Demarcating misconduct from misinterpretations and mistakes

Within recent years, scientific misconduct has become an increasingly important topic, not only in the scientific community, but in the general public as well. Spectacular cases have been extensively covered in the news media, such as the cases of the Korean stem cell researcher Hwang, the German nanoscientist Schön, or the Norwegian cancer researcher Sudbø. In Science's latest annual "breakthrough of the year" report from December 2006, the descriptions of the year's hottest breakthroughs were accompanied by a similar description of "the breakdown of the year: scientific fraud". Official guidelines for dealing with scientific misconduct were introduced in the 1990s. At this time, research agencies, universities and other research institutions around the world developed guidelines for good scientific practice and formed committees to handle cases of scientific misconduct. In this process it was widely debated how to define scientific misconduct. Most definitions centered on falsification, fabrication, and plagiarism (the so-called FFP definition), but suggestions were also made for definitions that were broader and more open-ended, such as the 1995 suggestion from the US Commission of Research Integrity to replace FFP with misappropriation, interference and misrepresentation (the so-called MIM definition). The MIM definition was not adopted in the US, but MIM-like definitions have been adopted in several other countries. In this paper, I shall describe these MIM-related definitions of scientific misconduct and analyze the arguments that have been advanced in their favor. I shall discuss some of the difficulties inherent in the MIM-related definitions, such as the distinction between misrepresentation and mistake, and the demarcation of misrepresentation in areas characterized by uncertainty or by diverging research paradigms. I shall illustrate the problems inherent in the MIM-definition through a particular case: the ruling of the Danish Committee on Scientific Dishonesty (DCSD) about Bjørn Lomborg's best-selling book The Skeptical Environmentalist in which he argued that contrary to what was claimed in the “litany” of the environmentalists, the state of the environment is getting better rather than worse. Lomborg was reported to the DCSD by several environmental scientists, and this controversial case from 2003 ended with a verdict that characterized Lomborg’s conclusions as misrepresentations, but acquitted Lomborg of misconduct due to his ignorance. I shall analyze this verdict and the problems it reveals with respect to the MIM-related definitions of misconduct

History and Philosophy of Modern Epidemiology

Epidemiological studies of chronic diseases began around the mid-20th century. Contrary to the infectious disease epidemiology which had prevailed at the beginning of the 20th century and which had focused on single agents causing individual diseases, the chronic disease epidemiology which emerged at the end of Word War II was a much more complex enterprise that investigated a multiplicity of risk factors for each disease. Involved in the development of chronic disease epidemi-ology were therefore fundamental discussions on the notion of causality, especially the question when causal inferences could be justified. In this paper, I shall analyze the implicit normativity of these de-bates. First, I shall give a brief overview of the historical background on which chronic disease epi-demiology emerged and describe how the pioneer studies on smoking and lung cancer became icon of the major challenge that the emerging chronic disease epidemiology was facing: the impossibility of proving that statistical associations reflected causal relations. Next, I shall describe how the develop-ment from the monocausal enterprise of infectious disease epidemiology to the multicausal enterprise of chronic disease epidemiology gave rise to intense discussions of the possible criteria by which to establish causal relationships between a given factor and a particular disease. I shall show how the necessary and sufficient conditions expressed in the so-called Henle-Koch criteria that had proved useful for the 19th century investigations of infectious diseases remained an ideal, although clearly an unobtainable one. Thus, I shall show how 20th century chronic disease epidemiologists on the one hand were searching for a new set of general principles which would provide a logical framework for their investigations, but on the other hand admitted that they would have to accept something more "pragmatic". I shall analyze the various positions in this debate, arguing that the implacability of the debate was due to unrecognized normative issues. I shall argue that many insisted on a distinction between science and application that was untenable, but that due to this distinction the values in-volved in deciding whether or not to act on the basis of a hypothesis were rarely explicitly discussed and the decision therefore continued to appear as a matter of taste rather than the result of a cogent normative analysis

Systems Science and the Art of Interdisciplinary Integration

Systems sciences address issues that cross-cut any single discipline and benefit from the synergy of combining several approaches. But interdisciplinary integration can be challenging to achieve in practice. Scientists with different disciplinary backgrounds often have different views on what count as good data, good evidence, a good model, or a good explanation. Accordingly, several scholars have reported on challenges encountered in interdisciplinary settings. This chapter outlines how some of the challenges play out in systems biology where disciplinary ideals and domain specific practices sometime collide. We focus on tensions arising due to differences in epistemic standards between modellers with a background in physics or systems engineering, on one hand, and experimenters with a background in molecular biology on the other. We propose that part of the problem of interdisciplinary integration can be understood as the result of unfounded “disciplinary imperialism” on both sides, in which standards from one discipline are uncritically applied to new domains without recognition of other valid or complementary perspectives. We suggest that addressing and explicating the disciplinary background for the different views can help facilitate interdisciplinary collaboration in science as well as serve to improve science education

Bibliografia/Bibliography

Bibliografia/Bibliograph

Systems Science and the Art of Interdisciplinary Integration

Systems sciences address issues that cross-cut any single discipline and benefit from the synergy of combining several approaches. But interdisciplinary integration can be challenging to achieve in practice. Scientists with different disciplinary backgrounds often have different views on what count as good data, good evidence, a good model, or a good explanation. Accordingly, several scholars have reported on challenges encountered in interdisciplinary settings. This chapter outlines how some of the challenges play out in systems biology where disciplinary ideals and domain-specific practices sometime collide. We focus on tensions arising due to differences in epistemic standards between modellers with a background in physics or systems engineering, on one hand, and experimenters with a background in molecular biology on the other. We propose that part of the problem of interdisciplinary integration can be understood as the result of unfounded “disciplinary imperialism” on both sides, in which standards from one discipline are uncritically applied to new domains without recognition of other valid or complementary perspectives. Addressing and explicating the disciplinary background for the different views can help facilitate interdisciplinary collaboration in science and improve science education

A210 Valle kirke. Konservering av lerretsmaleriet "Christian IVs syn"

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