Applied conservation consequences of philosophical taxonomy problems (HF) + Trusting expert judgement (VH)
Hannah Fraser, Victoria Hemming ()

May 17, 2017, 9:00am - 10:00am
History and Philosophy of Science, The University of Melbourne

Rm 553 Arts West-North Wing
University of Melbourne
Parkville 3010
Australia

Organisers:

Fiona Fidler
The University of Melbourne

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Hannah Fraser:

I recently submitted my PhD in the Quantitative and Applied Ecology Group (School of BioSciences) but a large part of my work was more in line with History and Philosophy of Science than with ecology. A passion for birds and a supervisor interested in woodlands ignited my interest for ‘woodland birds’. However, when I started researching ‘woodland birds’ it became clear that studies that ostensibly consider the same group refer to different sets of species but results from these studies are compared or combined to understand ‘woodland bird’ ecology. This seemed like a reasonably large scientific flaw and I spent my PhD trying to understand why it occurs and how problematic it is. I will discuss some of my key findings and conclusions in this seminar

Victoria Hemming:

I’m in the final year of my PhD exploring how we can improve expert judgement for conservation decisions when data is absent is or uninformative, which, in conservation is often the rule rather than the exception. Studies into expert judgement show that poor selection and elicitation of experts’ opinion can lead to poor judgements.  However, selecting a diverse group of knowledgeable individuals and eliciting their judgments using structured protocols can often yield accurate and well-calibrated judgements. My research aims to explore whether the group’s performance can be further improved through weighted aggregations and test questions.  However, to develop reliable questions we need a model of the system in question, or at least an understanding of the limits of domain knowledge. In fields such as ecology, domains are not well defined, and models are rarely agreed upon, even if models are agreed data may not be available to test experts. So how do we develop good test questions in these domains? Is it possible? And if not is there still a purpose for test questions? In this presentation I will present some of my results from my PhD.

For more information contact: [email protected]

https://hpsseminar.wordpress.com/

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