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    BCH ๋ถ€ํ˜ธ๋ฅผ ์ด์šฉํ•œ FrodoKEM์˜ ์„ฑ๋Šฅ ๊ฐœ์„  ๋ฐ ๋™ํ˜• ๋น„๊ต๋ฅผ ์œ„ํ•œ ํ•ฉ์„ฑํ•จ์ˆ˜์— ์˜ํ•œ ๋ถ€ํ˜ธ ํ•จ์ˆ˜์˜ ๋ฏธ๋‹ˆ๋งฅ์Šค ๊ทผ์‚ฌ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ •๋ณด๊ณตํ•™๋ถ€, 2020. 8. ๋…ธ์ข…์„ .In this dissertation, two main contributions are given as; Performance improvement of FrodoKEM using Gray and error-correcting codes (ECCs). Optimal minimax polynomial approximation of sign function by composite polynomial for homomorphic comparison. First, modification of FrodoKEM using Gray codes and ECCs is studied. Lattice-based scheme is one of the most promising schemes for post-quantum cryptography (PQC). Among many lattice-based cryptosystems, FrodoKEM is a well-known key-encapsulation mechanism (KEM) based on (plain) learning with errors problems and is advantageous in that the hardness is based on the problem of unstructured lattices. Many lattice-based cryptosystems adopt ECCs to improve their performance, such as LAC, Three Bears, and Round5 which were presented in the NIST PQC Standardization Round 2 conference. However, for lattice-based cryptosystems that do not use ring structures such as FrodoKEM, it is difficult to use ECCs because the number of transmitted symbols is small. In this dissertation, I propose a method to apply Gray and ECCs to FrodoKEM by encoding the bits converted from the encrypted symbols. It is shown that the proposed method improves the security level and/or the bandwidth of FrodoKEM, and 192 message bits, 50\% more than the original 128 bits, can be transmitted using one of the modified Frodo-640's. Second, an optimal minimax polynomial approximation of sign function by a composite polynomial is studied. The comparison function of the two numbers is one of the most commonly used operations in many applications including deep learning and data processing systems. Several studies have been conducted to efficiently evaluate the comparison function in homomorphic encryption schemes which only allow addition and multiplication for the ciphertext. Recently, new comparison methods that approximate sign function using composite polynomial in the homomorphic encryption, called homomorphic comparison operation, were proposed and it was proved that the methods have optimal asymptotic complexity. In this dissertation, I propose new optimal algorithms that approximate the sign function in the homomorphic encryption by using composite polynomials of the minimax approximate polynomials, which are constructed by the modified