This is an extensive summary of the all the lectures given during the course Science and Communication at the VU (in 2019). The summary is supplemented with figures taken from the lecture slides and each lecture contains a heading with the topic and the lecturer. Additionally, some notes on potenti...
L1: introduction – Carina Pittens (3/9)
CARQ:
C: Core citation of the text at issue
A: Argumentation
R: Relation the article as to what you know from other contexts, with other texts discussed in the
course, with non-central issues dealt with in the text
Q: Questions that are formulated in such fashion as to stimulate discussion
L2: what is communication? – Frank Kupper (3/9)
“The situation is hopeless, but not serious” People don’t understand each other, as we tend to
think our ideas/beliefs are true. However, we can change how we relate and can communicate.
Our personal background and morals help us to understand messages (see poster with ‘forests are
the lungs of the planet’). When a science journalist sees a message he starts to debunk and fact-
check. When the message is correct, but the facts are wrong, this can lead to a conflict. A lot of
reporting has a political aim. A lot of scientific research and communication is an intervention in the
world and not just communication of information.
“We define science communication as organised actions aiming to communicate scientific
knowledge, methodology, processes or practices in settings where non-scientists are a recognised
part of the audience.”
Models of communication
Linear (sender-receiver) models:
Lasswell (1948): who says what to whom through
what channel with wat effect? It assumes that
the message stays the same along the line, when
the receiver doesn’t understand it means that there
is a mistake along the way. There is an illusion of
control.
Shannon-Weaver (1949): adds the addition of noise,
everything that distorts the message is noise.
Assumptions of the linear model:
- Transmission: information flows in 1 direction
- The receiver is passive and neutral, yet capable and willing
- Communication is a means to an end
o Subjectivity is noise
Misconceptions:
- Communication is always a 2-way flow
o Receiving is feedback
o Continuous process
- Not passive – receivers actively give meaning
o Filter information on the basis of perceptions, assumptions and judgments
o Interpret and shape message depending on the context of experience, beliefs, traits,
worldview
- Not a means – communication in context
o Watzlawick (1967): interactional view > people that communicate never speak the
same language. You try to get as close as possible
Transmission model
,Characterised by: linearity, asymmetry, 1-way. This model fits with scientific literacy and public
understanding of science. The two models mentioned above are transmission models.
Transaction model
Characterised by: dynamic, symmetry, 2-way
Messages are shared, there is no single sender and receiver, but both parties form the message. This
model fits best to science in society.
Communication is:
- A continuous, transactional process, involving participants operating in specific contexts
- Creating a relationship by simultaneously sending and receiving messages through channels,
often distorted by noise
- (un)intentional, contextual
- Irreversible, unrepeatable
The construction of knowledge
Active construction: people do not draw on models, text-book accounts of scientific
knowledge, but filter and supplement scientific representations with others
Contextual use: people select, construct and use knowledge according to their situation,
interest, involvement
Credibility: people do not accept knowledge passively, credibility depends on perceived
interests
Sense-making: people integrate scientific elements with ethical views and tacit
understandings to form a personal position on controversial matters
L3: What is science? – Pim Klaassen (4/9)
We live in a post-truth society. Science and Technology Studies’s detailed accounts of the
construction of knowledge show that it requires infrastructure, effort, ingenuity and validation
structures. If we abandon/discredit the current knowledge structures, then science communication
won’t be democratic, but will most likely become authoritarian (as Trump tries to do).
Convictions at the basis of this lecture
Today, multiple views on what science is co-exist, but these views cannot all be true
simultaneously.
If you communicate in or about science, your communication will – at least implicitly –
manifest one such particular view on what science is.
Reflection on the nature of science can help you when thinking about communicating about
science
After this lecture you should be able to name 3 different views on science, and explain the distinctive
features of each of these views. After Friday’s CARQ-seminar, you should be able to identify
manifestations of these views in communication in or about science.
Exercise: write down why science is important + the characteristics of science that you think are
conducive to science having the importance you think it has.
- To understand things use it to improve our lives, to advance society
- Strive for understanding
- Question things
- Being precise
Exercise: what does this mean for communication about science?
- To other scientists: open, sharing of information
- To non-scientists: availability, simplification of information, give tools to help understanding
, The colloquial image of science – logical positivism
Science consists of the systematic combination of empirical observation (induction) and logical
deduction, which produces reliable knowledge about the world. Characteristics are:
Autonomy: scientific research and its output are not influenced by external factors (e.g.
politics, money)
Neutrality: scientists are not led by personal views, interests or ideologies in their research
choices or data interpretations.
Factuality: values and norms do not play a role in scientific theories.
These characteristics were formulated by the Vienna circle in the 1920s, they called themselves
logical postivists and are proponents of the ‘scientific world view’.
Logical:
- Logical analysis of language, to distinguish what is meaningful from what is meaningless
- “verification theory of meaning”: only statements of which one can say when they are true
or false, are meaningful.
- Unify all sciences, using one logical (artificial, formal) language
Positivism:
- No place for anything that is not observable (including for instance “causation” and
“mechanisms”)
All that matters (to philosophy?) about science are the statements of fact it produces; the question
logical positivism asks is whether these can be justified. There is no attention for the so-called
‘context of discovery’.
Logical positivism fails, because:
- The truth of (allegedly) universal statements, such as the laws of physics, cannot be verified.
Hence, the laws of physics are meaningless according to LP.
- With its focus on “verification” its rests on induction, but induction can’t be logically
justified. (black swan example)
- Logical positivism assumes we immediately observe “the empirically given”, whereas in fact
all observation is theory-laden (how do we know that the swan is a swan, and not a
disguised duck?)
Karl Popper
Karl Popper was a big criticist of the logical positivism. He wanted to understand how we can justify
scientific truth or value.
- Context of discovery: scientists are free to choose or develop their theories in any way they
want theory
- Context of justification: theory deduce basic statement potential falsifier
o Option 1: accept basic statement, reject theory
o Option 2: do not accept basic statement, do not reject theory (corroboration)
o E.g. all swans are white: potential falsifier is ‘there are no black swans’.
Example: sir Eddington’s boat. He wanted to test whether Einstein’s or Newton’s theory about light
was correct. Einstein described light as particles and Newton as waves. Eddington went on sea and
tested whether he could see the light from a star that was behind the sun and the moon. When
Newton would be right he wouldn’t be able to see the star, if Einstein was right he would. For
Newton’s theory a potential falsifier is ‘the star can be seen’, and for Einstein ‘the star cannot be
seen’. Sir Eddington observed the star and thus accepted the basic statement ‘the star can be seen’,
which falsified Newton’s theory and corroborated Einstein’s theory.
Karl Popper works with the falsification principle: it is demonstrable whether a theory is not true.
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