In European countries (excluding the UK and Ireland), official statistics do not use racial or ethnic categories, but instead rely on proxies to collect data about discrimination. In the German microcensus, the proxy category adopted is ‘migration background’ (Migrationshintergrund): an individual has a ‘migration background’ when one or more of their parents does not have German citizenship by birth. We apply a coupled ethical-epistemic analysis to the ‘migration background’ category to illuminate how the epistemic issues contribute to ethical ones. (...) Our central claim is that these ethical-epistemic issues with the ‘migration background’ category are best analysed in terms of Charles Mills's ‘white ignorance’. Appealing to Annette Martín's structural account of white ignorance, we highlight the cyclical reinforcement of ignorance and racial injustice in the use of the ‘migration background’ variable. Colourblind eliminativism about race perpetuates the use of ‘migration background’, which sustains and intensifies racial injustices. (shrink)

This article describes and analyzes the design and functioning of the Statistical Ethics System (SETE) in Colombia’s National Statistical Office. It presents the methodology and general process of planning and implementation of the System, supported by a conceptual analysis of the requirements for an ethical functioning of official statistics. The general objective of the article is to make a practical contribution to the understanding of conceptual and practical features that ought to be considered in the implementation of an (...) ethical system in the operation of the public sector, particularly in the area of the production of official statistics. The text is divided into five parts. In the first part, we make a general introduction to the ethical value of official statistics. In the second and third parts, we make a presentation and analysis of the principles and risks that were selected as the basic ethical framework for the production of official statistics at the National Administrative Department of Statistics (DANE). The fourth section presents the conceptual and practical bases of how SETE operates. The fifth section we present some concluding remarks. (shrink)

Statistics education at all levels includes data collected on human subjects. Thus, statistics educators have a responsibility to educate their students about the ethical aspects related to the collection of those data. The changing statistics education landscape has seen instruction moving from being formula-based to being focused on statistical reasoning. The widely implemented Guidelines for Assessment and Instruction in Statistics Education (GAISE) Report has paved the way for instructors to present introductory statistics to students in (...) a way that is both approachable and engaging. However, with technological advancement and the increase in availability of real-world datasets, it is necessary that instruction also integrate the ethical aspects around data sources, such as privacy, how the data were obtained and whether participants consent to the use of their data. In this article, we propose incorporating ethics into established curricula and integrating ethics into undergraduate-level introductory statistics courses based on recommendations in the GAISE Report. We provide a few examples of how to prompt students to constructively think about their ethical responsibilities when working with data. (shrink)

The purpose of this qualitative study is to answer calls to examine social media, ethical engagement, and marginalized publics. Findings suggest that strategic communication and public relations pr...

It is argued that the practice of omitting outliers when calibrating thromboplastin time, as recommended by the World Health Organization, should not continue unless it can be justified statistically and that possible harmful effects of omitting such data should be investigated.

Ethical conduct is an essential component in research, especially in medical research. Statistical methods for design and analysis are powerful research tools if used properly. Abuse of these principles and methods are just as unethical as other laboratory or clinical misconduct. Inadequate research design can produce worthless results and thus wastes effort and valuable resources. For clinical research, patient resources are wasted. Inappropriate analysis of data can also produce misleading results and conclusions. For clinical research, inferior therapy might be given (...) to patients as a consequence. These ethical concerns can have implications for and affect the individuals responsible for the statistical design and analysis. Examples are provided which illustrate some possible abuses and inappropriate pressures. (shrink)

Industry involvement in the machine learning (ML) community seems to be increasing. However, the quantitative scale and ethical implications of this influence are rather unknown. For this purpose, we have not only carried out an informed ethical analysis of the field, but have inspected all papers of the main ML conferences NeurIPS, CVPR, and ICML of the last 5 years—almost 11,000 papers in total. Our statistical approach focuses on conflicts of interest, innovation, and gender equality. We have obtained four main (...) findings. (1) Academic–corporate collaborations are growing in numbers. At the same time, we found that conflicts of interest are rarely disclosed. (2) Industry papers amply mention terms that relate to particular trending machine learning topics earlier than academia does. (3) Industry papers are not lagging behind academic papers with regard to how often they mention keywords that are proxies for social impact considerations. (4) Finally, we demonstrate that industry papers fall short of their academic counterparts with respect to the ratio of gender diversity. We believe that this work is a starting point for an informed debate within and outside of the ML community. (shrink)

Achieving a good clinical trial design increases the likelihood that a trial will take place as planned, including that data will be obtained from a sufficient number of participants, and the total number of participants will be the minimal required to gain the knowledge sought. A good trial design also increases the likelihood that the knowledge sought by the experiment will be forthcoming. Achieving such a design is more than good sense—it is ethically required in experiments when participants are at (...) risk of harm. This paper argues that doing a power analysis effectively contributes to ensuring that a trial design is good. The ethical importance of good trial design has long been recognized for trials in which there is risk of serious harm to participants. However, whether the quality of a trial design, when the risk to participants is only minimal, is an ethical issue is rarely discussed. This paper argues that even in cases when the risk is minimal, the quality of the trial design is an ethical issue, and that this is reflected in the emphasis the Belmont Report places on the importance of the benefit of knowledge gained by society. The paper also argues that good trial design is required for true informed consent. (shrink)

The purpose of this study was to investigate the relationship between organizational ethical context and the individual ethical decision-making process. In addition, a new statistical approach combining cluster and discriminant analyses was developed to overcome violations of regression assumptions, which are commonly not identified and/or ignored in behavioral and psychological research. Using regressions and this new alternative method, the findings indicated that ethical context does indeed influence the various components of ethical reasoning. However, social desirability was the strongest predictor of (...) ethical decision making, which raises new concerns about how this bias can confound business ethics research. Finally, the findings showed that the alternative method provided more useful and interpretive results, indicating that it has the capacity to influence future empirical work in the field of business ethics, particularly when dealing with data that do not satisfy regression assumptions. The implications and limitations of the study are discussed, and several noteworthy suggestions for future research are provided. (shrink)

Serious ethical violations in medicine, such as sexual abuse, criminal prescribing of opioids, and unnecessary surgeries, directly harm patients and undermine trust in the profession of medicine. We review the literature on violations in medicine and present an analysis of 280 cases. Nearly all cases involved repeated instances of intentional wrongdoing, by males in nonacademic medical settings, with oversight problems and a selfish motive such as financial gain or sex. More than half of cases involved a wrongdoer with a suspected (...) personality disorder or substance use disorder. Despite clear patterns, no factors provide readily observable red flags, making prevention difficult. Early identification and intervention in cases requires significant policy shifts that prioritize the safety of patients over physician interests in privacy, fair processes, and proportionate disciplinary actions. We explore a series of 10 questions regarding policy, oversight, discipline, and education options. Satisfactory answers to these questions will require input from diverse stakeholders to help society negotiate effective and ethically balanced solutions. (shrink)

Statisticians in medicine can disagree on appropriate methodology applicable to the design and analysis of clinical trials. So called Bayesians and frequentists both claim ethical superiority. This paper, by defining and then linking together various dichotomies, argues there is a place for both statistical camps. The choice between them depends on the phase of clinical trial, disease prevalence and severity, but supremely on the ethics underlying the particular trial. There is always a tension present between physicians primarily obligated to (...) their own patients (the weight of 'individual ethics') and ethical committees responsible for the scientific merit of the trial and its long-term implications ('collective ethics'). Individual ethics, it is proposed, favour the Bayesian approach; collective ethics, the frequentist. Though in some situations the choice appears clear-cut, there remain other where both methodologies can be appropriate. (shrink)

All professional ethics are dependent on the epistemology of the profession. The possibility of following a code of ethics, whether the official one or an alternative code, is dependent on being able to obtain knowledge and understand the world. Professional knowledge has to be based on inferences from limited information. Statistics provides the optimal methods for making such inferences, and thus ethical professional conduct requires individual or collective understanding of some statistical thcory and practice. This is demonstrated (...) using the medical profession as an example. Statistical methods are essential in all areas of medicine, in routine medical practice, in screening for disease and in research. Evidence from medical journals, textbooks and research bodies shows that the statistical basis for ethical conduct is lacking. However, there are attempts to improve the situation. (shrink)

Professionals often believe that they must “exercise judgment” in making decisions critical to other people's lives. The relative superiority of statistical prediction rules to intuitive judgment for combining incomparable sources of information to predict important human outcomes leads us to question this personal input belief. Some professionals hence use SPR's to “educate” intuitive judgment, rather than replace it. In psychology in particular, such amalgamation is not justified. If a well-validated SPR that is superior to professional judgment exists in a relevant (...) decision making context, professionals should use it, totally absenting themselves from the prediction. (shrink)