Remez algorithm. It is proved that the number of required non-scalar multiplications and depth consumption for the proposed algorithms are less than those for any methods that use a composite polynomial of component polynomials with odd degree terms approximating the sign function, respectively. In addition, an optimal polynomial-time algorithm for the proposed homomorphic comparison operation is proposed by using dynamic programming. As a result of numerical analysis, for the case that I want to minimize the number of non-scalar multiplications, the proposed algorithm reduces the required number of non-scalar multiplications and depth consumption by about 33% and 35%, respectively, compared to those for the previous work. In addition, for the case that I want to minimize the depth consumption, the proposed algorithm reduces the required number of non-scalar multiplications and depth consumption by about 10% and 47%, respectively, compared to those for the previous work.์ด ํ•™์œ„ ๋…ผ๋ฌธ์—์„œ๋Š”, ๋‹ค์Œ ๋‘ ๊ฐ€์ง€ ๋‚ด์šฉ์ด ์—ฐ๊ตฌ๋˜์—ˆ๋‹ค. FrodoKEM์„ ๊ทธ๋ ˆ์ด ๋ถ€ํ˜ธ ๋ฐ ์˜ค๋ฅ˜์ •์ •๋ถ€ํ˜ธ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๊ฐœ์„  ๋™ํ˜• ๋น„๊ต ์—ฐ์‚ฐ์„ ์œ„ํ•ด ํ•ฉ์„ฑ ๋‹คํ•ญ์‹์„ ์‚ฌ์šฉํ•œ ๋ถ€ํ˜ธ ํ•จ์ˆ˜์˜ ์ตœ์  ๋ฏธ๋‹ˆ๋งฅ์Šค ๋‹คํ•ญ์‹ ๊ทผ์‚ฌ ๋จผ์ €, ๊ทธ๋ ˆ์ด ๋ถ€ํ˜ธ ๋ฐ ์˜ค๋ฅ˜์ •์ •๋ถ€ํ˜ธ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ FrodoKEM์„ ๋ณ€ํ˜•์‹œํ‚ค๋Š” ๋ฐฉ๋ฒ•์ด ์—ฐ๊ตฌ๋˜์—ˆ๋‹ค. ๊ฒฉ์ž๊ธฐ๋ฐ˜์•”ํ˜ธ๋Š” ๊ฐ€์žฅ ์œ ๋งํ•œ ํฌ์ŠคํŠธ ์–‘์ž ์•”ํ˜ธ ์Šคํ‚ด์ด๋‹ค. ๋งŽ์€ ๊ฒฉ์ž๊ธฐ๋ฐ˜์•”ํ˜ธ ์‹œ์Šคํ…œ ์ค‘์—์„œ FrodoKEM์€ learning with errors (LWE) ๋ฌธ์ œ์— ๊ธฐ๋ฐ˜์„ ๋‘” ์ž˜ ์•Œ๋ ค์ง„ ํ‚ค-์บก์Šํ™” ๋ฉ”์ปค๋‹ˆ์ฆ˜ (KEM) ์ด๋ฉฐ ๊ตฌ์กฐ๋ฅผ ๊ฐ–์ง€ ์•Š์€ ๊ฒฉ์ž ๋ฌธ์ œ์— ๊ธฐ๋ฐ˜์„ ๋‘” ์–ด๋ ค์›€์„ ๊ฐ€์ง„๋‹ค๋Š” ์žฅ์ ์ด ์žˆ๋‹ค. NIST ํฌ์ŠคํŠธ ์–‘์ž ์•”ํ˜ธ ํ‘œ์ค€ํ™” ๋ผ์šด๋“œ 2์— ๋ฐœํ‘œ๋œ LAC, Three Bears, Round5์™€ ๊ฐ™์ด ์„ฑ๋Šฅ ๊ฐœ์„ ์„ ์œ„ํ•ด ์˜ค๋ฅ˜์ •์ •๋ถ€ํ˜ธ๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ๋งŽ์€ ์•”ํ˜ธ ์‹œ์Šคํ…œ๋“ค์ด ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ FrodoKEM๊ณผ ๊ฐ™์ด ๋ง ๊ตฌ์กฐ๋ฅผ ์‚ฌ์šฉํ•˜์ง€ ์•Š๋Š” ๊ฒฉ์ž๊ธฐ๋ฐ˜ ์•”ํ˜ธ ์‹œ์Šคํ…œ์—์„œ๋Š” ์ „์†ก๋˜๋Š” ์‹ฌ๋ณผ ๊ฐœ์ˆ˜๊ฐ€ ์ž‘๊ธฐ ๋•Œ๋ฌธ์— ์˜ค๋ฅ˜์ •์ •๋ถ€ํ˜ธ๋ฅผ ์‚ฌ์šฉํ•˜๊ธฐ ์–ด๋ ต๋‹ค. ๋‚˜๋Š” ์•”ํ˜ธํ™”๋œ ์‹ฌ๋ณผ๋กœ๋ถ€ํ„ฐ ๋ณ€ํ™˜๋œ ๋น„ํŠธ๋“ค์„ ๋ถ€ํ˜ธํ™”ํ•˜์—ฌ ์˜ค๋ฅ˜์ •์ •๋ถ€ํ˜ธ์™€ ๊ทธ๋ ˆ์ด ๋ถ€ํ˜ธ๋ฅผ FrodoKEM์— ์ ์šฉํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ์ œ์•ˆํ•œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ FrodoKEM์˜ ๋ณด์•ˆ์„ฑ ๋ ˆ๋ฒจ ํ˜น์€ ๋ฐ์ดํ„ฐ์ „์†ก๋Ÿ‰์„ ํ–ฅ์ƒํ•˜๊ณ  ๊ธฐ์กด 128๋น„ํŠธ๋ณด๋‹ค 50\% ๋งŽ์€ 192๋น„ํŠธ๊ฐ€ ๋ณ€ํ˜•๋œ Frodo-640์—์„œ ์ „์†ก๋  ์ˆ˜ ์žˆ์Œ์„ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. ๋‘ ๋ฒˆ์งธ๋กœ, ํ•ฉ์„ฑ ๋‹คํ•ญ์‹์„ ์‚ฌ์šฉํ•œ ๋ถ€ํ˜ธ ํ•จ์ˆ˜์˜ ์ตœ์  ๋ฏธ๋‹ˆ๋งฅ์Šค ๋‹คํ•ญ์‹ ๊ทผ์‚ฌ๊ฐ€ ์—ฐ๊ตฌ๋˜์—ˆ๋‹ค. ๋‘ ์ˆซ์ž์˜ ๋น„๊ต ํ•จ์ˆ˜๋Š” ๋”ฅ๋Ÿฌ๋‹ ๋ฐ ๋ฐ์ดํ„ฐ ์ฒ˜๋ฆฌ ์‹œ์Šคํ…œ์„ ํฌํ•จํ•œ ๋งŽ์€ ์‘์šฉ์—์„œ ๊ฐ€์žฅ ๋งŽ์ด ์‚ฌ์šฉ๋˜๋Š” ์—ฐ์‚ฐ ์ค‘ ํ•˜๋‚˜์ด๋‹ค. ์•”ํ˜ธ๋ฌธ ์ƒ์—์„œ์˜ ๋ง์…ˆ๊ณผ ๊ณฑ์…ˆ๋งŒ ์ง€์›ํ•˜๋Š” ๋™ํ˜• ์•”ํ˜ธ์—์„œ ๋น„๊ต ํ•จ์ˆ˜๋ฅผ ํšจ์œจ์ ์œผ๋กœ ๊ณ„์‚ฐํ•˜๋Š” ๋ช‡๋ช‡ ์—ฐ๊ตฌ๊ฐ€ ์ง„ํ–‰๋˜์—ˆ๋‹ค. ๋™ํ˜• ์•”ํ˜ธ์—์„œ ํ•ฉ์„ฑ ๋‹คํ•ญ์‹์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ถ€ํ˜ธ ํ•จ์ˆ˜๋ฅผ ๊ทผ์‚ฌํ•˜๋Š” ๋น„๊ต ๋ฐฉ๋ฒ•์€ ๋™ํ˜• ๋น„๊ต ์—ฐ์‚ฐ์ด๋ผ๊ณ  ๋ถˆ๋ฆฌ๋Š”๋ฐ ์ตœ๊ทผ ์ƒˆ๋กœ์šด ๋™ํ˜• ๋น„๊ต ์—ฐ์‚ฐ ๋ฐฉ๋ฒ•์ด ์ œ์•ˆ๋˜์—ˆ๊ณ  ๊ทธ ๋ฐฉ๋ฒ•์ด ์ตœ์  ์ ๊ทผ์  ๋ณต์žก๋„๋ฅผ ๊ฐ€์ง„๋‹ค๋Š” ๊ฒƒ์ด ์ฆ๋ช…๋˜์—ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ ๋‚˜๋Š” ๋ฏธ๋‹ˆ๋งฅ์Šค ๊ทผ์‚ฌ๋‹คํ•ญ์‹์˜ ํ•ฉ์„ฑํ•จ์ˆ˜๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๋™ํ˜•์•”ํ˜ธ์—์„œ ๋ถ€ํ˜ธ ํ•จ์ˆ˜๋ฅผ ๊ทผ์‚ฌํ•˜๋Š” ์ƒˆ๋กœ์šด ์ตœ์  ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•œ๋‹ค. ๋ฏธ๋‹ˆ๋งฅ์Šค ๊ทผ์‚ฌ ๋‹คํ•ญ์‹์€ modified Remez ์•Œ๊ณ ๋ฆฌ์ฆ˜์— ์˜ํ•ด ์–ป์„ ์ˆ˜ ์žˆ๋‹ค. ์ œ์•ˆํ•˜๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ์ž„์˜์˜ ๋ถ€ํ˜ธ ํ•จ์ˆ˜๋ฅผ ๊ทผ์‚ฌํ•˜๋Š” ํ™€์ˆ˜ ์ฐจ์ˆ˜ ํ•ญ๋“ค์„ ๊ฐ€์ง„ ๋‹คํ•ญ์‹์˜ ํ•ฉ์„ฑ ๋‹คํ•ญ์‹์„ ์‚ฌ์šฉํ•˜๋Š” ๋ฐฉ๋ฒ•๋ณด๋‹ค ๋” ์ ์€ ๋„Œ์Šค์นผ๋ผ ๊ณฑ ๋ฐ ๋Ž์Šค ์†Œ๋ชจ๋ฅผ ์‚ฌ์šฉํ•œ๋‹ค๋Š” ๊ฒƒ์ด ์ฆ๋ช…๋˜์—ˆ๋‹ค. ๋˜ํ•œ, ์ œ์•ˆํ•œ ๋™ํ˜• ๋น„๊ต ์—ฐ์‚ฐ์— ๋Œ€ํ•œ ๋‹ค์ด๋‚˜๋ฏน ํ”„๋กœ๊ทธ๋ž˜๋ฐ์„ ์‚ฌ์šฉํ•œ ์ตœ์  ๋‹คํ•ญ์‹œ๊ฐ„ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ์ œ์•ˆ๋˜์—ˆ๋‹ค. ์ˆ˜์น˜ ๋ถ„์„ ๊ฒฐ๊ณผ, ๋„Œ์Šค์นผ๋ผ ๊ณฑ ๊ฐœ์ˆ˜๋ฅผ ์ตœ์†Œ๋กœ ํ•  ๋•Œ, ์ œ์•ˆํ•˜๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ํ•„์š”ํ•œ ๋„Œ์Šค์นผ๋ผ ๊ณฑ ๊ฐœ์ˆ˜์™€ ๋Ž์Šค ์†Œ๋ชจ๋ฅผ ๊ธฐ์กด ๋ฐฉ๋ฒ•์˜ ํ•„์š”ํ•œ ๋„Œ์Šค์นผ๋ผ ๊ณฑ ๊ฐœ์ˆ˜ ๋ฐ ๋Ž์Šค ์†Œ๋ชจ๋ณด๋‹ค ๊ฐ๊ฐ 33%, 35%์ •๋„ ๊ฐ์†Œ์‹œํ‚จ๋‹ค. ๋˜ํ•œ, ๋Ž์Šค ์†Œ๋ชจ๋ฅผ ์ตœ์†Œ๋กœ ํ•  ๋•Œ, ์ œ์•ˆํ•˜๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ํ•„์š”ํ•œ ๋„Œ์Šค์นผ๋ผ ๊ณฑ ๊ฐœ์ˆ˜์™€ ๋Ž์Šค ์†Œ๋ชจ๋ฅผ ๊ธฐ์กด ๋ฐฉ๋ฒ•์˜ ํ•„์š”ํ•œ ๋„Œ์Šค์นผ๋ผ ๊ณฑ ๊ฐœ์ˆ˜ ๋ฐ ๋Ž์Šค ์†Œ๋ชจ๋ณด๋‹ค ๊ฐ๊ฐ 10%, 47%์ •๋„ ๊ฐ์†Œ์‹œํ‚จ๋‹ค.1 Introduction 1 1.1 Background 1 1.2 Overview of Dissertation 3 1.3 Notations 5 2 Preliminaries 6 2.1 NIST Post-Quantum Cryptography Standardization 6 2.1.1 Background 6 2.1.2 Categories for Security Level 7 2.1.3 List of Algorithms in NIST PQC Round 2 8 2.2 Public-Key Encryption and Key-Encapsulation Mechanism 10 2.3 Lattice-Based Cryptogaphy 13 2.3.1 Learning with Errors Problem 13 2.3.2 Overview of FrodoPKE Algorithm 