Welcome to my inside talk at the PCST 20 plus 1.
My name is Christian Hum.
I'm a researcher at the Karlsruhe Institute of Technology in the
Department of Science Communication.
Today, I will talk about exclusion in science communication.
This problem has gained attention in the last years and more and more
research is focused on it.
Today, it is clear that science communication, at least in the West,
often reaches only a very specific part of the population that is
typically white, male, academic and better learning.
However, there is still a lack of systematic approaches regarding the
underlying factors that cause exclusion.
Thus, my colleagues, Philipp Schroegl and Anette Lesmerman and me,
developed a typology of exclusion factors in science communication.
Through a systematic literature review in science communication
research and other fields like disability studies, added education or
political science, we were able to identify and describe 31 factors.
We split them in three dimensions, individual, social and structural
factors.
As you can see, the typology includes factors like language barriers,
gender, habitus or place.
Unfortunately, I don't have the time to explain these factors here in
detail.
In order to empirically test the typology and its factors, we used the
combined quantitative and qualitative approach.
Quantitatively, we analyzed the survey Wissenschaftsbarometer, science
barometer in English, for the years 2017, 18 and 19.
The survey is representative for the German population.
In our analysis, we looked for connections between exclusion factors
found in the survey, like age, and different indicators like visits to
public lectures or interest in science.
Statistical regression analysis show that proximity to science, that
is knowing a scientist or working in science, is a strong explanatory
factor.
Education, age, gender and income are also significant for some
indicators.
In contrast, migration background and religiousness are only seldom
significant, which might be a bit surprising.
Taken together, these exclusion factors are especially influential for
conative indicators, that are indicators about doing something, like
visiting a museum or going to a public lecture.
To gain qualitative insight into the typology, we conducted three case
studies with underrepresented audiences, that were residents of a
marginalized city quarter, vocational students in a craft, and young
Muslims with a migration background.
We did interviews and focus groups with them to identify the relevance
of exclusion factors.
All three groups were interested in science, but hardly consumed
science communication.
As reasons for that, they mentioned on the one hand material factors,
like lack of local offerings and infrastructure, missing financial and
time resources, as well as language barriers.
On the other hand, emotional factors were relevant too.
They were fear, frustration and insecurity, often originating from
experiences in school, emotional and habitual distance towards
science, as well as self and external perception of not being a
science person.
You can find our more detailed analysis in the article on the slide.
To sum up my insight talk, the typology of exclusion factors in
science communication remains a work in progress and is absolutely
open for discussion.
First empirical tests with quantitative and qualitative methods are
promising.
However, not all factors have been tested for their relevance and
usability in research.
We hope that the typology can both serve researchers in analyzing
exclusion in science communication, as well as practitioners in self
-reflecting their own work and thus lead to more inclusive science
communication.
In order to make the typology accessible especially to practitioners,
we created a hidden object picture, of which you can see a detail on
the slide.
On the picture, exclusion factors are visually illustrated and
accompanied by short explanations.
You can download it for free via the link or order a free copy by
emailing me.
And that's it.
Thank you for your attention.