​This book describes argumentative tools and strategies that can be used to guide policy decisions under conditions of great uncertainty. Contributing authors explore methods from philosophical analysis and in particular argumentation analysis, showing how it can be used to systematize discussions about policy issues involving great uncertainty. The first part of the work explores how to deal in a systematic way with decision-making when there may be plural perspectives on the decision problem, along with unknown consequences of what we do. (...) Readers will see how argumentation tools can be used for prioritizing among uncertain dangers, for determining how decisions should be framed, for choosing a suitable time frame for a decision, and for systematically choosing among different decision options. Case studies are presented in the second part of the book, showing argumentation in practice in the areas of climate geoengineering, water governance, synthetic biology, nuclear waste, and financial markets. In one example, argumentation analysis is applied to proposals to solve the climate problem with various technological manipulations of the natural climate system, such as massive dispersion of reflective aerosols into the stratosphere. Even after a thorough investigation of such a proposal, doubt remains as to whether all the potential risks have been identified. In such discussions, conventional risk analysis does not have much to contribute since it presupposes that the risks have been identified, whereas the argumentative approach to uncertainty management can be used to systematize discussions. (shrink)

Based on a framework that distinguishes several types, roles and functions of values in science, we discuss legitimate applications of values in the validation of computer simulations. We argue that, first, epistemic valuesEpistemic values, such as empirical accuracyAccuracy and coherence with background knowledgeBackground knowledge, have the role to assess the credibilityCredibility of simulation results, whereas, second, cognitive valuesCognitive values, such as comprehensiveness of a conceptual modelConceptual model or easy handling of a numerical model, have the role to assess the usefulness (...) of a model for investigating a hypothesisHypothesis. In both roles, values perform what we call first-order functions. In addition, cognitive values may also serve an auxiliary function by facilitating the assessment of credibility. As for a third type of values, i.e. social valuesSocial values, their legitimate role consists in specifying and weighing epistemic and cognitive values with respect to practical uses of a simulation, which is considered a second-order function. Rational intersubjective agreementAgreement on how to specify and weigh the different values is supposed to ensure objectivity in simulation validation. (shrink)

Das Buch vermittelt methodische Grundlagen für die Arbeit mit Texten in den Wissenschaften, besonders die Fähigkeit, Inhalt und Argumentation komplexer Texte zu erfassen, wiederzugeben und zu beurteilen. Die Einführung entspricht den fachlichen Standards der Philosophie und Geisteswissenschaften, ist fachübergreifend konzipiert und setzt kein spezifisches Wissen voraus. Der Band richtet sich an Studierende verschiedener Fachrichtungen sowie an Personen, die sich mit dem Wissen anderer Fachrichtungen auseinandersetzen oder im Dialog mit der Öffentlichkeit stehen. Mit Fallbeispielen aus verschiedenen Wissensbereichen und kommentierten Literaturhinweisen.

Science-based methods for assessing the practical rationality of a proposed public policy typically represent assumed future outcomes of policies and values attributed to these outcomes in an idealized, that is, intentionally distorted way and abstracted from aspects that are deemed irrelevant. Different types of methods do so in different ways. As a consequence, they instantiate the properties that result from abstraction and idealization such as conceptual simplicity versus complexity, or comprehensiveness versus selectivity of the values under consideration to different degrees. (...) I hold that none of these methods is best in general. Instead, I opt for the valuation method that is useful for the policy issue in question both in terms of its relevance and in terms of its practicability. Relevance requires that the method can represent and account for what is at stake in the policy issue. Practicability refers to aspects such as easy versus difficult handling of the method. To argue for the claim, I evaluate three types of valuation methods: cost–benefit analysis that rests on unidimensional measurement and ranking, multi-criteria decision analysis that applies multi-dimensional measurement but unidimensional ranking, and non-aggregate indicator systems that operate with multi-dimensional measurement and sometimes also multi-dimensional ranking. Second-order justification indicating whether and how the valuation method chosen is capable of accounting for the substantive value considerations that constitute the real-world policy issue in question renders the conditions on which the results of a proposed policy evaluation rest transparent. (shrink)

Sustainable development calls for choices among alternative policy options. It is a common view that such choices can be justified by appealing to an evaluative ranking of the options with respect to how their consequences affect a broad range of prudential and moral values. Three philosophically motivated proposals for analysing evaluative rankings are discussed: the measured merits model (e.g. Chang), the ordered values model (e.g. Griffin), and the permissible preference orderings model (Rabinowicz). The analysis focuses on the models’ potential for (...) making transparent how an evaluative ranking can contribute to a justified choice among options, particularly in situations that involve diverse values as typically found in debates on sustainable development. Such transparency plays a crucial role when policy rankings are going to be used as arguments in political decision processes. The measured merits model is found to have questionable consequences for the concept of sustainability, while the ordered values model calls for an axiological framework that cannot plausibly be spelled out for sustainability. The permissible preference orderings model is more promising. Its formal structure and its ability to deal with value-pluralism provide an interesting re-structuring of the problem of justifying choices in sustainability issues. (shrink)

