A guide for interdisciplinary researchers: Adding axiology alongside ontology and epistemology

Community member post by Peter Deane

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Peter Deane (biography)

Can philosophical insights be useful for interdisciplinary researchers in extending their thinking about the role of values and knowledge in research? More broadly, can a model or heuristic simplify some of the complexity in understanding how research works?

It’s common for interdisciplinary researchers to consider ontology and epistemology, two major arms of philosophical inquiry into human understanding, but axiology – a third major arm – is oft overlooked.

I start by describing axiology, then detail work by Michael Patterson and Daniel Williams (1998) who place axiology alongside ontology and epistemology. The outcome herein is to cautiously eject and then present a part of their work as a heuristic that may help interdisciplinary researchers to extend understanding on philosophical commitments that underlie research. Continue reading

Interdisciplinarity and evil – Understanding incommensurability

Community member post by J. Britt Holbrook

J. Britt Holbrook (biography)

Incommensurability is a recognized problem in interdisciplinary research. What is it? How can we understand it? And what can we do about it?

What is it?

Incommensurability is best illustrated by a real example. I once co-taught a class with a colleague from another discipline. Her discipline depends on empirical analysis of data sets, literally on counting things. I, on the other hand, am a philosopher. We don’t count. One day she said to our students, “If you don’t have an empirical element in what you’re doing, it’s not research.” I watched the students start nodding, paused for half a beat, and volunteered, “So, I’ve never done any research in my entire career.” “That’s right!” she replied, immediately, yet hesitating somewhere between a discovery and a joke. Continue reading

Storytelling ethnography as a way of doing transdisciplinary research

Community member post by Jane Palmer

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Jane Palmer (biography)

Storytelling ethnography is a valuable tool if your research traverses several disciplines and aims for insights that transcend all of them. Stories not only integrate knowledge from diverse disciplines, but can also “change the way people act, the way they use available knowledge” (Griffiths 2007).

The special qualities of transdisciplinarity are:

  • its potential for integrative inquiry and emergent solutions,
  • its engagement with community and other non-academic knowledges, and
  • the breadth of its outcomes for researchers, participants and the wider community.

These are also qualities of what I call storytelling ethnography. Continue reading

What makes a translational ecologist? Part 3: Dispositional attributes

Community member post by the Translational Ecology Group 

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Translational Ecology Group (participants)

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Four related blog posts on translational ecology:

Introduction to translational ecology

What makes a translational ecologist – Part 1: Knowledge / Part 2: Skills / Part 3: Dispositional attributes (this blog post)

This is the third and final blog post considering competencies to make ecologists more effective in informing and supporting policy and practice change (see the right sidebar for links to all four related blog posts on translational ecology). In other words these are the competencies underpinning a new discipline of translational ecology.

The two previous blog posts examined the knowledge and skills required in three major areas:

  1. Socio-ecological systems
  2. Communication across boundaries, with beneficiaries, stakeholders and other scientists
  3. Engagement with beneficiaries, stakeholders and other scientists.

This blog post uses the same three areas to examine the dispositional attributes required.

What are dispositional attributes?

Each person’s internal cognitive and moral qualities are collectively known as dispositions. Continue reading

Modeling as social practice

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Jeremy Trombley (website and biography)

Community member post by Jeremy Trombley

Modeling – the creation of simplified or abstract representations of the world – is something that people do in many different ways and for many different reasons, and is a social practice. This is true even in the case of scientific and computational models that don’t meet the specific criteria of “participatory” or “collaborative.” Scientists and modelers interact with one another, share information, critique and help to refine one another’s work, and much more as they build models.

Furthermore, all of these activities take place within broader social structures – universities, government agencies, non-government organizations, or simply community groups – and involve resources – funding sources, technologies – that also have social factors that are both embedded within and emerging from them. Understanding the relationship between all of these social dimensions as well as those of the problems that modeling is being used to address is an important task, particularly in participatory modeling projects. Continue reading