As health care embraces the tenets of evidence-based medicine it is important to ask questions about how evidence is produced and interpreted. This essay explores normative dimensions of evidence production, particularly around issues of setting the tolerable level of uncertainty of results. Four specific aspects are explored: what health care providers know about statistics, why alpha levels have been set at 0.05, the role of randomization in the generation of sufficient grounds of belief, and the role of observational studies. (...) The essay concludes with recommendations to acknowledge the value permeation of outcome measures and suggests that attention to reasoning and argument analysis can augment traditional evidence-based approaches in providing a robust critical approach to medical knowledge. (shrink)

This paper discusses the experiences of a consultant medical statistician who is also a REC member.

Professionals often believe that they must “exercise judgment” in making decisions critical to other people’s lives. The relative superiority of statistical prediction rules to intuitive judgment for combining incomparable sources of information to predict important human outcomes leads us to question this personal input belief. Some professionals hence use SPR’s to “educate” intuitive judgment, rather than replace it. In psychology in particular, such amalgamation is not justified. If a well‐validated SPR that is superior to professional judgment exists in a relevant (...) decision making context, professionals should use it, totally absenting themselves from the prediction. (shrink)

This paper outlines the approaches of two apparently competing schools of statistics. The criticisms made by supporters of Bayesian statistics about conventional Frequentist statistics are explained, and the Bayesian claim that their method enables research into new treatments without the need for clinical trials is examined in detail. Several further important issues are considered, including: the use of historical controls and data routinely collected on patients; balance in randomised trials; the possibility of giving information to patients; patient (...) choice and patient autonomy; and how widely the results of clinical trials can be used. It is concluded that good statistical techniques in the design and analysis of medical studies are essential, but the statistical school used in developing such techniques is relatively unimportant. (shrink)

It is one thing to hold that merely statistical evidence is _sometimes_ insufficient for rational belief, as in typical lottery and profiling cases. It is another thing to hold that merely statistical evidence is _always_ insufficient for rational belief. Indeed, there are cases where statistical evidence plainly does justify belief. This project develops a dispositional account of the normativity of statistical evidence, where the dispositions that ground justifying statistical evidence are connected to the goals (= proper function) of objects. There (...) are strong intuitive motivations for doing this. For we can turn almost any case of _non-justifying_ merely statistical evidence into a case of _justifying_ merely statistical evidence by adding information about the dispositions and goals of the objects involved. The resulting view not only helps us understand when and why merely statistical evidence is normatively significant, but it also helps us understand how statistical evidence relates to more standard forms of evidence (perceptual, testimonial). The emerging view also has surprising applications, as it imposes limitations on the epistemic value of fine-tuning arguments for theism as well as undermines a standard class of case-based arguments for moral encroachment. (shrink)

A major problem for interpersonal aggregation is how to compare utility across individuals; a major problem for decision-making under normative uncertainty is the formally analogous problem of how to compare choice-worthiness across theories. We introduce and study a class of methods, which we call statistical normalization methods, for making interpersonal comparisons of utility and intertheoretic comparisons of choice-worthiness. We argue against the statistical normalization methods that have been proposed in the literature. We argue, instead, in favor of normalization of variance: (...) we claim that this is the account that most plausibly gives all individuals or theories ‘equal say’. To this end, we provide two proofs that variance normalization has desirable properties that all other normalization methods lack, though we also show how different assumptions could lead one to axiomatize alternative statistical normalization methods. (shrink)

Courts and jurors sometimes refuse to assign liability to defendants on the basis of statistics alone, despite their apparent reliability. I argue that this refusal is best understood as a recognition of defendants’ right to security. Understood as a robust good in Philip Pettit’s sense, security requires that someone risking harm to others’ protected interests adopt a disposition of concern that controls against wrongfully harming them. Since trials risk harm, the state must adopt such a disposition. Statistics leave (...) open the possibility of innocence and so wrongful harm in a way that the state cannot ignore; if it does use such statistics, it makes defendants wrongfully insecure. This explanation of the problem of bare statistical evidence is especially apt because security grounds the right to a fair trial and judicial procedural rights more generally. (shrink)

