Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Scientific Realism vs. Anti-Realism: Toward a Common Ground

Hanti Lin

Abstract

The debate between scientific realism and anti-realism remains at a stalemate, making reconciliation seem hopeless. Yet, important work remains: exploring a common ground, even if only to uncover deeper points of disagreement and, ideally, to benefit both sides of the debate. I propose such a common ground. Specifically, many anti-realists, such as instrumentalists, have yet to seriously engage with Sober's call to justify their preferred version of Ockham's razor through a positive account. Meanwhile, realists face a similar challenge: providing a non-circular explanation of how their version of Ockham's razor connects to truth. The common ground I propose addresses these challenges for both sides; the key is to leverage the idea that everyone values some truths and to draw on insights from scientific fields that study scientific inference -- namely, statistics and machine learning. This common ground also isolates a distinctively epistemic root of the irreconcilability in the realism debate.

Scientific Realism vs. Anti-Realism: Toward a Common Ground

Abstract

The debate between scientific realism and anti-realism remains at a stalemate, making reconciliation seem hopeless. Yet, important work remains: exploring a common ground, even if only to uncover deeper points of disagreement and, ideally, to benefit both sides of the debate. I propose such a common ground. Specifically, many anti-realists, such as instrumentalists, have yet to seriously engage with Sober's call to justify their preferred version of Ockham's razor through a positive account. Meanwhile, realists face a similar challenge: providing a non-circular explanation of how their version of Ockham's razor connects to truth. The common ground I propose addresses these challenges for both sides; the key is to leverage the idea that everyone values some truths and to draw on insights from scientific fields that study scientific inference -- namely, statistics and machine learning. This common ground also isolates a distinctively epistemic root of the irreconcilability in the realism debate.

Paper Structure

This paper contains 23 sections, 11 equations, 10 figures.

Table of Contents

  1. An Invitation
  2. The Disagreement
  3. A Common Ground Easy to Come By?
  4. Proposal: Seeking a Common Ground
  5. Benefiting Both Parties
  6. A Little Story of Pursuit of Truth
  7. Preliminaries: The Notion of Empirical Problems
  8. Formal Learning Theory
  9. The Achievabilist Framework for Convergentism
  10. Frequentist Hypothesis Testing
  11. Toward an Epistemology for Anti-Realism
  12. Preliminaries: Parametric Models and Predictive Power
  13. Instrumentalist Pursuit of Truth
  14. Prospects for Anti-Realist Epistemology
  15. Toward an Epistemology for Realism
  16. ...and 8 more sections

Figures (10)

  • Figure 1: A simple problem of theory choice: '$\theta = 0$' vs. '$\theta \neq 0$'
  • Figure 2: A statistical problem of theory choice: '$\theta = 0$' vs. '$\theta \neq 0$'
  • Figure 3: A pasta model of Perrin's case
  • Figure 4: An example of evidence in Perrin's case
  • Figure 5: Underdetermination in Perrin's case
  • ...and 5 more figures