Eric Weil, who died at Nice on February 1, 1977, was a prominent philosopher and an authority on Hegel. He was born at Parchim on June 6, 1904. From 1922 to 1928 he studied under E. Cassirer at Hamburg and Berlin. His doctoral thesis “Die Philosophie des Pietro Pomponazziz” was published in 1932 in the Archiv für Geschichte der Philosophie. In 1933 he migrated to France, received French nationality, took part in World War II, and became a prisoner of war (...) in Germany. From 1946 to 1956 he taught in the Ecole Practique des Hautes Etudes in Paris, graduated again, this time in France, with La Logique de la philosophie, his main work published in 1950, was a professor at the universities of Lille, where he organized the Congress of the Internationale Hegel Vereinigung in 1968, and Nice, received an honorary degree at Munster in 1969. His main works are also: Hegel et l’Etat, Philosophie politique, Philosophie morale, Problemes kantiens, Essais et Conférences. For a complete bibliography up to 1970 see Archives de Philosophie 1970, p. 605–622. He helped to get rid of some false interpretations rejected also emphatically the marxist interpretation of Hegel. For Weil, as for, so he thought, Aristotle and Hegel, philosophy is an endless endeavor to build up a “discours coherent” of reality as a whole. Man is a finite being, needy, compelled to act in order to live but, as he is at the same time reasonable, he may live meaningfully, promote freedom and justice, undertake to understand himself and the whole of reality, even violence and error, and mainly the behavior of other people and their conceptions of the world. As philosophy considers man not as an object but as a subject, it is not a science properly but, mainly as the logic of philosophy, it is as coherent and as strict as a science. Weil disliked “constructivism” - as deducing a system from a “necessary being”, or predicting the course of history. Though he was often a fellow traveller of Hegel, he acknowledged more and more that he felt a kantian, but a “post-hegelian” kantian. (shrink)

D’Hondt's trilogy is a defence of Hegel against widespread criticisms. Hegel has been indicted for being the philosopher of reaction against the Revolution, a bourgeois hostile to any political or social improvement and, last but not least, the builder of an a priori system of concepts foreign to the changing and living reality.

Under the balmy Mediterranean skies of Santa Margherita Ligure on the beautiful Italian Riviera, forty Hegelian scholars from nine countries put their heads together on the theme “Hegel’s Philosophie des subjectiven Geistes” at the Conference of the Internationale Hegel-Vereinigung, May 24–27, 1973. Enjoying the generosity of the Italian Government and the official hospitality of the Municipality of Santa Margherita, the participants heard and discussed four papers by German scholars, two each by Italians and Americans, and one each by a Dutch (...) and a French scholar. Professor Valerio Verra of the University of Rome served as host, and Professor Dieter Henrich, President of the Internationale Hegel-Vereinigung, introduced the theme of the Conference and officiated the proceedings. Chairing individual sessions and participating in the discussions were such internationally known figures as Hans-Georg Gadamer of Germany, Eric Weil and Marcel Régnier of France, W. H. Walsh and Anthony Kenny of Great Britain, and Enrico de Negri of Italy. (shrink)

This article investigates the meaning of doing good and doing well in positive business. It examines the relationship between the two expressions and discusses their relevance, shedding new light on the significance of ‘positive’ in positive business and positive organizational scholarship. Thus, this article illuminates the ultimate end of positive states and practices. ‘Positive’ primarily represents values and assumptions. These lead to the creation of beneficial situations and marked improvements, which put individuals and organizations on an upward trajectory toward achieving (...) excellent functioning, assuring profitability in addition to sustainability and social well-being. Doing well, with reference to economic performance and profits, is partly constitutive of doing good. This presents a new approach regarding the role of economic outcomes in positive business and POS. It means that financial criteria do not have priority. Profits are considered vital and necessary, but the final ‘raison d'être’ of positive states and practices is the overall well-being of the stakeholders. (shrink)

