『計量国語学』アーカイブ

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KK300707
Guest Lecture
ヨーロッパにおける計量言語学：
言語学に適用される科学哲学の諸原理について ［英語原文］

Title

Quantitative Linguistics in Europe:
Principles of the Philosophy of Science as Applied toLinguistics [Original text in English]

著者

Reinhard KÖHLER
Reinhard KÖHLER
30巻7号
2016年12月20日

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471
475
計量国語学会
KK300706の英語原文．

Mathematical Linguistics, Vol.30 No.7 (December 2016) pp.471-475.

Guest Lecture

Quantitative Linguistics in Europe:
Principles of the Philosophy of Science as Applied to Linguistics
Reinhard Köhler (University of Trier, Germany)

Keywords: Quantitative Linguistics, Philosophy of Science, Europe, Synergetic Linguistics, selforganization in language
Abstract:
On the basis of the fundamental terms and concepts of the general philosophy of science, researchstrategies and methods of Quantitative Linguistics are described, as conducted in Europe since George
Kingsley Zipf's seminal work. These general principles are in line with those practised in the naturalsciences. Philosophical considerations as well as some decades of experience show that only specificmethodological differences between studies on natural phenomena and on cultural ones such as
language can be found. European approaches include empirical (inductive) and theoretical (deductive)
strategies with a preference on the latter ones. The presentation starts with a description and explicationof some terms and concepts which are fundamental for any kind of research, such as (scientific)
problem, hypothesis, law, boundary condition, theory, and explanation – terms, which are often
confused in linguistics. Examples are given of how these terms should be applied in linguistic work if
the principles of linguistic research as practised in Europe are followed. In particular, the deductive
strategy to find new laws is exemplified. The talk will also shed some light on the importance of laws
not only for theoretical progress but also for practical purposes. Finally, a recent approaches is
described which attempts to give a theoretical modelling background from which new law hypotheses
can be derived and known ones can be systemised.
One of the fundamental requirements of scientific research is a clear and precise way ofcommunication among scientists. The use of logics and mathematics serves this aim. An additional
principle in science is the clarification (elucidation) and definition of each concept and of each term
involved in scientific statements. The concepts and terms of science which have proved to befundamental for each discipline have, therefore, been discussed in the Philosophy of Science. We willconsider here the most basic terms used in any science.
Let us begin with the scientific problem because any scientific activity begins with a problem. Scientificproblems differ from everyday problems by the following four properties: meaningfulness, wellformedness, well-formulatedness, and connections with previous scientific knowledge. Scientificproblems can be differentiated into factual (empirical), conceptual, methodological, and valuational
ones. A scientific hypothesis is an assumption about a possible way to solve a given problem, often inform of an assumed answer to the question in the problem. Hypotheses are the core of a science – notdata as sometimes believed. A hypothesis in not a scientific hypothesis if it fails to be well-formed,471

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well-formulated and testable. There are several kinds of hypotheses, among them singular hypotheses,existential, statistical, bound and unbound universal ones. Only universal hypotheses which meet some
additional conditions can become laws (see below). The way to formulate new hypotheses (and laws)
thus starts from a problem and opens four kinds of epistemological approaches: analogy (find a similar
problem which has already been solved and try to adopt the solution), inductive (starting fromexperience with appropriate data and formulate a generalization), intuitive (just have an idea and try),and deductive (start from a set of well-corroborated hypotheses (and laws if available), draw
consequences from them which would answer the question at hand if correct).
According to M. Bunge, the famous Argentine philosopher of science, there are four levels ofvalidation of hypotheses, which we can illustrate in the following way:
Experience/empirical findings

