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The Role of Justification in the Ordinary Concept of Scientific Progress

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Abstract

Alexander Bird and Darrell Rowbottom have argued for two competing accounts of the concept of scientific progress. For Bird, progress consists in the accumulation of scientific knowledge. For Rowbottom, progress consists in the accumulation of true scientific beliefs. Both appeal to intuitions elicited by thought experiments in support of their views, and it seems fair to say that the debate has reached an impasse. In an attempt to avoid this stalemate, we conduct a systematic study of the factors that underlie judgments about scientific progress. Our results suggest that (internal) justification plays an important role in intuitive judgments about progress, questioning the intuitive support for the claim that the concept of scientific progress is best explained in terms of the accumulation of only true scientific belief.

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Notes

  1. Though this is the view that Bird defends, it is important to note that knowledge is not taken here to be justified true belief. Instead, Bird thinks that his arguments about scientific progress support Williamson’s (1997, 2000) view that knowledge is a foundational concept in epistemology and that it does not have an analysis.

  2. Proponents of the semantic approach (S) include Popper (1979) and Niiniluoto (1987).

  3. Proponents of functional-internalist approach (FI) include Kuhn (1962/1996) and Laudan (1977).

  4. There are many different ways in which the belief formation method may be inadequate. For instance, Bird also considers the real-world example of René Blondlot’s (apparently entirely spurious and irrational) belief in entities called N-rays. Had these entities actually existed, then on (S), but not (E), this would be a case of scientific progress because his belief would have been true.

  5. Importantly, neither Kuhn nor Laudan think that science requires knowledge; Laudan due to the pessimistic induction, and Kuhn due to his critiques of truth and verisimilitude.

  6. For Kuhn (1962/1996), exemplars, rather than the application of rules, play a dominant role in scientific cognition. A puzzle-solution may be accepted or not, according to Kuhn, depending on its similarity to paradigmatic puzzle-solutions. For Kuhn, determining the similarities between puzzle-solutions is not a matter of following or applying rules. See Bird (2000).

  7. According to Laudan (1981, 148), “the problem-solving approach allows a problem solution to be credited to a theory, independent of how well established the theory is, just so long as the theory stands in a certain formal relation to (a statement of) the problem.” In that respect, Laudan’s account is like Hempel’s Deductive-Nomological model of explanation (at least superficially) to the extent that, according to the DN model, “the explanandum (i.e., a statement describing the phenomenon to be explained) must be a logical consequence of the explanans (i.e., the class of those statements that are adduced to account for the phenomenon)” (Hempel 1965, 247–248).

  8. Participants, 160 female, aged 19–68, M = 36 years, SD = 11.97 years. Participants were recruited using Amazon Mechanical Turk as well as through the Yale Experiment Month initiative (http://www.yale.edu/cogsci/XM/Info.html). Participants were tested online using Qualtrics survey software, and compensated $0.25 for approximately 2–3 min of their time. Participants were located throughout the United States. They filled out a brief demographic survey after testing. Participants reported highest level of education (7.6 % high school graduate; 22.2 % some college, no degree; 27 % bachelor’s degree; 30.2 % graduate degree). Participants also reported levels of post-secondary training specifically in the natural sciences (28.2 %), social sciences (35.9 %), and technology or engineering (16.1 %). We did not detect any differences in intuitions of scientific progress based on these demographic variables.

  9. For Theoretical Progress cases: No External/No Internal (M = 4.69, SD = 1.67); No External/Internal (M = 5.77, SD = 1.38); External/No Internal (M = 4.83, SD = 1.53); External/Internal (M = 5.51, SD = 1.41). For Technological Progress cases: No External/No Internal (M = 4.58, SD = 1.56); No External/Internal (M = 6.00, SD = 1.21); External/No Internal (M = 4.42, SD = 1.60); External/Internal (M = 6.05, SD = 1.09).

  10. A multiple-way between-subjects analysis of variance was conducted to evaluate the effect of internal justification, external justification, and scientific goal on participants’ judgments about scientific progress. We found a main effect for internal justification F(1,389) = 67.34, p < 0.01, but were not able to detect a main effect for external justification F(1,389) = 0.15, p = 0.699. We also detected an interaction effect between internal justification and scientific goal, F(1,389) = 4.86, p < 0.05.

  11. In that respect, we should add the following caveat. If one interprets our results as support for (E), then one must be willing to pay a certain price. The price, it seems, is that one might have to forego externalism about justification, at least as far as scientific knowledge is concerned. We acknowledge that some might reasonably think that this is a heavy price to pay.

