Theory of Knowledge
Theory of Knowledge
13
Chapters
165
Notes
Chapter 1 - Knowledge & The Knower(Core)
Chapter 1 - Knowledge & The Knower(Core)
Chapter 2 - Knowledge & Technology(Optional)
Chapter 2 - Knowledge & Technology(Optional)
Chapter 3 - Knowledge & Language(Optional)
Chapter 3 - Knowledge & Language(Optional)
Chapter 4 - Knowledge & Politics(Optional)
Chapter 4 - Knowledge & Politics(Optional)
Chapter 5 - Knowledge & Religion(Optional)
Chapter 5 - Knowledge & Religion(Optional)
Chapter 6 - Knowledge & Indigenous Societies(Optional)
Chapter 6 - Knowledge & Indigenous Societies(Optional)
Chapter 7 - History(AoK)
Chapter 7 - History(AoK)
Chapter 8 - The Human Sciences(AoK)
Chapter 8 - The Human Sciences(AoK)
Chapter 9 - The Natural Sciences(AoK)
Chapter 9 - The Natural Sciences(AoK)
Chapter 10 - The Arts(AoK)
Chapter 10 - The Arts(AoK)
Chapter 11 - Mathematics(AoK)
Chapter 11 - Mathematics(AoK)
Chapter 12 - ToK Exhibition
Chapter 12 - ToK Exhibition
Chapter 13 - ToK Essay
Chapter 13 - ToK Essay
IB Resources
Chapter 8 - The Human Sciences(AoK)
Theory of Knowledge
Theory of Knowledge

Chapter 8 - The Human Sciences(AoK)

Mathiness & Physics Envy: Unraveling Economics' Complex Relationship With Science

Word Count Emoji
760 words
Reading Time Emoji
4 mins read
Updated at Emoji
Last edited on 14th Jun 2024

Table of content

Economics - the rigorous human science?

  • Economists often view their field as the most rigorous among human sciences. Some perceive this rigour as a reflection of a natural order in social reality. However, this belief can seem strange given the field’s repeated inability to predict and prevent economic crises.
  • Real-world Example: The 2009 global recession was unexpected, even though economists had claimed to solve the problem of depression prevention six years prior.

The critique of over-reliance on mathematical models

  • Critics argue that the pursuit of rigour has led to over-reliance on abstract mathematical models. These models can often obscure pseudo-scientific methodology and are not effective in making accurate predictions.
  • Real-world Example: Nobel laureate Paul Krugman criticised economists for mistaking the beauty of impressive-looking mathematics for truth.

Understanding mathiness

  • Coined by Nobel Laureate Paul Romer, "mathiness" describes the tendency to disguise academic politics as science through a confusing blend of words and symbols, formal and natural language, and theoretical and empirical content.
  • Romer believes mathiness obstructs access to economic discourse and gives undeserved authority to the work. Both are significant knowledge issues.

Political and business incentives

  • According to Krugman, the appearance of authority, bolstered by "fancy equations," can mask less tenable model assumptions in academia and policy.
  • Real-world Exampleal: Neoliberal economics, criticised for not accounting for the irrationality of economic agents, uses mathiness to defend its validity.

Mathiness and its impact

  • John Rapley argues that in economics, conclusions often come first, and economists tend to gravitate towards theories that fit their moral worldviews. Mathiness can make these theories more convincing and challenging to critique.

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IB Resources
Chapter 8 - The Human Sciences(AoK)
Theory of Knowledge
Theory of Knowledge

Chapter 8 - The Human Sciences(AoK)

Mathiness & Physics Envy: Unraveling Economics' Complex Relationship With Science

Word Count Emoji
760 words
Reading Time Emoji
4 mins read
Updated at Emoji
Last edited on 14th Jun 2024

Table of content

Economics - the rigorous human science?

  • Economists often view their field as the most rigorous among human sciences. Some perceive this rigour as a reflection of a natural order in social reality. However, this belief can seem strange given the field’s repeated inability to predict and prevent economic crises.
  • Real-world Example: The 2009 global recession was unexpected, even though economists had claimed to solve the problem of depression prevention six years prior.

The critique of over-reliance on mathematical models

  • Critics argue that the pursuit of rigour has led to over-reliance on abstract mathematical models. These models can often obscure pseudo-scientific methodology and are not effective in making accurate predictions.
  • Real-world Example: Nobel laureate Paul Krugman criticised economists for mistaking the beauty of impressive-looking mathematics for truth.

Understanding mathiness

  • Coined by Nobel Laureate Paul Romer, "mathiness" describes the tendency to disguise academic politics as science through a confusing blend of words and symbols, formal and natural language, and theoretical and empirical content.
  • Romer believes mathiness obstructs access to economic discourse and gives undeserved authority to the work. Both are significant knowledge issues.

Political and business incentives

  • According to Krugman, the appearance of authority, bolstered by "fancy equations," can mask less tenable model assumptions in academia and policy.
  • Real-world Exampleal: Neoliberal economics, criticised for not accounting for the irrationality of economic agents, uses mathiness to defend its validity.

Mathiness and its impact

  • John Rapley argues that in economics, conclusions often come first, and economists tend to gravitate towards theories that fit their moral worldviews. Mathiness can make these theories more convincing and challenging to critique.

Unlock the Full Content! File Is Locked Emoji

Dive deeper and gain exclusive access to premium files of Theory of Knowledge. Subscribe now and get closer to that 45 🌟