Background In the last years, there has been an increase in publication of systematic reviews of normative literature or of normative information in bioethics. The aim of a systematic review is to search, select, analyse and synthesise literature in a transparent and systematic way in order to provide a comprehensive and unbiased overview of the information sought, predominantly as a basis for informed decision-making in health care. Traditionally, one part of the procedure when conducting a systematic review is an appraisal (...) of the quality of the literature that could be included. Main text However, while there are established methods and standards for appraising e.g. clinical studies or other empirical research, quality appraisal of normative literature in the context of a systematic review is still rather a conundrum – not only is it unclear how it could or should be done, but also the question whether it necessarily must be done is not settled yet. Based on a pragmatic definition of “normative literature” as well as on a typology of different types of systematic reviews of normative literature/information, this paper identifies and critically discusses three possible strategies of conducting quality appraisal. Conclusions The paper will argue that none of the three strategies is able to provide a general and satisfying solution to the problems associated with quality appraisal of normative literature/information. Still, the discussion of the three strategies allows outlining minimal conditions that elaborated strategies have to meet in future, and facilitates sketching a theoretically and practically promising strategy. (shrink)

In several accounts of what models are and how they function a specific view dominates. This view contains the following characteristics. First, there is a clear-cut distinction between theories, models and data and secondly, empirical assessment takes place after the model is built. This view in which discovery and justification are disconnected is not in accordance with several practices of mathematical business-cycle model building. What these practices show is that models have to meet implicit criteria of adequacy, such as satisfying (...) theoretical, mathematical and statistical requirements, and be useful for policy. In order to be adequate, models have to integrate enough items to satisfy such criteria. These items include besides theoretical notions, policy views, mathematisations of the cycle and metaphors also empirical data and facts. So, the main thesis of this chapter is that the context of discovery is the successful integration of those items that satisfy the criteria of adequacy. Because certain items are empirical data and facts, justification can be built-in. (shrink)

Economics is dominated by model building, therefore a comprehension of how such models work is vital to understanding the discipline. This book provides a critical analysis of the economist's favourite tool, and as such will be an enlightening read for some, and an intriguing one for others.

This paper critically reviews and discusses the concept of organizational virtuousness as presented in positive organizational scholarship. It identifies Kim S. Cameron, David S. Bright, and Arran Caza as the most influential researchers within this field and portrays commonalities, differences, and inconsistencies among the various notions of organizational virtuousness offered in positive organizational literature throughout the last 15 years. While the commonalities refer to attributes, levels of analyses, outcomes, and methodology, the variances concern the locus of residence, the priority of (...) outcomes, indicators, supporting features and the virtues included in positive organizational virtuousness. The analysis further discusses the strengths and weaknesses of these differences and stresses the challenges which the POS movement needs to face in order to clarify its definition of organizational virtuousness and, maybe, converge on one unified meaning. Finally, these challenges are summarized and linked to future research proposals which offer potential ideas on how to further develop the concept of positive organizational virtuousness. (shrink)

Since the February 2020 publication of the article ‘Flattening the curve’ in The Economist, political leaders worldwide have used this expression to legitimize the introduction of social distancing measures in fighting Covid-19. In fact, this expression represents a complex combination of three components: the shape of the epidemic curve, the social distancing measures and the reproduction number \. Each component has its own history, each with a different history of control. Presenting the control of the epidemic as flattening the curve (...) is in fact flattening the underlying natural-social complexity. The curve that needs to be flattened is presented as a bell-shaped curve, implicitly suggesting that the pathogen’s spread is subject only to natural laws. The \ value, however, is, fundamentally, a metric of how a pathogen behaves within a social context, namely its numerical value is affected by sociopolitical influences. The jagged and erratic empirical curve of Covid-19 illustrates this. Although the virus has most likely infected only a small portion of the total susceptible population, it is clear its shape has changed drastically. This changing shape is largely due to sociopolitical factors. These include shifting formal laws and policies, shifting individual behaviors as well as shifting various other social norms and practices. This makes the course of Covid-19 curve both erratic and unpredictable. (shrink)