type of hypothesis

theoretical knowledge

none

intuitive, speculation, guessing

none

yes

empirical generalization

none

none

deduced consequence

yes

yes

deduced consequence,empirically well corroborated,= plausible hypothesis

yes- Intuitive hypotheses without any empirical evidence and also without any theoretical justification
may be nevertheless correct but there is only an infinitely small chance to find them true. - Empiricalgeneralizations are grounded on some experience but they are still rather weak. For a very long time,science thought that all living things on earth need moderate temperature and oxygen to keep living.
Only a few years ago, thermophile bacteria have been detected, which feel well in boiling water, anda kind of worms in the deep sea live on "black smokers", they get their energy from hot water above
volcanic flaws. - Deductive hypotheses come with good reasons and are, therefore, more likely to turnout correct – but there is still a risk to find them wrong. - Only the fourth type, the universal, plausible,
well-tested hypothesis has a perfect probability to be true. If such a hypothesis is anchored in a systemof theoretical statements which are themselves at least of this type can it, when it has been tested again
and again on more and more data from various sources, may be called a law. The structure of scientificresearch can be illustrated by means of a diagram after Bunge:472

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Body of available
knowledge
ProblemHypotheses
Testableconsequences

Test technique

Evaluations ofhypotheses

New body ofknowledge
New problem

Evidence
Figure taken from Bunge (1998a, p.11)

Science proceeds on three levels: observation (in linguistics the observation how people communicate
with linguistic means), description (the level of dictionaries and grammars) and explanation (the levelof laws and theories). We will therefore have a short look at the terms law, theory, and explanation.
As stated above, a law is a particularly well tested and corroborated universal hypothesis which follows
from a theory or at least from a set of theoretically plausible statements. Laws are the only means toexplain fact or phenomena or to predict events. Nothing can be explained without corresponding laws.
They are expected to be valid everywhere in the universe and at all times.
A set of interconnected laws and accepted hypotheses is called a theory.
We must confess that in linguistics the presented terms are very often misused and cause someconfusion. Individual claims and statements, methods, concepts, and descriptive approaches are called
theories although all these elements do not contain any laws or hypotheses and fail to explain anything.
All these elements will have to be explained themselves.
Now, what is a scientific explanation? It took many centuries until this concept was understood.
Not earlier than in 1965, Carl Hempel published a paper which showed that previous ideas about how
logically correct and complete explanations can be achieved. The following scheme has become
known as "Hempel-Oppenheim structure", showing the logical structure of the so-called deductivenomological explanation. As this term indicates, explanation is understood as logical subsumption ofa fact under laws by logical deduction.

G1, G2, G3, …, Gn
R1, R2, R3, …, Rm
Fact
The first two lines are called explanans, the last line is the explanandum. The G1, G2, G3, …, Gn standfor the relevant laws, whereas the R1, R2, R3, …, Rm represent boundary conditions. In linguistics, somelaws are connected with boundary conditions such as that the object of analysis be an individual full473

