Epistemetrics {ReadingNotes}

Epistemetrics by Nicholas Rescher - ISBN 0521861209 - Cambridge University Press 2006

Motivation

Importance of epistemology yet lack of quantitative formalism or computational epistemology, ideally directly a dedicated programming framework.

Pre-reading model

Draw a schema (using PmGraphViz or another solution) of the situation of the area in the studied domain before having read the book.

Reading

• 1 Asking for More Than Truth: Duhem’s Law of Cognitive Complementarity
  • Security/Definiteness Trade-off : s × d ≤ const (p1)
  • ∫ ydx = c ∫ dx/x ≈ log x (p2)
• 2 Kant’s Conception of Knowledge as Systematized Information
  • "to qualify as authentic, cognitively significant knowledge, informative contentions must be part of a system" (p12)
  • "Kant’s line of thought can be carried a step further to the idea that in a well-designed systemic exposition of information, systemic role mirrors cognitive status." (p13)
• 3 Spencer’s Law of Cognitive Development
  • "the developmental process may be of limited applicability in biological evolution, but there can be little question about its holding good in cognitive evolution." (p16)
  • "what may be called Spencer’s Law of Cognitive Development: As a body of information on any given topic grows in size the complexity of that body – its inner variation and diversification – also increases" (p17)
  • compl (I) ≈ ∫ d#I/#I ∝ log #I
    • information (I)
    • the volume of that body of information (#I)
  • "With the expansion of information, its complexity does increase, but only at a decreasing (logarithmic) rate." (p28)
• 4 Gibbon’s Law of Logarithmic Returns
  • K[I] = log #I (p33)
    • K[I] quantity of knowledge inherent in a body of information I of size #I
  • ∫ΔE/E = log E (p35)
    • fresh experience superadds its additional increment ΔE to the preexisting total E
  • mention of Kuhn's The Structure of Scientific Revolution (p35)
  • "In milking additional information for cognitively significant insights it is generally the proportion of the increase that matters: its percentage rather than its brute amount." (p40)
  • "Where compilation increases information by multiplicative leaps and bounds, the increase in knowledge is merely additive." (p40)
  • mention of how a newly opened domain can be rushed in similar to ideas presented by Allen Newell in his Desires and Diversions 1993 talk at CMU
  • "The increase of knowledge over time stands to the increase of information in a proportion fixed by the inverse of the volume of already available information:
    • d/dt K[I] ≈ d/dt log #I ≈ 1/#I * d/dt #I" (p43-44)
• 5 Adams’s Thesis on Exponential Growth
  • (p45)
• 6 Quality Retardation
  • Wikipedia:Lotka's law (p64)
  • "importance can just as effectively be estimated in terms of prominence in citation space as by prominence in discussion space." (p71)
• 7 How Much Can Be Known? A Leibnizian Perspective on the Quantitative Discrepancy Between Linguistic Truth and Objective Fact
  • (p73)
• 8 On the Limits of Knowledge: A Kantian Perspective on Cognitive Finitude
  • "Geographic exploration can expect eventual completeness; cognitive exploration cannot." (p102)
  • "It has been said insightfully that from the vantage point of a less developed technology, another substantially advanced technology is indistinguishable from magic. And exactly the same holds for a more advanced conceptual (rather than physical) technology." (p104)
• Conclusion
  • Summarize each chapter in few sentences without equations (p105-106)

See also

• extended Table of contents
• Nicholas Rescher, University of Pittsburgh
• Wikipedia:Nicholas Rescher
• Reviewed by Jeffrey Tlumak, Vanderbilt University, University of Notre Dame Philosophical Reviews 2006
• Epistemetrics: What We Measure by Eliezer Geisler, IGI Global 2008
• Epistemetrics: conceptual domain and metrics of knowledge management by Eliezer Geisler and Nilmini Wickramasinghe, International Journal of Innovation and Learning 2008
• brief history of Google MapReduces jobs including the ize of the datasets A study in Scalability and A little systems horse sense, My missives November 2010
• Wikipedia:Jonathan Huebner

Overall remarks and questions

• trace your personal epistemic path
  1. take the list of papers you have read over time
  2. extract category per paper + read date
  3. animate a node over a scientometrics map with the related categories
  • could be journal names rather than category (e.g. scientometric map)
• it feels more and more than giving equations is the last century way of be rigorous with ones' ideas
  • it doesn't mean that every software implementation of an idea makes it rigorous though
• since we have quantities over time, could such principles also be used to measure the speed of advances?
  • eventually the theoretical or average maximum speed of epistemic progresses?

Synthesis

So in the end, it was about X and was based on Y.

Critics

Point A, B and C are debatable because of e, f and j.

Vocabulary

(:new_vocabulary_start:) new_word (:new_vocabulary_end:)

Post-reading model

Draw a schema (using PmGraphViz or another solution) of the situation of the area in the studied domain after having read the book. Link it to the pre-reading model and align the two to help easy comparison.

Categories

• UncategorizedBook

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