Music plays an important role in business because it affects consumer behavior. However, companies do not only value music as a tool to engrain their brands in the mind of their customers, they have also discovered the positive effects that music at work can have on employees’ job performance. The challenges of today’s organizations, nevertheless, are manifold and their responsibilities go much further than just to assure some reasonable financial results. Nowadays most stakeholders and customers expect companies to be run (...) ethically and in strict compliance with the law. Today’s leaders need to be equipped with strategies and instruments that ensure ethical behavior within their organizations. In this paper I argue that music can also represent a practical tool to foster ethical conduct at work. Music helps organizations to do good and well. (shrink)

The kinds of models discussed in this paper function as measuring instruments. We will concentrate on two necessary steps for measurement: (1) the search of a mathematical representation of the phenomenon; (2) this representation should cover an invariant relationship between the properties of the phenomenon to be measured and observable accociated attributes of a measuring instrument. Therefore, the measuring instrument should function as a nomological machine. However, invariant relationships are not necessarily ceteris paribus regularities, but could also occur when the (...) influence of the environment is negligible. Then we are able to achieve accurate measurements outside the laboratory. (shrink)

In this chapter, we discuss a specific kind of progress in economics, namely, progress that is pushed by the repeated use of mathematical models in most sub-branches of economics today. We adopt a functional account of progress to argue that progress in economics occurs via the use of what we call ‘common recipes’ and the use of model templates to define and solve problems of relevance for economists. We support our argument by discussing the case of twentieth-century business cycle research. (...) By presenting this case study in detail, we show how model templates are not only re-applied to different phenomena. We also show how scientists come up with them in the first place and how – once they are considered less useful – they are replaced with new ones. Finally, our case also illustrates that it is not only the mathematical structure that is re-used but that such a re-use also requires a shared conceptual vision of core properties of the phenomenon. If that vision is not shared anymore among economists, a model template can become useless and has to be replaced – sometimes through overcoming resistance – with a different one. (shrink)

In the social sciences we hardly can create laboratory conditions, we only can try to find out which kinds of experiments Nature has carried out. Knowledge about Nature's designs can be used to infer conditions for reliable predictions. This problem was explicitly dealt with in Haavelmo's (1944) discussion of autonomous relationships, Friedman's (1953) as-if methodology, and Simon's (1961) discussions of nearly-decomposable systems. All three accounts take Marshallian partitioning as starting point, however not with a sharp ceteris paribus razor but with (...) the blunt knife of negligibility assumptions. As will be shown, in each account reflection on which influences are negligible, for what phenomena and for how long, played a central role. (shrink)

Templates travel because they offer a tractable format that can be used for model-building in a variety of domains. It is often because of this quality that a particular template is chosen. But one cannot assume that there are always templates ready to model a new phenomenon, and moreover, templates have also been designed at some point. A critical aspect of this designing process is the choice of the mathematical objects with which one hopes to capture this phenomenon. This means (...) that one has to assess which of the properties of different kinds of mathematical objects and which combinations of them are most appropriate. The selection of these objects is based on whether their properties enable the model to perform its function. This selection of mathematical objects is similar to the selection of materials in mechanical design. (shrink)

Glenn Harrison [Journal of Economic Methodology, 2013, 20, 103–117] discusses four related forms of methodological intolerance with respect to field experiments: field experiments should rely on some form of randomization, should be disconnected from theory, the concept of causality should only be defined in terms of observables, and the role of laboratory experiments is dismissed. As is often the case, the cause of intolerance is ignorance, as it is here. To acquire knowledge about potential influences, which we need for both (...) the evaluation of internal and external validity of experimental results, we cannot do without theory. A purely empiricist methodology will be unable to give us sufficient understanding of the validity of these results. An account of causality only based on directly observed things, is an account based on factual influences only. This account will be too restricted, because it will not deal with the unobserved potential influences, which we need – again – for the evaluat... (shrink)

Medizinethische Entscheidungsfindungsmodelle müssen nachweisen können, weshalb die mit ihnen getroffenen Entscheidungen richtig oder zumindest „belastbar“ sind. Hierfür sind theoretische Rechtfertigungsansätze aus der Ethik unverzichtbar. Der Klinischen Ethik wird aber mitunter ein Mangel an theoretischer Fundierung vorgeworfen. Um diesem Vorwurf entgegenzutreten, soll unter Bezugnahme auf ein Projekt der Klinischen Ethik („METAP“) die ethische Unterstützung in Form der ethischen Fallbesprechung und der Ethikkonsultation mittels Prinzipienethik und Diskursethik gerechtfertigt werden. Prinzipienethik und Diskursethik können einander über das Medium der ethischen Fallbesprechung oder Ethikkonsultation fruchtbar (...) ergänzen. So können einige theoretische und praktische Schwächen der beiden Ansätze durch den jeweils anderen abgefedert werden. Die Diskursethik übernimmt bspw. die Sicherung der ethischen Gültigkeit von moralischen Entscheidungen bzw. Handlungsnormen und vermindert dadurch ein Rechtfertigungsdefizit, welches bei einem rein prinzipienorientierten Verfahren auftritt. Umgekehrt antwortet die Prinzipienethik u. a. auf Fragen der ethischen Angemessenheit und dient v. a. der adäquaten Einzelfallentscheidung. Durch die Integration des einen Ansatzes in den anderen ist eine umfassendere Rechtfertigungsleistung erzielbar als bei einem alleinigen Einsatz von Prinzipienethik oder Diskursethik. Selbst wenn einige Herausforderungen bestehen bleiben und auch das integrierte Modell moralische Dissense nicht immer verhindern kann, vermag es durch seine „doppelte“ Absicherung (Prinzipien und Diskurs) ein praktisches Vertrauen in die getroffene ethische Entscheidung zu stärken und so der Klinischen Ethik mehr „Robustheit“ zu geben, als sie bisher besitzt. (shrink)

The Representational Theory of Measurement conceives measurement as establishing homomorphisms from empirical relational structures into numerical relation structures, called models. Models function as measuring instruments by transferring observations of an economic system into quantitative facts about that system. These facts are evaluated by their accuracy. Accuracy is achieved by calibration. For calibration standards are needed. Then two strategies can be distinguished. One aims at estimating the invariant (structural) equations of the system. The other is to use known stable facts about (...) the system to adjust the model parameters. For this latter strategy, the requirement of models as homomorphic mappings is not required anymore. (shrink)

Psychologists and neuroscientists extensively rely on computational models for studying and analyzing the human mind. Traditionally, such computational models have been hand-designed by expert researchers. Two prominent examples are cognitive architectures and Bayesian models of cognition. While the former requires the specification of a fixed set of computational structures and a definition of how these structures interact with each other, the latter necessitates the commitment to a particular prior and a likelihood function which – in combination with Bayes’ rule – (...) determine the model's behavior. In recent years, a new framework has established itself as a promising tool for building models of human cognition: the framework of meta-learning. In contrast to the previously mentioned model classes, meta-learned models acquire their inductive biases from experience, i.e., by repeatedly interacting with an environment. However, a coherent research program around meta-learned models of cognition is still missing to this day. The purpose of this article is to synthesize previous work in this field and establish such a research program. We accomplish this by pointing out that meta-learning can be used to construct Bayes-optimal learning algorithms, allowing us to draw strong connections to the rational analysis of cognition. We then discuss several advantages of the meta-learning framework over traditional methods and reexamine prior work in the context of these new insights. (shrink)

Judges in multiple US states, such as New York, Pennsylvania, Wisconsin, California, and Florida, receive a prediction of defendants’ recidivism risk, generated by the COMPAS algorithm. If judges act on these predictions, they implicitly delegate normative decisions to proprietary software, even beyond the previously documented race and age biases. Using the ProPublica dataset, we demonstrate that COMPAS predictions favor jailing over release. COMPAS is biased against defendants. We show that this bias can largely be removed. Our proposed correction increases overall (...) accuracy, and attenuates anti-black and anti-young bias. However, it also slightly increases the risk that defendants are released who commit a new crime before tried. We argue that this normative decision should not be buried in the code. The tradeoff between the interests of innocent defendants and of future victims should not only be made transparent. The algorithm should be changed such that the legislator and the courts do make this choice. (shrink)

Generally, simulations are carried out to answer specific questions. The assessment of the reliability of an answer depends on the kind of question investigated. The answer to a 'why' question is an explanation. The premises of an explanation have to include invariant relationships, and thus the reliability of such answer depends on whether the domain of invariance of the relevant relationships covers the domain of the question. The answer to a 'how much' question is a measurement. A measurement is reliable (...) when it is an output of a calibrated measuring instrument. (shrink)

According to Suppes, measurement theory, like any scientific theory, should consist of two parts, a set-theoretical defined structure and the empirical interpretation of that structure. An empirical interpretation means the specification – ‘coordinating definitions’ – of a ‘hierarchy of models’ between the theory and the experimental results. But in the case of measurement theory, he defined the relationship between numerical structure and the empirical structure specifically in terms of homomorphism. This is rather a highly restrictive relation between models, and therefore (...) he never succeeded in giving his measurement theory empirical content. This paper discusses what an empirical measurement theory will look like if we would use less restrictive ‘coordinating definitions’ to specify the relationships between the various models. (shrink)

Templates travel because they offer a tractable format that can be used for model-building in a variety of domains. It is often because of this quality that a particular template is chosen. But one cannot assume that there are always templates ready to model a new phenomenon, and moreover, templates have also been designed at some point. A critical aspect of this designing process is the choice of the mathematical objects with which one hopes to capture this phenomenon. This means (...) that one has to assess which of the properties of different kinds of mathematical objects and which combinations of them are most appropriate. The selection of these objects is based on whether their properties enable the model to perform its function. This selection of mathematical objects is similar to the selection of materials in mechanical design. (shrink)

The Representational Theory of Measurement conceives measurement as establishing homomorphisms from empirical relational structures into numerical relation structures, called models. There are two different approaches to deal with the justification of a model: an axiomatic and an empirical approach. The axiomatic approach verifies whether a given relational structure satisfies certain axioms to secure homomorphic mapping. The empirical approach conceives models to function as measuring instruments by transferring observations of a phenomenon under investigation into quantitative facts about that phenomenon. These facts (...) are evaluated by their accuracy and precision. Precision is generally achieved by least squares methods and accuracy by calibration. For calibration standards are needed. Then two polar strategies can be distinguished: white-box modeling and black-box modeling. The first strategy of modeling aims at estimating the invariant equations of the phenomenon, thereby fulfilling Hertz’s correctness requirement. The latter strategy of modeling is to use known stable facts about the phenomenon to adjust the model parameters, thereby fulfilling Hertz’s appropriateness requirement. For this latter strategy, the requirement of models as homomorphic mappings has been dropped. Where one will find the axiomatic approach more often used for measurement in the laboratory, the empirical approach is more appropriate for measurement outside the laboratory. The reason for this is that for measurement of phenomena outside the laboratory, one also needs to take account of the environment to achieve accurate results. Environments are generally too relation-rich for an axiomatic approach, which are only applicable for relation-poor systems. The white-box modeling strategy, reflecting the complexity of the environment due to its correctness requirement, will, however, lead to immensely large models. To avoid this problem, modular design is an appropriate strategy to reduce this complexity. Modular design is a grey-box modeling strategy. Grey-box models are assemblies of modules; these are black boxes with standard interface. It should be noted that the structure of the assemblage need not be homomorphic to the relations describing the interaction between phenomenon and environment. These three modeling strategies map out the possible designs for computer simulations as measuring instruments. Whether a simulation is based on a white-box, grey-box or black-box model is only determined by the relationship between the phenomenon and its environment and not by e.g. its materiality or physicality. (shrink)

Generally, rational decision-making is conceived as arriving at a decision by a correct application of the rules of logic and statistics. If not, the conclusions are called biased. After an impressive series of experiments and tests carried out in the last few decades, the view arose that rationality is tough for all, skilled field experts not excluded. A new type of planner's counsellor is called for: the normative statistician, the expert in reasoning with uncertainty par excellence. To unravel this view, (...) the paper explores a specific practice of clinical decision-making, namely Evidence-Based Medicine. This practice is chosen, because it is very explicit about how to rationalize practice. The paper shows that whether a decision-making process is rational cannot be assessed without taking into account the environment in which the decisions have to be taken. To be more specific, the decision to call for new evidence should be rational too. This decision and the way in which this evidence is obtained are crucial to validate the base rates. Rationality should be model-based, which means that not only the isolated decision-making process should take a Bayesian updating process as its norm, but should also model the acquisition of evidence (priors and tests results) as a rational process. (shrink)