Quantitative researchers often discuss research ethics as if specific ethical problems can be reduced to abstract normative logics (e.g., virtue ethics, utilitarianism, deontology). Such approaches overlook how values are embedded in every aspect of quantitative methods, including ‘observations,’ ‘facts,’ and notions of ‘objectivity.’ We describe how quantitative research practices, concepts, discourses, and their objects/subjects of study have always been value-laden, from the invention of statistics and probability in the 1600s to their subsequent adoption as a logic made (...) to appear as if it exists prior to, and separate from, ethics and values. This logic, which was embraced in the Academy of Management from the 1960s, casts management researchers as ethical agents who ought to know about a reality conceptualized as naturally existing in the image of statistics and probability (replete with ‘constructs’), while overlooking that S&P logic and practices, which researchers made for themselves, have an appreciable role in making the world appear this way. We introduce a different way to conceptualize reality and ethics, wherein the process of scientific inquiry itself requires an examination of its own practices and commitments. Instead of resorting to decontextualized notions of ‘rigor’ and its ‘best practices,’ quantitative researchers can adopt more purposeful ways to reason about the ethics and relevance of their methods and their science. We end by considering implications for addressing ‘post truth’ and ‘alternative facts’ problems as collective concerns, wherein it is actually the pluralistic nature of description that makes defending a collectively valuable version of reality so important and urgent. (shrink)

This paper analyzes statistical decisions during the interim analyses of clinical trials. After some general remarks about the ethical and scientific demands of clinical trials, I introduce the notion of a hard-case clinical trial, explain the basic idea behind it, and provide a real example involving the interim analyses of zidovudine in asymptomatic HIV-infected patients. The example leads me to propose a decision analytic framework for handling ethical conflicts that might arise during the monitoring of hard-case clinical trials. I use (...) computer simulations to show how the framework can assist in reconciling certain ethical conflicts. The framework is partial, lacking the precision of a complete systematization of statistical monitoring procedures in practice. (shrink)

The paper "Environmental Ethics and Cultural Values related to the Philosophical Approaches to Eco-Axiology" examines the complex interplay of ethical concerns about the environment, cultural viewpoints, and human values. This research explores eco-axiology, the philosophical study of values in connection to the natural world, observing at how moral precepts influence how people interact with the natural world. For measuring, the research study used SPSS software and generated results, including descriptive statistics and one-way ANOVA test analysis, which also explains (...) the pair sample analysis between them. The contrast between ecocentrism and anthropocentrism is examined, emphasizing the range of moral viewpoints and the influence of cultural norms on environmental ethics. The usefulness of environmental ethics in solving urgent environmental issues like climate change and biodiversity loss is highlighted, along with its practical implications in policymaking, education, corporate practices, and individual behavior. The research found a positive and significant relationship between environmental ethics and cultural values. Ultimately, this discussion is a call to action, imploring people to practice moral stewardship and substitute a more peaceful coexistence with nature for the sake of both the current and the future generations. (shrink)

This paper recommends how authors of statistical studies can communicate to general audiences fully, clearly, and comfortably. The studies may use statistical methods to explore issues in science, engineering, and society or they may address issues in statistics specifically. In either case, readers without explicit statistical training should have no problem understanding the issues, the methods, or the results at a non-technical level. The arguments for those results should be clear, logical, and persuasive. This paper also provides advice for (...) editors of general journals on selecting high quality statistical articles without the need for exceptional work or expense. Finally, readers are also advised to watch out for some common errors or misuses of statistics that can be detected without a technical statistical background. (shrink)

Responsible research and good science are concepts with various meanings depending on one’s perspective and assumptions. Fellow researchers, research participants, policy makers and the general public also have differing expectations of the benefits of research ranging from accurate and reliable data that extend the body of knowledge, to solutions to societal concerns. Unless these differing constituencies articulate their differing views they may fail to communicate and undermine the value of research to society.

“Responsible research” and “good science” are concepts with various meanings depending on one’s perspective and assumptions. Fellow researchers, research participants, policy makers and the general public also have differing expectations of the benefits of research ranging from accurate and reliable data that extend the body of knowledge, to solutions to societal concerns. Unless these differing constituencies articulate their differing views they may fail to communicate and undermine the value of research to society.