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text in a natural language – not a fragment and not a collection of texts. From such laws and boundary
conditions facts can be deduced following the rules of logic reasoning.
Thus, the highest and most demanding goal of any science is the explanation of observed and describedphenomena by means of a theory. In linguistics, two approaches to set up a theory are known. One ofthem is called Synergetic Linguistics (Köhler) and is based on a systems theoretic model, the other one,
the Unified Theory (Wimmer and Altmann) consists of a complicated differential or difference
equation. We will here describe Synergetic Linguistics because it is particularly well suitable to findand develop new laws by deduction from theoretical considerations, to test them, to combine them intoa network of laws and hypotheses which are law candidates, and to explain the phenomena observed.
As linguistic explanation is not likely to be possible by means of causal relations, synergetic linguistics
aims at functional explanation (similar to biology). This type of explanation, however, is logicallysound only under certain circumstances. A central axiom of synergetic linguistics is, therefore, that
language is a self-organizing and self-regulating system (similar to an organism) – a special kind of
dynamic system with particular properties.
Modelling in the framework of synergetic linguistics proceeds iteratively in refining phases, whereeach phase consists of six individual steps. In the first step, axioms are set up for the subsystem underconsideration. There is one structural axiom which belongs to the synergetic approach itself: the axiom
that language is a self-organising and self-regulating system. Other axioms take the form of system
requirements. In synergetic terminology, these requirements are order parameters. They are not part ofthe system under consideration but are linked to it and have some influence on the behaviour of thesystem. In the terminology of the philosophy of science, they play the role of boundary conditions.
These requirements can be subdivided into three kinds: (1) language-constituting requirements (among
them the fundamental coding requirement, representing the necessity to provide expressions for given
meanings, the application requirement, i.e. the need to use a given expression in order to express oneof its meanings, the specification requirement, representing the need to form more specific expressions
than the ones which are available at a given time, and the de-specification requirement for the cases
where the available expressions are too specific for the current communicative purpose), (2) languageforming requirements (such as the economy requirement in its various manifestations) and (3) controllevel requirements (the adaptation requirement, i.e. the need for a language to adapt itself to varying
circumstances, and the opposite stability requirement). The second step is the determination of systemlevels, units, and variables which are of interest to the current investigation. In step three, relevant
consequences, effects, and interrelations are determined. Here, the researcher sets up or systematises
hypotheses about dependences of variables on other variables, e.g. with increasing polytextuality of alexical item its polysemy increases monotonically, or, the higher the position of a syntactic construction(i.e. the more to the right hand side of its mother constituent) the less its information, etc. The fourth
step consists of the search for functional equivalents and multi-functionalities. In language, there are
not only 1 : 1 correspondences – many relations are of the 1 : n or m : n type. This fact plays animportant role in the logics of functional explanation. Step five is the mathematical formulation of the474

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hypotheses set up so far – a precondition for any rigorous test – and step 6 is the empirical test of thesemathematically formulated hypotheses.
Laws are not only indispensible for the theoretic development of a scientific discipline but also offundamental importance for practical problems. Even such seemingly simple tasks such as thecomparison of two texts with respect to a specific property cannot be reliably solved without thebackground of at least one corresponding law. A researcher can define and use some measure anddetermine its value for the two (or more) texts. However, it is impossible to determine the significanceof the differences between the measured values without knowledge of the lawful distribution of thegiven measure. The quest for laws serves both kinds of scientific activities: pure science and appliedscience.
References:
Bunge, Mario
1967 Scientific Research I, II. Berlin, Heidelberg, New York: Springer.
1998a Philosophy of science. From problem to theory. New Brunswick, London:Transaction Publishers. 3rd ed. 2005.
1998b Philosophy of science. From explanation to justification. New Brunswick, London:Transaction Publishers. 4th ed. 2007.
Hempel, Carl
1965 Aspects of Scientific Explanation and other Essays in the Philosophy of Science. New
York: Free Press.
Köhler, Reinhard
1986 Zur linguistischen Synergetik. Struktur und Dynamik der Lexik. Bochum: Brockmeyer.
1987 “Systems theoretical linguistics.” In: Theoretical Linguistics 14/2-3; 241–257.
1990a “LinguistischeAnalyseebenen.Hierarchisierung und Erklärung im Modell dersprachlichen Selbstregulation.” In: Hřebíček Ludék (ed.), Glottometrika 11. Bochum:Brockmeyer, 1–18.
2005b “Synergetic linguistics.” In: Köhler, Reinhard; Altmann, Gabriel; Piotrowski,Rajmond G. (eds.), Quantitative Linguistik. Ein internationales Handbuch.
Quantitative Linguistics. An International Handbook. Berlin, New York: de Gruyter,760–774.
Wimmer, Gejza; Altmann, Gabriel
2005 “Unified derivation of some linguistic laws.” In: Köhler, Reinhard; Altmann, Gabriel;
Piotrowski, Rajmond G. (eds.), Quantitative Linguistik. Ein internationales Handbuch.
Quantitative Linguistics. An International Handbook. Berlin, New York: de Gruyter,791-807.
（Received on May 29, 2016）

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