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Acknowledgments

This study was included in Experiment Month, which was sponsored by the American Philosophical Association (APA) and coordinated by Yale University’s Cognitive Science. The results were presented at the APA Eastern Division 108th Annual Meeting in Washington DC, December 27–30, 2011. We would like to thank Joshua Knobe, Mark Phelan, and Darrell Rowbottom for helpful discussion. We are also grateful to two anonymous reviewers for the Journal for General Philosophy of Science for helpful comments on an earlier draft.

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Correspondence to Moti Mizrahi.

Appendix

Appendix

 

Theoretical goal

Technological goal

External justification

No external

External justification

No external

Internal justification

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  2. 2.

    A group of scientists at the Institute for Advanced Study has been studying the speed of light. Working with the Theory of Relativity, the scientists were trying to find particles that travel faster than light. One day, during an anomalous power surge, the computer program the scientists were using managed to mathematically demonstrate the existence of these faster-than-light particles with an equation. As it turns out, this equation works perfectly, and these particles, called “tachyons,” really do exist. The scientists reviewed the logs immediately, and they figured out how the program performed the demonstration.

  3. 3.

    A group of scientists at the Institute for Advanced Study has been studying the speed of light. Working with the Theory of Relativity, the scientists were trying to find particles that travel faster than light. One day, during a day of routine calculations, the computer program the scientists were using managed to mathematically demonstrate the existence of these faster-than-light particles with an equation. As it turns out, this equation works perfectly, and these particles, called “tachyons,” really do exist. The scientists reviewed the logs immediately, but they could not figure out how the program performed the demonstration.

  4. 4.

    A group of scientists at the Institute for Advanced Study has been studying the speed of light. Working with the Theory of Relativity, the scientists were trying to find particles that travel faster than light. One day, during an anomalous power surge, the computer program the scientists were using managed to mathematically demonstrate the existence of these faster-than-light particles with an equation. As it turns out, this equation works perfectly, and these particles, called “tachyons,” really do exist. The scientists reviewed the logs immediately, but they could not figure out how the program performed the demonstration.

  5. 5.

    A group of scientists at the Institute for Advanced Study has been studying the speed of light. Working with electronic circuit boards, the scientists were trying to find particles that travel faster than light. One day, during a day of routine calculations, the computer program the scientists were using managed to physically accelerate the particles in the circuit boards to speeds faster than that of light. As it turns out, the circuit boards work perfectly, and these faster-than-light particles, called “tachyons,” really were being accelerated. The scientists reviewed the logs immediately, and they figured out how the program performed the acceleration.

  6. 6.

    A group of scientists at the Institute for Advanced Study has been studying the speed of light. Working with electronic circuit boards, the scientists were trying to find particles that travel faster than light. One day, during an anomalous power surge, the computer program the scientists were using managed to physically accelerate the particles in the circuit boards to speeds faster than that of light. As it turns out, the circuit boards work perfectly, and these faster-than-light particles, called “tachyons,” really were being accelerated. The scientists reviewed the logs immediately, and they figured out how the program performed the acceleration.

  7. 7.

    A group of scientists at the Institute for Advanced Study has been studying the speed of light. Working with electronic circuit boards, the scientists were trying to find particles that travel faster than light. One day, during a day of routine calculations, the computer program the scientists were using managed to physically accelerate the particles in the circuit boards to speeds faster than that of light. As it turns out, the circuit boards work perfectly, and these faster-than-light particles, called “tachyons,” really were being accelerated. The scientists reviewed the logs immediately, but they could not figure out how the program performed the acceleration.

  8. 8.

    A group of scientists at the Institute for Advanced Study has been studying the speed of light. Working with electronic circuit boards, the scientists were trying to find particles that travel faster than light. One day, during an anomalous power surge, the computer program the scientists were using managed to physically accelerate the particles in the circuit boards to speeds faster than that of light. As it turns out, the circuit boards work perfectly, and these faster-than-light particles, called “tachyons,” really were being accelerated. The scientists reviewed the logs immediately, but they could not figure out how the program performed the acceleration.

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Mizrahi, M., Buckwalter, W. The Role of Justification in the Ordinary Concept of Scientific Progress. J Gen Philos Sci 45, 151–166 (2014). https://doi.org/10.1007/s10838-014-9243-y

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