Model evaluation for long-term climate predictions must be done on quantities other than the actual prediction, and a comprehensive uncertainty quantificationUncertainty quantification is impossible. An ad hoc alternative is provided by coordinated model intercomparisonsModel intercomparisons which typically use a “one model one vote” approach. The problem with such an approach is that it treats all models as independent and equally plausible. Reweighting all models of the ensemble for performance and dependence seems like an obvious way to improve on model democracy, (...) yet there are open questions on what constitutes a “good” model, how to define dependency, how to interpret robustnessRobustness, and how to incorporate background knowledgeBackground knowledge. UnderstandingUnderstanding those issues have the potential to increase confidence in model predictions in modeling efforts outside of climate scienceClimate science where similar challenges exist. (shrink)

Dealing with complex problems often requires argumentative skills that go beyond the natural abilities even of gifted students and lecturers. We sketch how to reconstruct and evaluate arguments and outline how the fostering of argumentative skills is integrated into the curriculum in Environmental Sciences at the Department of Environmental Systems Sciences of ETH Zurich.

Cognitive values like simplicity, broad scope, and easy handling are properties of a scientific representation that result from the idealization which is involved in the construction of a representation. These properties may facilitate the application of epistemic values to credibility assessments, which provides a rationale for assigning an auxiliary function to cognitive values. In this paper, I defend a further rationale for cognitive values which consists in the assessment of the usefulness of a representation. Usefulness includes the relevance of a (...) representation regarding the investigation of a given problem and its practicability for the users. This rationale builds on the claim that any evaluation of scientific representations should pursue two aims: providing information about their credibility and providing information about their usefulness. Cognitive values relating to the usefulness of a representation and epistemic values relating to its credibility both perform a first-order function. Cognitive values are abstract, and several values with first-order functions may conflict in their application. Thus, in order for cognitive values to account for the sort of problem that is to be investigated by means of a representation, they need to be appropriately specified and weighed. Comprehensiveness, complexity, high resolution, and easy handling, for instance, may be required in a first-order function for model-based prediction of regional climate impacts but not for explaining how the global climate system works. Specifying and weighing cognitive and epistemic values relative to a given problem is a legitimate second-order function of social values. (shrink)

Based on a framework that distinguishes several types, roles and functions of values in science, we discuss legitimate applications of values in the validation of computer simulations. We argue that, first, epistemic values, such as empirical accuracy and coherence with background knowledge, have the role to assess the credibility of simulation results, whereas, second, cognitive values, such as comprehensiveness of a conceptual model or easy handling of a numerical model, have the role to assess the usefulness of a model for (...) investigating a hypothesis. In both roles, values perform what we call first-order functions. In addition, cogni¬tive values may also serve an auxiliary function by facilitating the assessment of credibility. As for a third type of values, i.e. social values, their legitimate role consists in specifying and weighing epistemic and cognitive values with respect to practical uses of a simulation, which is considered a second-order function. Rational intersubjective agreement on how to specify and weigh the different values is supposed to ensure objectivity in simulation validation. (shrink)

Weber's Ideal Type as a Method of Forming the Content of Theoretical Concepts in Social Sciences}. Max Weber introduced the ideal type as the specific method of concept formation in social sciences. But the ideal type is not established in social research. Instead, authors in philosophy of science until today try to reconstruct and interpret what Weber said about ideal types as well as what might be their importance in Weber's social theory. The thesis of the following paper is that (...) the difficulties in understanding Weber's ideal types are linked with Weber's intensional logic of concept formation. The thesis is defended in three steps. The first step deals with Weber's understanding of what is a scientific question in cultural sciences. Secondly Weber's critical arguments against positivism, hegelianism and historism are worked out. Thirdly, Weber's method of concept formation is reconstructed. (shrink)

Model evaluation for long term climate predictions must be done on quantities other than the actual prediction, and a comprehensive uncertainty quantification is impossible. An ad hoc alternative is provided by coordinated model intercomparisons which typically use a “one model one vote” approach. The problem with such an approach is that it treats all models as independent and equally plausible. Reweighting all models of the ensemble for performance and dependence seems like an obvious way to improve on model democracy, yet (...) there are open questions on what constitutes a “good” model, how to define dependency, how to interpret robustness, and how to incorporate background knowledge. Under¬standing those issues has the potential to increase confidence in model predictions in modeling efforts outside of climate science where similar challenges exist. (shrink)

