SPED102 Lecture Notes - Lecture 4: Facilitated Communication, Homeopathy, Paleolithic Diet
2 Jun 2018
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Science vs. Pseudoscience
What is science?
• From the Latin ‘scientia’ meaning knowledge
• Refers to the process of obtaining an organised body of knowledge about
natural phenomena through systematic, objective, replicable and rigorous
observation or experimentation
Key Features of the Scientific Approach:
• These are features that distinguish science from pseudoscience
• There is NOT one scientific method
• Evidence (vs. authority)
o Often need to accept qualifications and authority in everyday life, but
o Evidence should always trump authority in scientific research ideally
and eventually
o Science is self-correcting (Eventually) – ‘science advances – one
funeral at a time’ Max Planck
o Hierarchy of Evidence (from strong to weak):
▪ 1. Evaluate the evidence yourself where you have the
knowledge and expertise
▪ 2. Consensus of experts based on evidence (not always correct
but a good bet)
▪ 3. Individual expert with relevant training and background
(someone who may have a doctorate in the relevant area –
difficulty is that you can always find an expert with contrary
views)
▪ 4. Individual without relevant training and background
• Objectivity
o We are all prone to misperception, bias and self-delusion
o Scientific methods are designed to help us compensate for these
inherent flaws
o Focus on measurable objective data
o Minimise risks of human bias
• Falsification
o Proposed by Karl Popper → no amount of evidence can confirm a
theory but a single counterexample can disconfirm a theory
o Propositions must be able to be disconfirmed
o Propositions can best be tested by trying to prove them wrong
• Transparency
o Involves the process of peer review (doesn’t necessarily mean
reasonable though)
o Open methodology → the procedures that you use to achieve are able
for everyone to evaluate and inspect
o Open publication → everyone can access scientific literature
• Replication
o No single study provides definitive evidence –
▪ Methodological errors
▪ Analysis errors
▪ Chance results
▪ Very occasionally there may be fraud
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