Scientific measurements are made objective through the use of reliable instruments. Instruments can have this function because they can - as material objects - be investigated independently of the specific measurements at hand. However, their materiality appears to be crucial for the assessment of their reliability. The usual strategies to investigate an instrument’s reliability depend on and assume possibilities of control, and control is usually specified in terms of materiality of the instrument and environment. The aim of this paper is (...) to investigate the problem of reliability for non-material instruments, the instruments being applied in the social sciences. Any possible lack of reliability of the instrument hinders the measurements of ever becoming objective. (shrink)

The assessment of models in an experiment depends on their material nature and their function in the experiment. Models that are used to make the phenomenon under investigation visible - sensors - are assessed by calibration. However, calibration strategies assume material intervention. The experiment discssed in this paper is an experiment in economics to measure the influence of technology shocks on business cycles. It uses immaterial, mathematical instruments. It appears that calibration did not work for these kinds of models, it (...) did not provide reliable evidence for the facts of the business cycle. (shrink)

The metrology literature neglects a strong empirical measurement tradition in economics, which is different from the traditions as accounted for by the formalist representational theory of measurement. This empirical tradition comes closest to Mari's characterization of measurement in which he describes measurement results as informationally adequate to given goals. In economics, one has to deal with soft systems, which induces problems of invariance and of self-awareness. It will be shown that in the empirical economic measurement tradition both problems have been (...) on the agenda for a long while, and that the proposed solutions to these problems provide clues for the directions in which one could develop a measurement theory that takes account of soft systems. (shrink)

A typical difference between social science and natural science is the degree in which control is possible. Strategies in both sciences to obtain true facts are consequently different. Measurement errors are due to background noise. Laboratories are environments in which background conditions can be controlled. As a result, accurate observations { measurement results close to the true values of the measurands { can only be obtained in laboratories. Therefore, measuring instruments are built such that they function as mini laboratories. However, (...) observations in social science are usually passive, in the sense that control of background conditions is impossible. Models are built to solve this problem of (lack of) control. They function as nonmaterial laboratories by aiming at precision, that is reducing the spread of the measurement errors. The application of models as measuring instruments necessitates a shift of the requirement of accuracy to the requirement of precision, which is a feature of the instrument and not of the environment. (shrink)

Even though it is often presumed that the use of technology like medication administration technology is both safer and more effective, the importance of nurses' know‐how is not to be underestimated. In this article, we accordingly try to argue that nurses' labor, including their different forms of knowledge, must play a crucial role in the development, implementation and use of medication administration technology. Using three different theoretical perspectives (‘heuristic lenses') and integrating this with our own ethnographic research, we will explore (...) how nursing practices change through the use of medication technology. Ultimately, we will argue that ignoring (institutional) complexity and the various types of important knowledge that nurses have, will seriously complicate the implementation of medication administration technology. (shrink)

The practice of economic science is dominated by model building. To evaluate economic policy, models are built and used to produce numbers to inform us about economic phenomena. Although phenomena are detected through the use of observed data, they are in general not directly observable. To 'see' them we need instruments. More particularly, to obtain numerical facts of the phenomena we need measuring instruments. This paper will argue that in economics models function as such instruments of observation, more specific as (...) measuring instruments. In measurement theory, measurement is a mapping of some class of aspects of characteristics of the empirical world into a set of numbers. The paper's view is that economic modelling is a specific kind of mapping to which the standard account on how models are obtained and assessed does not apply. Models are not easily or simply derived from theories and subsequently tested against empirical data. Instruments are constructed by integrating several theoretical and empirical ideas and requirements in such a way that their performance meets a beforehand chosen standard. The empirical requirement is that the model should take account of the phenomenological facts, so that the reliability of the model is not assessed by post-model testing but obtained by calibration. (shrink)