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Communication Dans Un Congrès Année : 2013

An ontology of scientific uncertainty : methodological lessons from analyzing expressions of uncertainty in food risk assessment

Résumé

The relationship between scientific knowledge and uncertainty in science has been a central question in risk analysis. There have been several conceptualizations of uncertainty but most have been normative efforts to construct an ontology on the basis of theoretical considerations and there have been few empirical attempts to build such an ontology through textual analysis. Studies investigating how such ontologies work are equally scarce. We developed an ontology to investigate uncertainty in risk assessment in food safety comparing the EU and the US, and the two main domains of food safety: biohazards and contaminants. The ontology gauges expressions of uncertainty in two ways: one looks for stylistic clues of judgment, the other registers the content of the uncertainty expressed in the documents. We have built a large data base where English language risk assessment documents by the European Food Safety Agency and the three US agencies primarily responsible for food safety in the US are coded according to our ontology. We are also in the process of creating software that uses machine-learning algorithm to code risk assessment documents in our database. In our paper, we lay out our approach to scientific uncertainty, then describe the ontologies we developed to assess expressions of scientific uncertainty in risk assessment documents in food safety. We then discuss the results from supervised Machine Learning and the implications for both the method of machine coding and the insights we gained for human coding. Finally, we discuss some findings using the ontology testing three sets of hypotheses. The first one looks at differences in national styles in applied scientific research, the second differences in epistemic cultures between scientific subfields in food safety and the third about the effect of research and new knowledge on uncertainty.
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Dates et versions

hal-01565544 , version 1 (19-07-2017)

Identifiants

  • HAL Id : hal-01565544 , version 1
  • PRODINRA : 399112

Citer

Sandrine Blanchemanche, Akos Rona-Tas, Antoine Cornuéjols, Antonin Duroy, Christine Martin. An ontology of scientific uncertainty : methodological lessons from analyzing expressions of uncertainty in food risk assessment. 4S 2013 San Diego : Society for Social Studies of Science, Oct 2013, San Diego, United States. ⟨hal-01565544⟩
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