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Summary Topics covered under the rubric of "Scientific Language Misc" are simply those which do not fall in any straightforward manner into other sections of the "Scientific Language" category.
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  1. Wilda Anderson (1985). Rhetoric and Nomenclature in Lavoisier's Chemical Language. Topoi 4 (2):165-169.
    Implicit in the theoretical chemical writings of Antoine Laurent Lavoisier is a theory of language that is not in complete harmony with the philosopher of language whom he takes as his explicit authority, Condillac. Lavoisier's reform of the nomenclature of chemistry leads to his dividing scientific language into two sets with different properties: a denotative artificial nomenclature and connotative natural language. This division supposedly permits knowledge to be stored in the nomenclature while the natural language retains the rhetorical tools necessary (...)
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  2. Holger Andreas (2010). Semantic Holism in Scientific Language. Philosophy of Science 77 (4):524-543.
    Whether meaning is compositional has been a major issue in linguistics and formal philosophy of language for the last 2 decades. Semantic holism is widely and plausibly considered as an objection to the principle of semantic compositionality therein. It comes as a surprise that the holistic peculiarities of scientific language have been rarely addressed in formal accounts so far, given that semantic holism has its roots in the philosophy of science. For this reason, a model-theoretic approach to semantic holism in (...)
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  3. Jesús P. Zamora Bonilla (2003). Meaning and Testability in the Structuralist Theory of Science. Erkenntnis 59 (1):47 - 76.
    The connection between scientific knowledge and our empirical access to realityis not well explained within the structuralist approach to scientific theories. I arguethat this is due to the use of a semantics not rich enough from the philosophical pointof view. My proposal is to employ Sellars–Brandom's inferential semantics to understand how can scientific terms have empirical content, and Hintikka's game-theoretical semantics to analyse how can theories be empirically tested. The main conclusions are that scientific concepts gain their meaning through `basic (...)
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  4. Richard N. Boyd (1993). Metaphor and Theory Change. In A. Ortony (ed.), Metaphor and Thought, 2nd Edition. Cambridge University Press.
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  5. Jordi Cat (2012). Thomas Uebel. Empiricism at the Crossroads: The Vienna Circle's Protocol-Sentence Debate. Full Circle: Publications of the Archive of Scientific Philosophy 4. Chicago: Open Court, 2007. Pp. Xviii+ 518. $80.96 (Paper). [REVIEW] Hopos 2 (2):354-360.
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  6. Steven G. Darian (2003). Understanding the Language of Science. University of Texas Press.
    "To my knowledge, there has never [before] been a volume that analyzes, in one place, the actual language of science--those elements of thinking that are acknowledged to be the basis of scientific thought. . . . [Thus] this is a very important book, contributing to several fields: science, education, rhetoric, medicine, and perhaps even philosophy. . . . Darian's erudition is truly astonishing." --Celest A. Martin, Associate Professor, College Writing Program, University of Rhode Island From astronomy to zoology, the practice (...)
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  7. Kevin Elliott, Ignorance, Uncertainty, and the Development of Scientific Language.
    Robert Proctor has argued that ignorance or non-knowledge can be fruitfully divided into at least three categories: (1) ignorance as native state or starting point; (2) ignorance as lost realm or selective choice; and (3) ignorance as strategic ploy or active construct. This chapter explores Proctor’s second category, ignorance as selective choice. When scientists investigate poorly understood phenomena, they have to make selective choices about what questions to ask, what research strategies and metrics to employ, and what language to use (...)
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  8. Jan Faye, Interpretation in the Natural Sciences.
    Interpretation in science has gained little attention in the past because philosophers of science believed that interpretation belongs to the context of discovery or must be associated with meaning. But scientists often speak about interpretation when they report their findings. Elsewhere I have argue in favour of a pragmatic-rhetorical theory of explanation, and it is in light of this theory that I suggest we can understand interpretation in the natural sciences.
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  9. E. Fischer (2014). Mind the Metaphor! A Systematic Fallacy in Analogical Reasoning. Analysis 75 (1):67-77.
    Conceptual metaphors facilitate both productive and pernicious analogical reasoning. This article addresses the question: When and why does the frequently helpful use of metaphor become pernicious? By applying the most influential theoretical framework from cognitive psychology in analysing the philosophically most prominent example of pernicious metaphorical reasoning , we identify a philosophically relevant but previously undescribed fallacy in analogical reasoning with metaphors. We then outline an explanation of why even competent thinkers commit this fallacy and obtain a psychologically informed ‘debunking’ (...)
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  10. Alan Ford & F. David Peat (1988). The Role of Language in Science. Foundations of Physics 18 (12):1233-1242.
    It is argued that language plays an active role in the development of scientific thought. A research project is outlined which will investigate this hypothesis and, in addition, focus on such questions as the role of mathematics in science and the status of the genetic code. “Nothing is more usual than for philosophers to encroach on the province of grammarians, and to engage in disputes of words, while they imagine they are handling controversies of the deepest importance and concern.”—David Hume.