Climate model projections are used to inform policy decisions and constitute a major focus of climate research. Confidence in climate projections relies on the adequacy of climate models for those projections. The question of how to argue for the adequacy of models for climate projections has not gotten sufficient attention in the climate modelling community. The most common way to evaluate a climate model is to assess in a quantitative way degrees of “model fit”; i.e., how well model results fit (...) observation-based data (empirical accuracy) and agree with other models or model versions (robustness). However, such assessments are largely silent about what those degrees of fit imply for a model’s adequacy for projecting future climate. We provide a conceptual framework for discussing the evaluation of the adequacy of models for climate projections. Drawing on literature from philosophy of science and climate science, we discuss the potential and limits of inferences from model fit. We suggest that support of a model by background knowledge is an additional consideration that can be appealed to in arguments for a model’s adequacy for long-term projections, and that this should explicitly be spelled out. Empirical accuracy, robustness and support by background knowledge neither individually nor collectively constitute sufficient conditions in a strict sense for a model’s adequacy for long-term projections. However, they provide reasons that can be strengthened by additional information and thus contribute to a complex non-deductive argument for the adequacy of a climate model or a family of models for long-term climate projections. (shrink)

In climate science, observational gridded climate datasets that are based on in situ measurements serve as evidence for scientific claims and they are used to both calibrate and evaluate models. However, datasets only represent selected aspects of the real world, so when they are used for a specific purpose they can be a source of uncertainty. Here, we present a framework for understanding this uncertainty of observational datasets which distinguishes three general sources of uncertainty: (1) uncertainty that arises during the (...) generation of the dataset; (2) uncertainty due to biased samples; and (3) uncertainty that arises due to the choice of abstract properties, such as resolution and metric. Based on this framework, we identify four different types of dataset ensembles — parametric, structural, resampling, and property ensembles—as tools to understand and assess uncertainties arising from the use of datasets for a specific purpose. We advocate for a more systematic generation of dataset ensembles by using these sorts of tools. Finally, we discuss the use of dataset ensembles in climate model evaluation. We argue that a more systematic understanding and assessment of dataset uncertainty is needed to allow for a more reliable uncertainty assessment in the context of model evaluation. The more systematic use of such a framework would be beneficial for both scientific reasoning and scientific policy advice based on climate datasets. (shrink)

Commercial success of big data has led to speculation that big-data-like reasoning could partly replace theory-based approaches in science. Big data typically has been applied to ‘small problems’, which are well-structured cases characterized by repeated evaluation of predictions. Here, we show that in climate research, intermediate categories exist between classical domain science and big data, and that big-data elements have also been applied without the possibility of repeated evaluation. Big-data elements can be useful for climate research beyond small problems if (...) combined with more traditional approaches based on domain-specific knowledge. The biggest potential for big-data elements, we argue, lies in socioeconomic climate research. (shrink)

In their 2018 paper, Carolina Adler, Gertrude Hirsch Hadorn, Thomas Breu, Urs Wiesmann, and Christian Pohl propose that transferability of knowledge across cases in transdisciplinary research should be thought of in terms of arguments by analogy. We aim to advance this discussion about transferability by examining it in the light of recent ideas about knowledge transfer, extrapolation, and external validity in the philosophy of science. We problematise Adler et al.’s proposal by identifying the ‘transdisciplinarian’s circle’, due to (...) which even knowledge that could be of use in other projects may be identified too late for efficient knowledge transfer to take place. We then suggest that Steel’s ideas on overcoming the ‘extrapolator’s circle’ can serve as a source of inspiration for addressing the issue of the transdisciplinarian’s circle. (shrink)

Keine ausführliche Beschreibung für "Wozu Wissenschaftsphilosophie?" verfügbar.

The author presents and defends three theses: (1) "the first is that it is not profitable for us at present to do moral philosophy; that should be laid aside at any rate until we have an adequate philosophy of psychology." (2) "the second is that the concepts of obligation, And duty... And of what is morally right and wrong, And of the moral sense of 'ought', Ought to be jettisoned if this is psychologically possible...." (3) "the third thesis is that (...) the differences between the well-Known english writers on moral philosophy from sidgwick to the present day are of little importance." (staff). (shrink)

Book reviewed in this article: Balancing Act: The New Medical Ethics of Medicine's New Economics. By E. Haavi Morreim.