The most compelling extant accounts of explanation casts all explanations as causal. Yet there are sciences, theoretical population biology in particular, that explain their phenomena by appeal to statistical, non-causal properties of ensembles. I develop a generalised account of explanation. An explanation serves two functions: metaphysical and cognitive. The metaphysical function is discharged by identifying a counterfactually robust invariance relation between explanans event and explanandum. The cognitive function is discharged by providing an appropriate description of this relation. I offer examples (...) of explanations from portfolio theory and population genetics that meet this characterisation. In each case the invariance relation holds between a statistical property of an ensemble and a change in structure of the ensemble. In neither case, however, does the statistical property cause the outcome it explains. There are genuine statistical, non-causal scientific explanations. (shrink)

This study provides evidence regarding the level of ethical cognition of business students at the entry to college as compared to a national norm. It also provides comparative evidence on the effects of group versus individual ethical cognition upon completion of a business ethics course. The Principled Score (P-score) from the Defining Issues Test (DIT) was used to measure the ethical cognition of a total sample of 301 business students (273 entering students plus 28 students in a business (...) class='Hi'>ethics course). The results indicate that (1) business students are not significantly different from the national norms at entry to college and (2) group reasoning helps male students improve their P-scores significantly in the business ethics course at a loss of P-score (albeit not statistically significant) for female students. (shrink)

There are many objections to statistical discrimination in general and racial profiling in particular. One objection appeals to the idea that people have a right to be treated as individuals. Statistical discrimination violates this right because, presumably, it involves treating people simply on the basis of statistical facts about groups to which they belong while ignoring non-statistical evidence about them. While there is something to this objection—there are objectionable ways of treating others that seem aptly described as failing to treat (...) them as individuals—it needs to be articulated carefully. First, most people accept that many forms of statistical discrimination are morally unproblematic, let alone morally justified all things considered. Second, even treating people on the basis of putative non-statistical evidence relies on generalizations. Once we construe treating someone as an individual in a way that respects this fact, it becomes apparent: (1) that statistical discrimination is compatible with treating people as individuals, and (2) that one may fail to treat people as individuals even without engaging in statistical discrimination. Finally, there are situations involving the expression of messages of inclusion where we think it is good, morally speaking, that we are not treated as individuals. (shrink)

As artificial intelligence becomes ubiquitous, it will be increasingly involved in novel, morally significant situations. Thus, understanding what it means for a machine to be morally responsible is important for machine ethics. Any method for ascribing moral responsibility to AI must be intelligible and intuitive to the humans who interact with it. We argue that the appropriate approach is to determine how AIs might fare on a standard account of human moral responsibility: a Strawsonian account. We make no claim (...) that our Strawsonian approach is either the only one worthy of consideration or the obviously correct approach, but we think it is preferable to trying to marry fundamentally different ideas of moral responsibility into a single cohesive account. Under a Strawsonian framework, people are morally responsible when they are appropriately subject to a particular set of attitudes—reactive attitudes—and determine under what conditions it might be appropriate to subject machines to this same set of attitudes. Although the Strawsonian account traditionally applies to individual humans, it is plausible that entities that are not individual humans but possess these attitudes are candidates for moral responsibility under a Strawsonian framework. We conclude that weak AI is never morally responsible, while a strong AI with the right emotional capacities may be morally responsible. (shrink)

To achieve accreditation standards and train residents for clinical practice, ACGME placed a lot of emphasis on ethical competence and professionalism. A crucial requirement for enhancing the standard of future medical practice is ethics education. This study sought to identify the requirement for ethics knowledge in clinical training from the perspective of the residents and determine the most effective methods for education. A cross-sectional descriptive study was conducted between March and May 2023. Participants included Lebanese postgraduate medical students, (...) 210 completed a Google Forms survey via WhatsApp. A validated questionnaire adapted from a previous study was used, focusing on demographics, ethical experience, attitudes, educational goals, and training effectiveness. Analyses were performed on IBM SPSS Statistics software (version 26.0) and R software. 210 residents representing a range of specialties participated in the survey. predominantly in internal medicine (54.8%). Residents strongly affirmed the importance of professionalism and ethics education. Participants overwhelmingly agreed that it should improve patient care and clinical decision-making (_p_. (shrink)