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  11. Hajo Greif (2005). Dawkins and Latour. A Tale of Two Unlikely Fellows. In Arno Bammé (ed.), Yearbook 2005 of the Institute for Advanced Studies on Science, Technology and Society. Profil. 99-124.
    Two popular, yet highly controversial concepts of non-human agency from two different fields of knowledge are compared in this essay: the theory of the Selfish Gene, introduced into neo-Darwinian evolutionary biology by Richard Dawkins, and Actor-Network Theory, as brought forward in Science & Technology Studies by Bruno Latour. It is argued that the two theories, despite all apparent differences, share key motifs and motivations when they try to forward knowledge in their respective fields by adopting a vocabulary that aims at (...)
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  12. D. Greimann (2000). The Judgement-Stroke as a Truth-Operator: A New Interpretation of the Logical Form of Sentences in Frege's Scientific Language. [REVIEW] Erkenntnis 52 (2):213-238.
    The syntax of Frege's scientific language is commonly taken to be characterized by two oddities: the representation of the intended illocutionary role of sentences by a special sign, the judgement-stroke, and the treatment of sentences as a species of singular terms. In this paper, an alternative view is defended. The main theses are: the syntax of Frege's scientific language aims at an explication of the logical form of judgements; the judgement-stroke is, therefore, a truth-operator, not a pragmatic operator; in Frege's (...)
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  13. Ernest H. Hutten (1954). Natural and Scientific Language. Philosophy 29 (108):27 - 43.
    Whenever we speak with someone in everyday life, when we write a letter or read a novel, we are said to use natural language. We have a historically given language like English or French; we consider familiar things and events; and we use the language more or less as most members of the same community use it.
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  14. Kevin B. Korb (2004). Introduction: Machine Learning as Philosophy of Science. Minds and Machines 14 (4):433-440.
    I consider three aspects in which machine learning and philosophy of science can illuminate each other: methodology, inductive simplicity and theoretical terms. I examine the relations between the two subjects and conclude by claiming these relations to be very close.
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  15. Ulrich Meyer (2002). Is Science First-Order? Analysis 62 (276):305-308.
    It is a popular view amongst some philosophers, most notably those with Quinean views about ontological commitment, that scientific theories are first-orderizable; that we can regiment all such theories in an extensional first-order language. I argue that this view is false, and that any acceptable account of science needs to take some modal notion as primitive.
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  16. Steven I. Miller & Marcel Fredericks (1997). Another View of Translation Manuals and the Study of Science. Synthese 113 (2):171-193.
    The article argues for the possibility of translation manuals having an implicit internal structure. This structure is composed of specific methodological assumptions and techniques. Using the (N)-type and (G)-type distinction developed by Fuller for the study of scientific behavior, it is shown that these are incomplete characterizations of translation manuals. A more complete characterization must involve an analysis of how the presence or absence of methodological rules influences the interpretation of specific research questions. It is further argued that while Quine's (...)
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  17. Andrew Moore (2013). On the State of Scientific English and How to Improve It–Part 3. Bioessays 35 (8):667-667.
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  18. Andrew Moore (2013). On the State of Scientific English and How to Improve It–Part 1. Bioessays 35 (5):409-409.
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  19. Andrew Moore (2013). On the State of Scientific English and How to Improve It–Part 4. Bioessays 35 (11):925-925.
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  20. A. Ortony (ed.) (1993). Metaphor and Thought. Cambridge University Press.
    The book will serve as an excellent graduate-level textbook in cognitive psychology, linguistics, and artificial intelligence.
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  21. S. Psillos (1996). Review. Science, Reality and Language. Michelle Marsonet. British Journal for the Philosophy of Science 47 (4):663-668.
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  22. Morton L. Schagrin (1973). Whewell's Theory of Scientific Language. Studies in History and Philosophy of Science Part A 4 (3):231-240.
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  23. Pradip Kumar Sengupta (1995). Science, Language, and Creativity. Progressive Publishers.
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  24. Yaroslav Sergeyev (2010). Counting Systems and the First Hilbert Problem. Nonlinear Analysis Series A 72 (3-4):1701-1708.
    The First Hilbert problem is studied in this paper by applying two instruments: a new methodology distinguishing between mathematical objects and mathematical languages used to describe these objects; and a new numeral system allowing one to express different infinite numbers and to use these numbers for measuring infinite sets. Several counting systems are taken into consideration. It is emphasized in the paper that different mathematical languages can describe mathematical objects (in particular, sets and the number of their elements) with different (...)
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  25. Roy A. Sorensen (1997). The Metaphysics of Precision and Scientific Language. Philosophical Perspectives 11 (s11):349-374.
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  26. J. Starobinski (1977). Poetic Language and Scientific Language. Diogenes 25 (100):128-145.
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  27. H. Stonert (1964). Languages and Theories Adequate to the Ontology of Scientific Language. Studia Logica 15 (1):76-77.
  28. Sean Walsh, Eleanor Knox & Adam Caulton (2014). Critical Review of Mathematics and Scientific Representation. [REVIEW] Philosophy of Science 81 (3):460-469.
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