11.1 Pathological Science: Difference between revisions
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More details | [https://sensesensibilityscience.berkeley.edu/topic/19 More details] | ||
After this lesson, students should | After this lesson, students should | ||
Revision as of 08:01, 28 November 2021
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| Write the "context" for how this lesson connects with others. |
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Learning Goals
[Link to PlayPosit]
[Link to instructional video]
After this lesson, students should
- Be able to identify the following:
- Good science that gets the wrong answer.
- Fraudulent science.
- Pathological science.
- Poorly-done science.
- Pseudo-science.
- Feel comfortable using Langmuir's Pathological Science Indicators to assess scientific articles.
- Be able to identify what is wrong in cases of fraudulent, pathological, poorly-done, and pseudo-science.
Definitions
- Spectrum of poor research:
- Good science that gets the wrong answer
- Even with a confidence level of 95%, 5% of the time the results will be wrong. This is normal.
- Poorly-done Science
- Science done honestly, but not done well.
- Pathological Science
- Indicated by Langmuir's criteria.
- Pseudo-science
- Pseudo-science is characterized by using scientific vocabulary without aligning with the corresponding concepts or engaging in real scientific practices (i.e., science being "skin deep," not scientific below the surface).
- Fraudulent Science
- Research that involves intentional deception, such as deliberately fabricating data or deliberately deceiving the reader about the strength of evidence.
- Good science that gets the wrong answer
- Langmuir's Pathological Science Indicators
- The effect is produced by a barely detectable cause, and the magnitude of the effect is substantially independent of the intensity of the cause.
- The effect is barely detectable, or has very low statistical significance. Claims of great accuracy.
- Claims of great accuracy.
- Involving fantastic theories contrary to experience.
- Criticisms are met with ad hoc excuses.
- Ratio of supporters to critics rises to near 50%, then drops back to near zero.
- Conclusion-motivated design & analysis.
Examples
- [item 1]
Common Misconceptions
- Mistaken quote
- Explanation.
Context
This lesson teaches students to be cautious of bad science of all kinds and aware of the signs thereof. We ask students to study a few established examples of pathological science in history dressed as science merely in form. The emphasis is on well-intentioned researchers "falling in love" with their own ideas, finding excuses to justify them even when reality has turned out to be contrary to them.
| Although blatant pseudoscience such as flat earth, astrology, creationism, and alternative medicine are also included, what deserves particular caution is seemingly genuine science done by seemingly genuine people that is nevertheless incorrect, possibly due to the researchers' own hubris. |
Before
- 1.2 Shared Reality
- Everyone in principle has access to the same shared reality. If a certain (amazing) result by one research group cannot seem to be replicated by many other groups, it is a good sign that it does not accurately describe the shared reality.
- 4.1 Finding Patterns in Random Noise
- It is expected that patterns arise from random noise. Good science can also turn out to be wrong just by chance, but stubbornly sticking with the original result would turn it into bad science.
- 5.1 Scientific Optimism
- In the spirit of personal persistence and iterative progress, setbacks such as a wrong or disappointing result should be accepted as an inevitable part of this progress.
- 6.2 Calibration of Credence Levels
- Overstating the confidence level of a scientific result is a sign of bad science.
After
- 9.2 When Is Science Suspect
- Bad science is particularly problematic when it concerns the study of human subgroups, as it may be motivated by or may perpetuate preexisting unequal power structures in society.
- 10.2 Blind Analysis
- Though not yet widely employed in all fields of science, various blind analysis techniques can help reduce the possibility that a scientific result may be contaminated by subtle analysis choices made by the researchers that are (often subconsciously) motivated by the desire for a certain anticipated result.
Recommended Outline
Before Class
- Each student will have read one of the three articles that we discuss in this section.
- Prepare a seating chart.
- Review PlayPosit and discussion questions and ask faculty, Gabriel, or Emlen any questions you have.
- (Optional) Prepare a presentation.
During Class
- (5 min) Come up with some fun way to assign the roles of spokesperson and notetaker (e.g. earliest birthday in the year, lives furthest from campus). Remind them of the responsibilities of these roles.
- ([#] min) [Description of some module from #Lesson Content]
- (5 min) Collect questions for plenary.
After Class
- [Any essential logistical things that need to be done as followup for this class]
- Collect answers from notetakers for the forum / plenary.
Lesson Content
Clicker Question
Question
| Correct answer. |
- First option
- Second option
- Third option
- Fourth option
Activity 1: Name
[Brief description of and motivation for the activity]
| Common misconceptions and any useful tricks, tips, guidelines, or other background |
Instructions
Discussion Questions
- Question 1
- Subquestion a
Possible misconception that may need to be corrected and clarified. Intended answer to the above question.
- Subquestion b
- Subquestion a
Collect Questions for Plenary
(5 min) Collect remaining questions from the students for faculty in plenary (can be questions for clarification, extension, discussion, etc.), and add [ here].