The principle that a sentence should be proportionate to the seriousness of the offence remains at the centre of penal practice and scholarly debate. This volume explores highly topical aspects of proportionality theory that require examination and further analysis. von Hirsch and Ashworth explore the relevance of the principle of proportionality to the sentencing of young offenders, the possible reasons for departing from the principle when sentencing dangerous offenders, and the application of the principle to socially deprived offenders. They (...) examine the claim that the principle tends to be associated with greater severity in sentencing, and explore the relevance of penance and of restorative justice to proportionality theory. Their examination of arguments and counter-arguments culminates in a re-statement of the main criteria for proportionate sentencing.The authors are well known for their previous writings on proportionality theory, and this volume broadens the theory to deal with important contemporary issues in crime and punishment. (shrink)

A sense of unity -- Basic objects : a reply to Xu -- Objectivity without objects -- The vagueness of identity -- Quantifier variance and realism -- Against revisionary ontology -- Comments on Theodore Sider's four dimensionalism -- Sosa's existential relativism -- Physical-object ontology, verbal disputes, and common sense -- Ontological arguments : interpretive charity and quantifier variance -- Language, ontology, and structure -- Ontology and alternative languages.

Two main claims are defended in this paper: first, that typical disputes in the literature about the ontology of physical objects are merely verbal; second, that the proper way to resolve these disputes is by appealing to common sense or ordinary language. A verbal dispute is characterized not in terms of private idiolects, but in terms of different linguistic communities representing different positions. If we imagine a community that makes Chisholm's mereological essentialist assertions, and another community that makes Lewis's four-dimensionalist (...) assertions, the members of each community speak the truth in their respective languages. This follows from an application of the principle of interpretive charity to the two communities. (shrink)

The intentionality of sensation -- The first person -- Substance -- The subjectivity of sensation -- Events in the mind -- Comments on Professor R.L. Gregory's paper on perception -- On sensations of position -- Intention -- Pretending -- On the grammar of "Enjoy" -- The reality of the past -- Memory, "experience," and causation -- Causality and determination -- Times, beginnings, and causes -- Soft determinism -- Causality and extensionality -- Before and after -- Subjunctive conditionals -- "Under a (...) description" -- Analysis competition--tenth problem -- A reply to Mr. C.S. Lewis's argument that "naturalism" is self-refuting. (shrink)

A number of jurisdictions, including England and Wales after their adoption of the 1991 Criminal Justice Act, require that sentences be `proportionate' to the severity of the crime. This book, written by the leading architect of `just deserts' sentencing theory, discusses how sentences may be scaled proportionately to the gravity of the crime. Topics dealt with include how the idea of a penal censure justifies proportionate sentences; how a penalty scale should be `anchored' to reduce overall punishment levels; how non-custodial (...) penalties should be graded and used; and how political pressures impinge on sentencing policies. (shrink)

I IT is often declared or evidently assumed that causality is some kind of necessary connexion, or alternatively, that being caused is — non-trivially ...

Past and Present brings together almost two dozen newly collected essays by the distinguished American historian and cultural critic, Gertrude Himmelfarb. Their common theme is the intriguing, often unexpected ways in which the past illuminates the present. The novelist William Faulkner wrote that "The past is never dead. It's not even past." In these essays, Himmelfarb shows the truth of this statement. She helps us find a new perspective on contemporary issues by bringing to bear a trenchant analysis of (...) debates and thinkers of the past. She allows the past to inform the present without distorting either past or present. The essays, unified by the common theme of present and past, are varied. The topics range from the disorders of modern democracy to the challenges of postmodernism, from the Victorian ethos to the Jewish question. The thinkers range from Edmund Burke to Leo Strauss, from Cardinal Newman to Lionel Trilling. The political figures range from Benjamin Disraeli to Winston Churchill, from the American founders to Queen Elizabeth II. The underlying premise and principle of the essays is the conviction that the pursuit of knowledge and truth, however difficult or discomforting, eminently matters, in the "practical life,"as Trilling put it,as in the "moral life."Past and Presentis a notable contribution to this endeavor-to understanding where we have been, where we are now, and where we may be-or should be-going. (shrink)

What is the role of psychoanalysis in today's world? _Yesterday, Today and Tomorrow _presents a selection of papers written by Hanna Segal. The collection introduces the reader to a wide spectrum of insights into psychoanalysis, ranging from current thoughts on the nature of dreaming to new ideas about vision and disillusionment. Her long interest in factors affecting war is pursued in her examination of the psychotic factors, symbolic significance and psychological impact of the events of September the 11th, and the (...) ensuing war on Iraq. The second half of the book discusses Segal's presentations to conferences and symposia from 1969-2000, this material is split into six sections: Models of the mind and mental processes Psychoanalytic technique Segal on Klein Segal on Bion Envy and narcissism Interviews. _Yesterday, Today and Tomorrow_ is a masterly contribution to the field. Segal's clarity of thought and striking clinical illustrations make the book accessible to those new to the field as well as those acquainted with her seminal work. (shrink)