked on peer reviews was over 100 million hours in 2020, equivalent to over 15 thousand years. (...) The estimated monetary value of the time US-based reviewers spent on reviews was over 1.5 billion USD in 2020. For China-based reviewers, the estimate is over 600 million USD, and for UK-based, close to 400 million USD.ConclusionsBy design, our results are very likely to be under-estimates as they reflect only a portion of the total number of journals worldwide. The numbers highlight the enormous amount of work and time that researchers provide to the publication system, and the importance of considering alternative ways of structuring, and paying for, peer review. We foster this process by discussing some alternative models that aim to boost the benefits of peer review, thus improving its cost-benefit ratio. (shrink)

Adequate Citation of data sets is crucial to the encouragement of data sharing, to the integrity and cost-effectiveness of science and to easy access to the work of others. The citation behavior of social scientists who have published based on shared data was examined and found to be inconsistent with important ideals of science. Insights gained from the social sciences, where data sharing is somewhat customary, suggest policies and incentives that would foster adequate citation by (...) secondary users, and greater openness and sharing in other disciplines. (shrink)

Our understanding of civilian casualties is not based solely on what is reported but also who reports these human rights abuses. Competing interests at the data collection stage have impeded the development of a more thorough understanding of civilian victimization during conflict. We find that current definitions of “casualty” neglect nonphysical forms of victimization and that group-based definitions of “civilian” can obscure the role of different individuals in conflict. We contend that the dominant definition of “civilian casualty” should be (...) expanded to include the full array of harm inflicted on individuals, including psychological harm and what we refer to as multiple casualties of conflict. Expanding our definition of civilian casualties to include different degrees and kinds of wartime victimization would improve both documentation and analysis. We propose several areas for improvement in terms of the documentation of civilian casualties as well as potential solutions to the problems we identify. (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)

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)

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)

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)

Human capital and ICT have a significant role in determining human development. The impacts of ICT and human capital on green growth and environmental sustainability should be explored for sustainable economic development. This research contributes to the literature on the role of ICTs and human capital in the determination of green growth and environmental performance. Based on time-series data 1990–2019, the study intends to investigate the impact of ICTs and human capital on environmental and green growth performance for China. (...) The study reports that ICTs tend to reduce CO2 emissions and improve green growth in the long-run. However, education reduces CO2 emissions in the long-run but does not produce any significant impact on green growth in the long-run. It is suggested that government should invest in environmental efficiency and environmental technologies simultaneously with human capital that could significantly contribute to pollution reduction. Lastly, policies to increase human capital should be implemented simultaneously with policies to promote ICTs contribution in order to confirm green growth and environmental protection. (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)

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)

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)

Physicians vary in their moral judgments about health care costs. Social intuitionism posits that moral judgments arise from gut instincts, called “moral foundations.” The objective of this study was to determine if “harm” and “fairness” intuitions can explain physicians’ judgments about cost-containment in U.S. health care and using cost-effectiveness data in practice, as well as the relative importance of those intuitions compared to “purity”, “authority” and “ingroup” in cost-related judgments.

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)

Japan has one of the highest numbers of high-cost medical devices installed relative to its population. While evaluations of the distribution of these devices traditionally involve simple population-based assessments, an indicator that includes the demand of these devices would more accurately reflect the situation. The purpose of this study was to develop an indicator of the supply–demand balance of such devices, using examples of magnetic resonance imaging scanners (MRI) and extracorporeal shockwave lithotripters (ESWL), and to investigate the relationship between (...) this indicator, personnel distribution statuses and operating statuses at the prefectural level. -/- Using data from nation-wide surveys and claims data from 16 hospitals, we developed an indicator based on the ratio of the supplied number of device units to the number of device units in demand for MRI and ESWL. The latter value was based on patient volume and utilization proportion. Correlation analyses were conducted between the supply–demand balances of these devices, personal distribution and operating statuses. -/- Comparisons between our indicator and conventional population-based indicators revealed that 15% and 30% of prefectures were at risk of underestimating the availability of MRI and ESWL, respectively. The numbers of specialist personnel/device units showed significant, negative correlations with our indicators in both devices. -/- Utilization-based analyses of health care resource placement and utilization status provide a more accurate indication than simple population-based assessments, and can assist decision makers in reviewing gaps between health policy and management. Such an indicator therefore has the potential to be a tool in helping to improve the efficiency of the allocation and placement of such devices. (shrink)

With the increase in the costs of providing education and concerns about financial responsibility, heightened consideration of accountability and results, elevated awareness of the range of teacher skills and student learning styles and needs, more focus is being placed on the promises offered by online software and educational technology. One of the most heavily marketed, exciting and controversial applications of edtech involves the varied educational programs to which different students are exposed based on how big data applications have evaluated (...) their likely learning profiles. Characterized most often as ‘personalized learning,’ these programs raise a number of ethical concerns especially when used at the K-12 level. This paper analyzes the range of these ethical concerns arguing that characterizing them under the general rubric of ‘privacy’ oversimplifies the concerns and makes it too easy for advocates to dismiss or minimize them. Six distinct ethical concerns are identified: information privacy; anonymity; surveillance; autonomy; non-discrimination; and ownership of information. Particular attention is paid to whether personalized learning programs raise concerns similar to those raised about educational tracking in the 1950s. The paper closes with discussion of three themes that are important to consider in ethical and policy discussions. (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)

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)

This paper investigates the conceptual possibility for, and the institutions relating to a positive right of private property to data. To do so, it distinguishes between structured data, as a designator, and datapoints, which are data embedded in the timeline. The reasoning being explored here is: the agents generating datapoints – he source of the data – have a right to private property to the datapoints they generate. The agents, then, can choose to retain the datapoints (...) or to sell them to data-users, aggregators, etc. Once these data-users render property of data themselves, they can further market it. There are, however, challenges to this view. One is the relative high cost of managing private property to data versus the relative low cost of misappropriating data and datapoints. The other is network effects: more precisely, data created or enriched in networks. (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)

This article presents an analysis and evaluation of what I call the “I’m not stupid” argument. This argument has ancient roots, which lie in Aristotle’s famous description of the weak man’s and strong man’s arguments. An “I’m not stupid” argument is typically used in a context of accusation and defense, by a defendant who argues that they did not commit the act of which they have been accused. The analysis of this type of argument takes the shape of an argumentative (...) pattern, which displays a full-fledged representation of its argumentation structure. It is based on a collection of ten contemporary instances of the “I’m not stupid” argument. Although ten instances constitute a small collection, the wide variation in the argumentative elements that they express explicitly or leave implicit made it possible to identify five new key premises in comparison with previous analyses of the weak man’s and strong man’s arguments (Walton, Tindale and Gordon 2014 in _Argumentation_ 28:85–119, 2014; Walton 2019 in _Argumentation_ 33:45–74, 2019). These new premises show that the crucial point of an evaluation of this argument is the arguer's supposedly rational character in making a gain-loss calculation. They also show that we need empirical data to strengthen our analyses of argument schemes and argumentation structures. (shrink)