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*Scientific Misconduct and Scientific Expertise***

1^st Barcelona HPS workshop

November 11, 2016

Departament de Filosofia & Centre d’Histňria de la Cičncia (CEHIC), 
Universitat Autňnoma de Barcelona (UAB)

Location: CEHIC,Mňdul de Recerca C, Seminari L3-05, c/ de Can Magrans 
s/n, Campus de la UAB, 08193 Bellaterra (Barcelona)

/Organized by Thomas Sturm & Agustí Nieto-Galan/

Current science is full of uncertainties and risks that weaken the 
authority of experts. Moreover, sometimes scientists themselves act in 
ways that weaken their standing: they manipulate data, exaggerate 
research results, do not give credit where it is due, violate the norms 
for the acquisition of academic titles, or are unduly influenced by 
commercial and political interests. Such actions, of which there are 
numerous examples in past and present times, are widely conceived of as 
violating standards of good scientific practice. At the same time, while 
codes of scientific conduct have been developed in different fields, 
institutions, and countries, there is no universally agreed canon of 
them, nor is it clear that there should be one. The workshop aims to 
bring together historians and philosophers of science in order to 
discuss questions such as the following: What exactly is scientific 
misconduct? Under which circumstances are researchers more or less 
liable to misconduct? How far do cases of misconduct undermine 
scientific authority? How have standards or mechanisms to avoid 
misconduct, and to regain scientific authority, been developed? How 
should they be developed?

/All welcome - but since space is limited, please register in advance. 
Write to: Thomas.SturmATuab.cat/

09:30 Welcome (Thomas Sturm & Agustí Nieto-Galan)

9:45 José Ramón Bertomeu-Sánchez (IHMC, 
<http://links.uv.es/bertomeu>Universitat de Valčncia): /Managing 
Uncertainty in the Academy and the Courtroom: Normal Arsenic and 
Nineteenth-Century Toxicology/

10:30 Carl Hoefer (ICREA & Philosophy, University of 
Barcelona):/Comments on Bertomeu-Sánchez/

10:45 Discussion (Chair: Agustí Nieto-Galan)

11:30 Coffee break

12:00 David Teira (UNED, Madrid): /Does Replication help with 
Experimental Biases in Clinical Trials?/

12:45 Javier Moscoso (CSIC, Madrid): /Comment on Teira/

13:00 Discussion (Chair: Thomas Sturm)


13:45-15:00 Lunch

15:00 Torsten Wilholt (Philosophy, Leibniz University Hannover): /Bias, 
Fraud and Interests in Science/

15:45 Oliver Hochadel (IMF, CSIC, Barcelona): /Comments on Wilholt/

16:00 Discussion(Chair:Silvia de Bianchi)

16:45-17:15: Agustí Nieto-Galan &Thomas Sturm:Concluding reflections

ABSTRACTS

José Ramón Bertomeu-Sánchez: *Managing Uncertainty in the Academy and 
the Courtroom: Normal Arsenic and Nineteenth-Century Toxicology*

This paper explores how the enhanced sensitivity of chemical tests 
sometimes produced unforeseen and puzzling problems in 
nineteenth-century toxicology. It focuses on the earliest uses of the 
Marsh test for arsenic and the controversy surrounding “normal arsenic”, 
i.e., the existence of traces of arsenic in healthy human bodies. The 
paper follows the circulation of the Marsh test in French toxicology and 
its appearance in the academy, the laboratory and the courtroom. The new 
chemical tests could detect very small quantities of poison, but their 
high sensitivity also offered new opportunities for imaginative defense 
attorneys to undermine the credibility of expert witnesses. In this 
context, toxicologists had to dispel the uncertainty associated with the 
new method, and to find arguments to refute the many possible criticisms 
(of which “normal arsenic” was one). Meanwhile, new descriptions of 
animal experiments, autopsies and cases of poisoning produced a steady 
flow of empirical data, sometimes supporting but, in many cases, 
questioning previous conclusions about the reliability of chemical 
tests. This particularly challenging scenario provides many clues about 
the complex interaction between science and law in the nineteenth 
century, particularly on how expert authority, credibility and 
trustworthiness were constructed, and frequently challenged, in the 
courtroom.


David Teira: *Does Replication help with Experimental Biases in Clinical 
Trials?*

This is an analysis of the role of replicability in correcting biases in 
the design and conduct of clinical trials. We take as biases those 
confounding factors that a community of experimenters acknowledges and 
for which there are agreed debiasing methods. When these methods are 
implemented in a trial, we will speak of /unintended biases/, if they 
occur. Replication helps in detecting and correcting them. /Intended 
biases/ occur when the relevant debiasing method is not implemented. 
Their effect may be stable and replication, on its own, will not detect 
them. /Interested/ outcomes are treatment variables that not every 
stakeholder considers clinically relevant. Again, they may be perfectly 
replicable. Intended biases, unintended biases and interested outcomes 
are often conflated in the so-called replicability crisis: our analysis 
shows that fostering replicability, on its own, will not sort out the 
crisis.

Torsten Wilholt: *Bias, Fraud and Interests in Science*

Cases of fraud and misconduct are the most extreme manifestations of the 
adverse effects that conflicts of interests can have on science. 
Fabrication of data and falsification of results may sometimes be 
difficult to detect, but they are easy to describe as epistemological 
failures. But arguably, detrimental effects of researchers' interests 
can also take more subtle forms. There are numerous ways by which 
researchers can influence the balance between the sensitivity and the 
specificity of their investigation. Is it possible to mark out some such 
trade-offs as cases of detrimental bias? I shall argue that it is, and 
that the key to understanding bias in science lies in relating it to the 
phenomenon of epistemic trust. Like fraud, bias exerts its negative 
epistemic effects by undermining the trust amongst scientists as well as 
the trust invested in science by the public. I will point out how this 
analysis can help us to draw the fine lines that separate 
unexceptionable from biased research and the latter from actual fraud.