Do privacy rights restrict what is permissible to infer about others based on statistical evidence? This paper replies affirmatively by defending the following symmetry: there is not necessarily a morally relevant difference between directly appropriating people’s private information—say, by using an X-ray device on their private safes—and using predictive technologies to infer the same content, at least in cases where the evidence has a roughly similar probative value. This conclusion is of theoretical interest because a comprehensive justification of the thought (...) that statistical inferences can violate privacy rights is lacking in the current literature. Secondly, the conclusion is of practical interest due to the need for moral assessment of emerging predictive algorithms. (shrink)

Ethics training is commonly cited as a primary method for increasing employees' ethical decision making and conduct. However, little is known about how the presence of ethics training can enhance other components of an organization's ethical environment such as employees' perception of company ethical values. Using a national sample of 313 business professionals employed in the United States, the relationship between ethics training and perceived organizational ethics was explored. The results of the analysis provide significant statistical (...) support for the notion that businesspersons employed in organizations that have formalized ethics training programs have more positive perceptions of their companies' ethical context than do individuals employed in organizations that do not. The analysis also indicated that job satisfaction was related to employees' attitudes about their ethical context. The managerial implications of the results are outlined, along with the limitations of the study and recommendations for future research. (shrink)

BackgroundCommentators believe that the ethical decision-making climate is instrumental in enhancing interprofessional collaboration in intensive care units. Our aim was twofold: to determine the perception of the ethical climate, levels of moral distress, and intention to leave one's job among nurses and physicians, and between the different ICU types and determine the association between the ethical climate, moral distress, and intention to leave.MethodsWe performed a cross-sectional questionnaire study between May 2021 and August 2021 involving 206 nurses and physicians in a (...) large urban academic hospital. We used the validated Ethical Decision-Making Climate Questionnaire and the Measure of Moral Distress for Healthcare Professionals tools and asked respondents their intention to leave their jobs. We also made comparisons between the different ICU types. We used Pearson's correlation coefficient to identify statistically significant associations between the Ethical Climate, Moral Distress, and Intention to Leave.ResultsNurses perceived the ethical climate for decision-making as less favorable than physicians. They also had significantly greater levels of moral distress and higher intention to leave their job rates than physicians. Regarding the ICU types, the Neonatal/pediatric unit had a significantly higher overall ethical climate score than the Medical and Surgical units and also demonstrated lower moral distress scores and lower “intention to leave” scores compared with both the Medical and Surgical units. The ethical climate and moral distress scores were negatively correlated ; moral distress and "intention to leave" was positively correlated ; and ethical climate and “intention to leave” were negatively correlated.ConclusionsSignificant differences exist in the perception of the ethical climate, levels of moral distress, and intention to leave between nurses and physicians and between the different ICU types. Inspecting the individual factors of the ethical climate and moral distress tools can help hospital leadership target organizational factors that improve interprofessional collaboration, lessening moral distress, decreasing turnover, and improved patient care. (shrink)

The cognitive developmental theory of ethics suggests that there is a positive relationship between ethical reasoning and ethical behavior. In this study, we trained a sample of accounting and finance students in performing competitive stock trading in our state-of-the-art trading room. The subjects then performed trading of stocks under two experimental conditions: insider information, and no-insider information where significant performance-based financial awards were at stake. We also administered the Defining Issues Test (DIT). Ethical behavior, as the dependent variable was (...) measured in a binary scale: whether the subjects used insider information for trading of stocks or not. Ethical reasoning as measured by the DIT P-score indicated statistically significant effect on ethical behavior. The results have important implications for recruitment and training of professionals engaged in the use of financial markets for securities trading. (shrink)

Although statistically common, and legal since 1973, abortion still bears significant stigma--a proverbial scarlet A. Fear of this stigma leads most of the women and men who are part of the 21% of American pregnancies that end in abortion to remain silent. This book brings the story of ordinary abortion out of the shadows and invites a new conversation about its actual practice, ethics, politics, and law. Katie Watson lends her incisive legal and medical ethics expertise to navigate (...) wisely and respectfully one of the most divisive topics of contemporary life. (shrink)

We start with the ambition -- dating back to the early days of the semantic web -- of assembling a significant portion human knowledge into a contradiction-free form using semantic web technology. We argue that this would not be desirable, because there are concepts, known as essentially contested concepts, whose definitions are contentious due to deep-seated ethical disagreements. Further, we argue that the ninetenth century hermeneutical tradition has a great deal to say, both about the ambition, and about why it (...) fails. We conclude with some remarks about statistics. (shrink)