14 2.3.3 Parameters of FrodoKEM 17 2.4 BCH and Gray Codes 18 2.5 Fully Homomorphic Encryption 20 2.5.1 Homomorphic Encryption 20 2.5.2 Comparison Operation in Fully Homomorphic Encryption 21 2.6 Approximation Theory 22 2.7 Algorithms for Minimax Approximation 24 3. Improvement of FrodoKEM Using Gray and BCH Codes 29 3.1 Modification of FrodoKEM with Gray and Error-Correcting Codes 33 3.1.1 Viewing FrodoPKE as a Digital Communication System 33 3.1.2 Error-Correcting Codes for FrodoPKE 34 3.1.3 Gray Coding 36 3.1.4 IND-CCA Security of Modified FrodoKEM 38 3.1.5 Evaluation of DFR 40 3.1.6 Error Dependency 43 3.2 Performance Improvement of FrodoKEM Using Gray and BCH Codes 43 3.2.1 Improving the Security Level of FrodoKEM 43 3.2.2 Increasing the Message Size of Frodo-640 47 3.2.3 Reducing the Bandwidth of Frodo-640 50 4. Homomorphic Comparison Using Optimal Composition of Minimax Approximate Polynomials 54 4.1 Introduction 54 4.1.1 Previous Works 55 4.1.2 My Contributions 56 4.2 Approximation of Sign Function by Using Optimal Composition of Minimax Approximate Polynomials 58 4.2.1 New Approximation Method for Sine Function Using Composition of the Minimax Approximate Polynomials 58 4.2.2 Optimality of Approximation of the Sign Function by a Minimax Composite Polynomial 64 4.2.3 Achieving Polynomial-Time Algorithm for New Approximation Method by Using Dynamic Programming 68 4.3 Numerical Results 80 4.3.1 Computation of the Required Non-Scalar Multiplications and Depth Consumption 81 4.3.2 Comparisons 81 5. Conclusions 88 Abstract (In Korean) 97Docto

    Eine Studie รผber die Ausformung der deutschen Lehre des Ermessensaktes

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๋ฒ•ํ•™๊ณผ, 2014. 2. ๋ฐ•์ •ํ›ˆ.๋ณธ ๋…ผ๋ฌธ์€ 19์„ธ๊ธฐ ํ›„๋ฐ˜๋ถ€ํ„ฐ 20์„ธ๊ธฐ ์ดˆ๋ฐ˜๊นŒ์ง€ ๋…์ผ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์˜ ํ˜•์„ฑ์— ๊ธฐ์—ฌํ•œ ์ฃผ์š” ํ•™์ž์ธ ๋ฒ ๋ฅด๋‚˜์น˜ํฌ(Bernatzik), ํ…Œ์ธ ๋„ˆ(Tezner), ๋ผ์šด(v. Laun), ์˜๋ฆฌ๋„คํฌ(Jellinek)์˜ ์ด๋ก ์— ๋Œ€ํ•œ ๋ถ„์„๊ณผ ๊ฒ€ํ† ๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ•œ๋‹ค. ์ด ์‹œ๊ธฐ๋ฅผ ์ง€๋‚˜ ์ฒด๊ณ„ํ™”๋œ ๋…์ผ์˜ ํšจ๊ณผ์žฌ๋Ÿ‰์ด๋ก ์€ ๊ทธ ํ‹€๊ณผ ๋‚ด์šฉ ๋ฉด์—์„œ ํฐ ๋ณ€ํ™” ์—†์ด ํ˜„์žฌ๊นŒ์ง€๋„ ๋…์ผ์—์„œ ํ†ต์„ค์ ์ธ ์œ„์น˜๋ฅผ ์ฐจ์ง€ํ•˜๊ณ  ์žˆ๊ณ , ์ด๊ฒƒ์ด ์šฐ๋ฆฌ๋‚˜๋ผ์˜ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์˜ ํ˜•์„ฑ์—๋„ ์ ์ง€ ์•Š์€ ์˜ํ–ฅ์„ ๋ฏธ์นœ ๊ฒƒ์ด ์‚ฌ์‹ค์ด๋‹ค. ๋น„์œ ์ปจ๋Œ€, ๋…์ผ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์˜ ๋ฟŒ๋ฆฌ์— ํ•ด๋‹นํ•œ๋‹ค๊ณ  ํ•  ์ˆ˜ ์žˆ๋Š” ์ฃผ์š”ํ•œ ์ด๋ก ์„ ์›์ „(ๅŽŸๅ…ธ)์˜ ๋ถ„์„์„ ํ†ตํ•ด ์ง์ ‘ ์‚ดํŽด๋ณด๊ณ  ๊ทธ ์˜์˜๋ฅผ ์žฌ์Œ๋ฏธํ•˜๊ณ  ์—ฐ๊ตฌํ•˜๋Š” ๊ฒƒ์€, ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์˜ ๊ธฐ์ดˆ์™€ ๋ฐฐ๊ฒฝ์— ๊ด€ํ•œ ๋ณด๋‹ค ๊นŠ์ด ์žˆ๋Š” ์ดํ•ด๋ฅผ ํ•˜๋Š” ๋ฐ ์ผ์กฐํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋ผ ์ƒ๊ฐํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์—ญ์‚ฌ์ โ€คํšŒ๊ณ ์  ์—ฐ๊ตฌ๋ฐฉ๋ฒ•๋ก ์€ ๊ธฐ์ดˆํ•™๋ฌธ์  ์„ฑ๊ฒฉ์„ ๊ฐ€์ง€๋Š” ๋™์‹œ์—, ์—ญ์‚ฌ์„ฑ์„ ๋ณธ์งˆ๋กœ ํ•˜๋Š” ๊ณต๋ฒ•ํ•™์˜ ๊ธฐ๋ณธ์  ๋ฐฉ๋ฒ•๋ก ์—๋„ ๋ถ€ํ•ฉํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋ณผ ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค. ๋ณธ ๋…ผ๋ฌธ์˜ ๊ตฌ์„ฑ์€ ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ๋จผ์ € ๋ณธ๊ฒฉ์ ์ธ ๋…ผ์˜์— ์•ž์„œ ๊ธฐ์ดˆ์ ์ธ ๊ฒ€ํ† ๋กœ์„œ, ์ œ1์žฅ์—์„œ๋Š” ์•ž์œผ๋กœ์˜ ๋…ผ์˜์— ํ•„์š”ํ•œ ๋ฒ”์œ„ ์•ˆ์—์„œ ๋…์ผ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์˜ ์—ญ์‚ฌ์™€ ๊ทธ ๋ฐœ์ „๊ณผ์ •์— ๋Œ€ํ•ด ๊ฐœ๊ด€ํ•œ๋‹ค. ํŠนํžˆ ์™œ 19์„ธ๊ธฐ ํ›„๋ฐ˜์— ๋…์ผ์ด ์•„๋‹Œ ์˜ค์ŠคํŠธ๋ฆฌ์•„์—์„œ๋ถ€ํ„ฐ ์ž์œ ์žฌ๋Ÿ‰์— ๊ด€ํ•œ ๋…ผ์˜๊ฐ€ ๋ณธ๊ฒฉํ™” ๋˜์—ˆ๊ณ , ์ œ2์ฐจ ์„ธ๊ณ„๋Œ€์ „ ์ดํ›„ ๋…์ผ์—์„œ ํšจ๊ณผ์žฌ๋Ÿ‰์ด๋ก ์ด ํ†ต์„ค์  ์ง€์œ„๋ฅผ ์ฐจ์ง€ํ•˜๊ฒŒ ๋˜์—ˆ๋Š”์ง€๋ฅผ ์‚ดํŽด๋ณด๋Š” ๊ฒƒ์ด ๊ทธ ์ค‘์‹ฌ์ ์ธ ๋‚ด์šฉ์ด๋‹ค. ์ œ2์žฅ์—์„œ๋Š” ์žฌ๋Ÿ‰์„ ๋ณธ๊ฒฉ์ ์ธ ๋ฒ•ํ•™์  ๋…ผ์˜์˜ ์žฅ(ๅ ด)์œผ๋กœ ๋Œ์–ด๋“ค์ด๊ณ  ๋ฒ•์ด๋ก ์ ์œผ๋กœ ์ ‘๊ทผ์„ ํ•œ ์„ ๊ตฌ์ž๋ผ ํ•  ์ˆ˜ ์žˆ๋Š” ๋ฒ ๋ฅด๋‚˜์น˜ํฌ(Bernatzik)์˜ ์š”๊ฑด์žฌ๋Ÿ‰์ด๋ก ์„ ๋‹ค๋ฃฌ๋‹ค. ํŠนํžˆ ๊ทธ๊ฐ€ ๋ฒ•๋ฅ ์š”๊ฑด ๋ถ€๋ถ„์— ์‚ฌ์šฉ๋œ ๋ชจํ˜ธํ•œ ์˜์—ญ(vage Kategorie), ์ฆ‰ ์ถ”์ƒ์ โ€ค๋ถˆํ™•์ • ๊ฐœ๋…์—์„œ ์žฌ๋Ÿ‰์ˆ˜๊ถŒ์˜ ์ฐฉ์•ˆ์ ์„ ๋ฐœ๊ฒฌํ•˜๊ณ  ๋˜ํ•œ ์ œ3์ž์˜ ์‹ฌ์‚ฌ๋ถˆ๊ฐ€๋Šฅ์„ฑ์œผ๋กœ์„œ ์žฌ๋Ÿ‰์˜ ๋ณธ์งˆ์„ ํŒŒ์•…ํ•˜๊ฒŒ ๋œ ๋…ผ๋ฆฌ์ ์ธ ํ๋ฆ„์„ ์‚ดํŽด๋ณด๋Š” ๊ฒƒ์ด ์ด ์žฅ์˜ ๋ชฉ์ ์ด๋‹ค. ์ œ3์žฅ์—์„œ๋Š” ๋‹น์‹œ ํ†ต์„ค์ด์—ˆ๋˜ ์š”๊ฑด์žฌ๋Ÿ‰์ด๋ก ์„ ๋น„ํŒํ•˜๋ฉด์„œ ํšจ๊ณผ์žฌ๋Ÿ‰์ด๋ก ์„ ์ฐฝ์‹œํ•œ ํ…Œ์ธ ๋„ˆ(Tezner)์˜ ๊ฒฌํ•ด๋ฅผ ์‚ดํŽด๋ณด๊ณ ์ž ํ•œ๋‹ค. ๊ทธ๋Š” ๋ฒ•์ •์ฑ…์ ์ธ ์ด์œ ์—์„œ ์žฌ๋Ÿ‰์˜ ์ธ์ •์˜์—ญ์„ ๋ฒ•๋ฅ ์š”๊ฑด์—์„œ ๋ฒ•๋ฅ ํšจ๊ณผ๋กœ ์ด๋™์‹œ์ผฐ๋‹ค. ์ฆ‰, ๊ทธ๋Š” ํ–‰์ •์— ๋Œ€ํ•˜์—ฌ ๊ฐ•ํ•œ ๋ถˆ์‹ ์„ ๊ฐ€์ง€๊ณ  ์žˆ์—ˆ๊ณ , ์‹œ๋ฏผ์  ์ž์œ ์ฃผ์˜์— ๋”ฐ๋ผ ์ ์  ์ฆ๋Œ€๋˜๋Š” ๊ณต๋ฒ•๊ด€๊ณ„์—์„œ์˜ ๊ถŒ๋ฆฌ๋ณดํ˜ธ ์š”๊ตฌ์— ๋Œ€ํ•˜์—ฌ ํ–‰์ •์žฌ๋Ÿ‰์— ๋Œ€ํ•œ ์‚ฌ๋ฒ•ํ†ต์ œ๊ฐ€ ๊ฐ•ํ™”๋˜์–ด์•ผ ํ•œ๋‹ค๊ณ  ์ฃผ์žฅํ•˜์˜€๋‹ค. ํ…Œ์ธ ๋„ˆ๋Š” ์ด๋Ÿฌํ•œ ๋ชฉ์ ์„ ๋‹ฌ์„ฑํ•˜๊ธฐ ์œ„ํ•ด ๋ฒ•๋ฅ ์š”๊ฑด์— ๋Œ€ํ•œ ํ–‰์ •์žฌํŒ๊ด€์˜ ๊ด‘๋ฒ”์œ„ํ•œ ์‚ฌ๋ฒ•์‹ฌ์‚ฌ๋ฅผ ์ฃผ์žฅํ•˜๋ฉด์„œ ๋ฒ•๋ฅ ์š”๊ฑด์—์„œ์˜ ์žฌ๋Ÿ‰์„ ๋ถ€์ •ํ•˜์˜€๊ณ , ๋Œ€์‹  ๋ฒ•๋ฅ ํšจ๊ณผ ์„ ํƒ์˜ ์ž์œ ๋ฅผ ์žฌ๋Ÿ‰์˜ ๋ณธ์งˆ๋กœ ๋ณด๋Š” ํšจ๊ณผ์žฌ๋Ÿ‰์ด๋ก ์„ ์ œ์‹œํ•˜๊ฒŒ ๋œ ๊ฒƒ์ด๋‹ค. ์ œ4์žฅ์—์„œ๋Š” ํšจ๊ณผ์žฌ๋Ÿ‰์ด๋ก ์„ ๋ณด๋‹ค ์ฒด๊ณ„ํ™”ํ•˜๊ณ  ๋ฐœ์ „์‹œํ‚จ ๋ผ์šด(v. Laun)์˜ ๊ฒฌํ•ด๋ฅผ ๊ฒ€ํ† ํ•œ๋‹ค. ์ข…๋ž˜ ์žฌ๋Ÿ‰์˜ ํ–‰์‚ฌ๋ฅผ ๋ฒ•์ ์šฉ์œผ๋กœ ๋ณด์•˜๋˜ ๋ฒ ๋ฅด๋‚˜์น˜ํฌ์™€ ํ…Œ์ธ ๋„ˆ์˜ ๊ฒฌํ•ด์—์„œ ๋ฒ—์–ด๋‚˜ ์žฌ๋Ÿ‰์˜ ํ–‰์‚ฌ๋ฅผ ์ •์น˜์ โ€คํ–‰์ •ํŽธ์˜์ ์ธ ํ•ฉ๋ชฉ์ ์„ฑ ํŒ๋‹จ์œผ๋กœ ๋ณด์•˜๋˜ ๋ผ์šด์€, ์žฌ๋Ÿ‰์˜ ๋ณธ์งˆ์„ ์ž…๋ฒ•์ž์˜ ์˜ํ–ฅ์„ ๋ฐ›์ง€ ์•Š๊ณ  ํ–‰์œ„๋ชฉ์ ์„ ์„ ํƒํ•  ์ˆ˜ ์žˆ๋Š” ์ž์œ ๋กœ ํŒŒ์•…ํ•˜์˜€๋‹ค. ํ•œํŽธ ๊ทธ์˜ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์€ ํŠนํžˆ ๋…์ผ์— ๋น„ํ•ด ์ƒ๋Œ€์ ์œผ๋กœ ํ–‰์ •๋ฒ•์˜ ๋ฐœ์ „์ด ์•ž์„ฐ๋˜ ํ”„๋ž‘์Šค์˜ ์˜ˆ๋ฅผ ๋ชจ๋ฒ”์œผ๋กœ ์žฌ๋Ÿ‰์˜ ํ•œ๊ณ„(Grenze)๋ฅผ ์ฒด๊ณ„ํ™”ํ•˜๋Š” ํ•œํŽธ, ๊ธฐ์†์žฌ๋Ÿ‰์˜ ๊ฐœ๋…์„ ๋„์ž…ํ•˜์—ฌ ํ–‰์ •์žฌ๋Ÿ‰์— ๋Œ€ํ•œ ์‚ฌ๋ฒ•์‹ฌ์‚ฌ์˜ ํ™•๋Œ€๋ฅผ ์ถ”๊ตฌํ•˜์˜€๋‹ค๋Š” ์ ์—์„œ ๊ทธ ์˜์˜๊ฐ€ ์žˆ๋‹ค. ์ œ5์žฅ์—์„œ๋Š” ๋ฒ•๋ฅ ์ด ์˜๋„ํ•œ ๋‹ค์˜์„ฑ(Mehrdeutigkeit)์„ ์žฌ๋Ÿ‰์˜ ๋ณธ์งˆ๋กœ ๋ณด๋ฉด์„œ ์ถ”์ƒ์ โ€ค๋ถˆํ™•์ • ๊ฐœ๋…์— ๋Œ€ํ•ด ๋‚ ์นด๋กœ์šด ์–ธ์–ดํ•™์  ๊ณ ์ฐฐ์„ ์‹œ๋„ํ–ˆ๋˜ ๋ฐœํ„ฐโ€ค์˜๋ฆฌ๋„คํฌ(W. Jellinek)์˜ ์ด๋ก ์„ ๊ฒ€ํ† ํ•œ๋‹ค. ๊ทธ๋Š” ์ž…๋ฒ•์ž๊ฐ€ ๋ฒ•๋ฅ ๊ทœ์ •์— ์–ธ์–ด์ ์œผ๋กœ ๋ชจํ˜ธํ•œ ํ‘œํ˜„์„ ์˜๋„์ ์œผ๋กœ ์‚ฌ์šฉํ•œ ๊ฒฝ์šฐ์—๋Š”, ๊ทธ๋Ÿฌํ•œ ๋ชจํ˜ธํ•œ ํ‘œํ˜„์ด ๋ฒ•๋ฅ ์š”๊ฑด ์ธก๋ฉด์—์„œ ์‚ฌ์šฉ๋˜๋“ ์ง€ ๋ฒ•๋ฅ ํšจ๊ณผ์˜ ์ธก๋ฉด์—์„œ ์‚ฌ์šฉ๋˜๋“ ์ง€ ๊ฐ„์— ์–‘์ž์—์„œ ๋ชจ๋‘ ์žฌ๋Ÿ‰์ด ์„ฑ๋ฆฝ๋  ์ˆ˜ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋ณด์•˜๋‹ค. ์ด๋Ÿฌํ•œ ์˜๋ฆฌ๋„คํฌ์˜ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์€ ์ผ๊ฒฌ ์žฌ๋Ÿ‰์˜ ์ธ์ •๋ฒ”์œ„๋ฅผ ๋„“ํ˜€ ๊ถŒ๋ฆฌ๊ตฌ์ œ์— ์†Œํ™€ํ•œ ๊ฒƒ์œผ๋กœ ๋น„์ถฐ์งˆ ์ˆ˜๋„ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ทธ๋Š” ํ•œํŽธ์œผ๋กœ๋Š” ๋ฒ•๋ฅ ์š”๊ฑด์— ์žˆ์–ด์„œ ๋ฒ•๋ฅ ํ•ด์„์— ์˜ํ•ด ์ผ์˜์ ์œผ๋กœ ํ™•์ • ๊ฐ€๋Šฅํ•œ ๋ถˆํ™•์ •๊ฐœ๋…์€ ์žฌ๋Ÿ‰์œผ๋กœ ์Šน์ธํ•˜์ง€ ์•Š์•˜๊ณ , ๋‹ค๋ฅธ ํ•œํŽธ์œผ๋กœ๋Š” ๊ด‘๋ฒ”์œ„ํ•œ ์žฌ๋Ÿ‰ํ•˜์ž๋ฅผ ์ธ์ •ํ•จ์œผ๋กœ์จ ์žฌ๋Ÿ‰์— ๋Œ€ํ•˜์—ฌ ์‹ค์งˆ์ ์ธ ์‚ฌ๋ฒ•ํ†ต์ œ์˜ ํ™•๋Œ€๋ฅผ ์‹œ๋„ํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ์ œ6์žฅ์—์„œ๋Š” ๋จผ์ € ๊ฐ ์ด๋ก ์— ๋Œ€ํ•˜์—ฌ ์ข…ํ•ฉ์ ์œผ๋กœ ๋ถ„์„ํ•˜๊ณ , ๋…ผ์˜ ๊ฒฐ๊ณผ๋ฅผ ์ •๋ฆฌํ•œ๋‹ค. ๋‹ค์Œ์œผ๋กœ ์šฐ๋ฆฌ๋‚˜๋ผ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์˜ ํ˜„ํ™ฉ๊ณผ ๋ฌธ์ œ์ ์„ ์‚ดํŽด๋ณด๊ณ  ์ด๋ก ๊ณผ ์‹ค๋ฌด์˜ ์กฐํ™”์ ์„ ์ฐพ์•„๋ณธ๋‹ค. ๋‚˜์•„๊ฐ€ ์•ž์„œ ์ •๋ฆฌํ•œ ๋ฐ”์™€ ๊ฐ™์ด ๋…์ผ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์˜ ํ˜•์„ฑ๊ธฐ์  ๋…ผ์˜๊ฐ€ ํ˜„์žฌ์˜ ์šฐ๋ฆฌ๋‚˜๋ผ์˜ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์˜ ๋ฌธ์ œํ•ด๊ฒฐ์— ์–ด๋– ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น  ์ˆ˜ ์žˆ๊ณ , ํ–ฅํ›„ ์šฐ๋ฆฌ์˜ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์˜ ๋ฐœ์ „์„ ์œ„ํ•ด ์–ด๋– ํ•œ ์˜๋ฏธ์™€ ๊ธฐ๋Šฅ์„ ๊ฐ€์ง€๊ณ  ์‹œ์‚ฌ์ ์„ ์ œ๊ณตํ•ด ์ค„ ์ˆ˜ ์žˆ์„ ๊ฒƒ์ธ์ง€๋ฅผ ์ƒ๊ฐํ•ด ๋ณด๊ณ ์ž ํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ๋…์ผ์˜ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์ด ์ฒด๊ณ„ํ™”๋˜๊ธฐ ์‹œ์ž‘ํ•œ 19์„ธ๊ธฐ ํ›„๋ฐ˜ ์ž…ํ—Œ๊ตฐ์ฃผ์ œ ์‹œ๋Œ€์˜ ๋ฒ ๋ฅด๋‚˜์น˜ํฌ(Bernatzik)์˜ ์š”๊ฑด์žฌ๋Ÿ‰์ด๋ก ๊ณผ 20์„ธ๊ธฐ ์ดˆ ํ…Œ์ธ ๋„ˆ(Tezner)์˜ ํšจ๊ณผ์žฌ๋Ÿ‰์ด๋ก ์˜ ๋Œ€๋ฆฝ์—์„œ๋ถ€ํ„ฐ, 20์„ธ๊ธฐ ์ดˆ ๋ฐ”์ด๋งˆ๋ฅด ๊ณตํ™”๊ตญ ์‹œ๋Œ€์˜ ์ด๋ก ์ธ ๋ผ์šด(v. Laun)๊ณผ ๋ฐœํ„ฐโ€ค์˜๋ฆฌ๋„คํฌ(W. Jellinek)์˜ ๊ฐ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์— ์ด๋ฅด๊ธฐ๊นŒ์ง€, ๋…์ผ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์˜ ๋ฟŒ๋ฆฌ์ด์ž ํ˜•์„ฑ ๊ณผ์ •์˜ ํ•ต์‹ฌ์ด๋ผ๊ณ  ํ•  ์ˆ˜ ์žˆ๋Š” ์ฃผ์š” ์ด๋ก ์— ๊ทธ ์—ฐ๊ตฌ๋ฒ”์œ„๋ฅผ ํ•œ์ •ํ•˜์˜€๋‹ค. ์ด ์‹œ๊ธฐ์—๋Š” ์•„์ง ์žฌ๋Ÿ‰ํ–‰์œ„์™€ ๊ธฐ์†ํ–‰์œ„์˜ ๊ตฌ๋ณ„ ๋ฌธ์ œ๊ฐ€ ํ–‰์ •์†Œ์†ก์˜ ๋Œ€์ƒ์ ๊ฒฉ ๋ฌธ์ œ์— ๋จธ๋ฌผ๋ €๋‹ค. ์ฆ‰, ๊ธฐ์†ํ–‰์œ„๋งŒ์ด ํ–‰์ •์žฌํŒ์†Œ์˜ ์‹ฌ์‚ฌ๋Œ€์ƒ์ด ๋˜์—ˆ๊ณ , ์žฌ๋Ÿ‰ํ–‰์œ„์˜ ๊ฒฝ์šฐ์—๋Š” ๋ช…๋ฌธ์˜ ๋ฒ•๋ฅ ๊ทœ์ • ๋˜๋Š” ์žฌํŒ์‹ค๋ฌด์— ์˜ํ•ด ์†Œ์†ก๋Œ€์ƒ์—์„œ ์ œ์™ธ๋˜์—ˆ๋˜ ๊ฒƒ์ด๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ œ2์ฐจ ์„ธ๊ณ„๋Œ€์ „ ์ดํ›„ ๋…์ผ ์—ฐ๋ฐฉ ํ–‰์ •์žฌํŒ์†Œ๋ฒ• ์ œ114์กฐ ์ œ1๋ฌธ์—์„œ ์žฌ๋Ÿ‰ํ–‰์œ„์— ์žฌ๋Ÿ‰๊ถŒ์˜ ์ผํƒˆโ€ค๋‚จ์šฉ์ด ์žˆ์œผ๋ฉด ์œ„๋ฒ•์„ฑ์ด ์ธ์ •๋˜์–ด ์Ÿ์†ก์ทจ์†Œ๊ฐ€ ๋  ์ˆ˜ ์žˆ์Œ์ด ๋ช…๋ฌธํ™”๋˜๋ฉด์„œ ์ด์ œ ์žฌ๋Ÿ‰์˜ ๋ฌธ์ œ๋Š” ๋ณธ์•ˆ์‹ฌ์‚ฌ์˜ ๋ฐฉ๋ฒ• ๋‚ด์ง€ ์‹ฌ์‚ฌ๊ฐ•๋„์˜ ๋ฌธ์ œ๊ฐ€ ๋˜์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๊ฐ€ ๋…์ผ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์˜ ํ˜•์„ฑ๊ธฐ์— ์žˆ์—ˆ๋˜ ์žฌ๋Ÿ‰์˜ ๋ณธ์งˆ์— ๊ด€ํ•œ ๋…ผ์˜์— ์ดˆ์ ์„ ๋งž์ถ”๊ธฐ๋กœ ํ•œ ์ด์ƒ, ํšจ๊ณผ์žฌ๋Ÿ‰์ด๋ก ์ด ํ†ต์„ค์ด ๋˜๊ณ  ์žฌ๋Ÿ‰์ด ์‹ฌ์‚ฌ๊ฐ•๋„์˜ ๋ฌธ์ œ๋กœ ์ „ํ™”(่ฝ‰ๅŒ–)๋œ ์ œ2์ฐจ ์„ธ๊ณ„๋Œ€์ „ ์ดํ›„์˜ ๋…ผ์˜๋Š” ๋ณธ ์—ฐ๊ตฌ์˜ ๋…ผ์˜ ๋Œ€์ƒ์—์„œ ์ œ์™ธํ•˜๊ธฐ๋กœ ํ•œ๋‹ค. ๋ฒ ๋ฅด๋‚˜์น˜ํฌ, ํ…Œ์ธ ๋„ˆ, ๋ผ์šด, ์˜๋ฆฌ๋„คํฌ์˜ ๊ฐ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์„ ์—ฐ๊ตฌํ•œ ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด ๋‹ค์Œ๊ณผ ๊ฐ™์€ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์˜ ๋ณ€์ฒœ ๋‚ด์šฉ์„ ๋„์ถœํ•  ์ˆ˜ ์žˆ๋‹ค. ์ฒซ์งธ๋กœ, ์žฌ๋Ÿ‰์˜ ํ–‰์‚ฌ๋ฅผ ๋ฐ”๋ผ๋ณด๋Š” ์‹œ๊ฐ์ด ๋ณ€ํ™”ํ•˜์˜€๋‹ค. ๋ฒ ๋ฅด๋‚˜์น˜ํฌ์™€ ํ…Œ์ธ ๋„ˆ๋Š” ์žฌ๋Ÿ‰์˜ ํ–‰์‚ฌ๋ฅผ ๋ชจ๋‘ ๋ฒ•์งˆ์„œ์˜ ์ง€๋ฐฐ๋ฅผ ๋ฐ›๋Š” ๋ฒ•์ ์šฉ์œผ๋กœ ๋ณด์•˜์œผ๋‚˜, ๋ผ์šด๊ณผ ์˜๋ฆฌ๋„คํฌ๋Š” ์žฌ๋Ÿ‰์˜ ํ–‰์‚ฌ๋ฅผ ์ •์น˜์ โ€คํ–‰์ •์  ํŽธ์˜์— ์˜ํ•ด ์ง€๋ฐฐ๋˜๋Š” ํ•ฉ๋ชฉ์ ์„ฑ ํŒ๋‹จ์œผ๋กœ ํŒŒ์•…ํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ๋‘˜์งธ๋กœ, ํ–‰์ •์ฒญ์ด ๋ฒ•๋ฅ ์š”๊ฑด์—์„œ ์‚ฌ์šฉ๋œ ์ถ”์ƒ์ โ€ค๋ถˆํ™•์ • ๊ฐœ๋…์„ ๊ตฌ์ฒดํ™” ํ•  ์ˆ˜ ์žˆ๋Š” ๊ถŒ๋Šฅ์„ ์ฒ˜์Œ์—๋Š” ์žฌ๋Ÿ‰์˜ ๋ฌธ์ œ๋กœ ๋ณด์•„ ์š”๊ฑด์žฌ๋Ÿ‰์ด๋ก ์ด ์„ฑ๋ฆฝ๋˜์—ˆ์œผ๋‚˜, ์ ์ฐจ ํšจ๊ณผ์žฌ๋Ÿ‰์ด๋ก ์ด ๋“์„ธํ•˜๋ฉด์„œ ์ด๋Š” ๋ฒ•๋ฅ ํ•ด์„์˜ ๋ฌธ์ œ๋กœ ์ทจ๊ธ‰๋˜์—ˆ๋‹ค. ์…‹์งธ๋กœ, ์ด๋Ÿฌํ•œ ๋ฒ•๋ฅ ์š”๊ฑด์—์„œ์˜ ํ•ด์„ ๊ธฐ๋Šฅ์˜ ํ™•๋Œ€์— ๋”ฐ๋ผ ์žฌ๋Ÿ‰์˜ ์ธ์ •์˜์—ญ์ด ๋ฒ•๋ฅ ์š”๊ฑด์—์„œ ๋ฒ•๋ฅ ํšจ๊ณผ๋กœ ์ด๋™ํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ์–ด๋– ํ•œ ๊ฒฝ์šฐ์— ์žฌ๋Ÿ‰์ด ์„ฑ๋ฆฝ๋˜๋Š” ๊ฒƒ์œผ๋กœ ๋ณผ ๊ฒƒ์ธ๊ฐ€๋ผ๋Š” ์žฌ๋Ÿ‰์˜ ์ธ์ •์˜์—ญ์˜ ๋ฌธ์ œ๋Š” ๋ฒ ๋ฅด๋‚˜์น˜ํฌ์™€ ํ…Œ์ธ ๋„ˆ์˜ ์žฌ๋Ÿ‰์— ๊ด€ํ•œ ๋…ผ์Ÿ์—์„œ ๋‘๋“œ๋Ÿฌ์กŒ๋‹ค. ๋ฒ ๋ฅด๋‚˜์น˜ํฌ๋Š” ์ž…๋ฒ•์ž๊ฐ€ ๋ฒ•๋ฅ ์š”๊ฑด์— ์ถ”์ƒ์ โ€ค๋ถˆํ™•์ • ๊ฐœ๋…์„ ์‚ฌ์šฉํ•˜๋ฉด์„œ ํ–‰์ •์ฒญ์œผ๋กœ ํ•˜์—ฌ๊ธˆ ์ด๋ฅผ ๊ตฌ์ฒดํ™”ํ•  ์ˆ˜ ์žˆ๋„๋ก ์ˆ˜๊ถŒ์„ ํ•œ ๊ฒฝ์šฐ์— ์žฌ๋Ÿ‰์ด ์„ฑ๋ฆฝ๋œ๋‹ค๊ณ  ๋ณธ ๋ฐ˜๋ฉด, ํ…Œ์ธ ๋„ˆ๋Š” ๋ฒ•๋ฅ ์š”๊ฑด์—์„œ์˜ ๋ถˆํ™•์ •๊ฐœ๋…์˜ ๊ตฌ์ฒดํ™”๋Š” ๋ฒ•ํ•ด์„์˜ ๋ฌธ์ œ๋กœ์„œ ํ–‰์ •์ฒญ์˜ ์žฌ๋Ÿ‰์„ ์ธ์ •ํ•  ์ˆ˜ ์—†๊ณ , ๋‹จ์ง€ ๋ฒ•๋ฅ ํšจ๊ณผ์—์„œ ํ–‰์ •์ฒญ์—๊ฒŒ ์„ ํƒ์˜ ์ž์œ ๊ฐ€ ์ฃผ์–ด์ง„ ๊ฒฝ์šฐ์— ์žฌ๋Ÿ‰์ด ์„ฑ๋ฆฝ๋œ๋‹ค๊ณ  ๋ณด์•˜๋˜ ๊ฒƒ์ด๋‹ค. ๋„ท์งธ๋กœ, ๊ตญ๊ฐ€๊ณต๊ถŒ๋ ฅ์œผ๋กœ๋ถ€ํ„ฐ ์‹œ๋ฏผ์˜ ์ž์œ ์™€ ์žฌ์‚ฐ์„ ๋ณดํ˜ธํ•ด ๋‹ฌ๋ผ๋Š” ์‹œ๋ฏผ์  ์ž์œ ์ฃผ์˜์˜ ์š”์ฒญ์€ ํ–‰์ •์žฌ๋Ÿ‰์— ๋Œ€ํ•œ ์‚ฌ๋ฒ•ํ†ต์ œ์˜ ํ™•๋Œ€ ์š”๊ตฌ๋กœ ์ด์–ด์ง€๊ฒŒ ๋˜์—ˆ๊ณ , ์ด์— ๋”ฐ๋ผ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์€ ํ•œํŽธ์œผ๋กœ๋Š” ๋ฒ•๋ฅ ์š”๊ฑด ์ธก๋ฉด์—์„œ ๋ฒ•ํ•ด์„์„ ํ†ตํ•œ ์ถ”์ƒ์ โ€ค๋ถˆํ™•์ • ๊ฐœ๋…์˜ ์ผ์˜์  ํ™•์ •๊ฐ€๋Šฅ์„ฑ์„ ๊ทผ๊ฑฐ๋กœ ํ•˜์—ฌ ์š”๊ฑด์žฌ๋Ÿ‰์˜ ์„ฑ๋ฆฝ ์—ฌ์ง€๋ฅผ ์ ์ฐจ ์ค„์—ฌ๋‚˜๊ฐ”๊ณ , ๋‹ค๋ฅธ ํ•œํŽธ์œผ๋กœ๋Š” ์žฌ๋Ÿ‰์„ ์†Œ์†ก๋Œ€์ƒ์œผ๋กœ ํฌ์ฐฉํ•  ์ˆ˜ ์žˆ๋Š” ๊ทผ๊ฑฐ๊ฐ€ ๋œ ์žฌ๋Ÿ‰ํ•˜์ž๋ก ์„ ๋ฐœ์ „์‹œํ‚ค๋Š” ๋ฐฉํ–ฅ์œผ๋กœ ๋‚˜์•„๊ฐ€๊ฒŒ ๋˜์—ˆ๋‹ค. ํ˜„์žฌ ์šฐ๋ฆฌ๋‚˜๋ผ์˜ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์€ ํšจ๊ณผ์žฌ๋Ÿ‰์ด๋ก ์ด ๋‹ค์ˆ˜์„ค๋กœ ์ •์ฐฉ๋œ ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋…์ผ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์˜ ์—ญ์‚ฌ์  ๋งฅ๋ฝ๊ณผ ๊ทธ ์ดˆ๊ธฐ ํ˜•์„ฑ๊ณผ์ •์„ ๋ถ„์„ํ•˜๊ณ  ๊ฒ€ํ† ํ•ด ๋ณด๋ฉด, ๋…์ผ์˜ ํŠน์ˆ˜ํ•œ ์—ญ์‚ฌ์  ๊ฒฝํ—˜์˜ ์‚ฐ๋ฌผ์ธ ํšจ๊ณผ์žฌ๋Ÿ‰์ด๋ก ์˜ ๋…ผ์˜๊ฐ€ ์šฐ๋ฆฌ๋‚˜๋ผ์—์„œ๋„ ๊ทธ๋Œ€๋กœ ํƒ€๋‹นํ•œ ๊ฒƒ์ธ์ง€๋Š” ๋‹ค์‹œ ํ•œ ๋ฒˆ ์ƒ๊ฐํ•ด ๋ณผ ํ•„์š”๊ฐ€ ์žˆ์Œ์„ ์•Œ ์ˆ˜ ์žˆ๋‹ค. ํŠนํžˆ ์šฐ๋ฆฌ๋‚˜๋ผ ๋Œ€๋ฒ•์› ํŒ๋ก€๋Š” ํ˜„์žฌ๊นŒ์ง€๋„ ๋ฒ•๋ฅ ํšจ๊ณผ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๋ฒ•๋ฅ ์š”๊ฑด์˜ ์ธก๋ฉด์—์„œ๋„ ์žฌ๋Ÿ‰์„ ์ธ์ •ํ•˜๊ณ  ์žˆ๋‹ค๋Š” ์ ์—์„œ๋„ ๊ทธ๋Ÿฌํ•˜๋‹ค. ๊ธ‰๋ณ€ํ•˜๋Š” ํ˜„๋Œ€์‚ฌํšŒ์˜ ์ƒˆ๋กœ์šด ์ˆ˜์š”์™€ ๋ณ€ํ™”์ƒ์— ๋Œ€์‘ํ•˜๊ธฐ ์œ„ํ•ด์„œ ํ–‰์ •์—๊ฒŒ ์žฌ๋Ÿ‰์„ ์ธ์ •ํ•˜๋Š” ๊ฒƒ์€ ํ•„์ˆ˜๋ถˆ๊ฐ€๊ฒฐํ•˜๊ณ , ๋˜ํ•œ ๊ณผ๊ฑฐ์— ๋น„ํ•ด ๋” ๊ฐ•ํ•œ ๋ฏผ์ฃผ์  ์ •๋‹น์„ฑ์„ ๊ฐ€์ง„ ํ–‰์ •์˜ ์ž์œจ์„ฑ๊ณผ ํšจ์œจ์„ฑ์ด๋ผ๋Š” ๊ฐ€์น˜ ๋˜ํ•œ ์ค‘์š”ํ•˜๋‹ค๋Š” ์ ์—์„œ๋„ ํ–‰์ •์˜ ์žฌ๋Ÿ‰์€ ์กด์ค‘๋˜์–ด์•ผ ํ•  ๊ฒƒ์ด๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์—ฌ์ „ํžˆ ํ–‰์ •์˜ ์œ„๋ฒ•ํ•œ ์žฌ๋Ÿ‰ํ–‰์œ„์— ๋Œ€ํ•œ ๊ตญ๋ฏผ์˜ ๊ถŒ์ต๋ณดํ˜ธ์—๋„ ์†Œํ™€ํ•จ์ด ์—†๋„๋ก ์žฌ๋Ÿ‰์— ๋Œ€ํ•œ ํšจ๊ณผ์ ์ธ ์‚ฌ๋ฒ•ํ†ต์ œ๊ฐ€ ๊ฐ€๋Šฅํ•ด์•ผ ํ•  ๊ฒƒ์ž„์€ ๋ฌผ๋ก ์ด๋‹ค. ๋”ฐ๋ผ์„œ ์•ž์œผ๋กœ ์–‘์ž๊ฐ€ ์กฐํ™”๋ฅผ ์ด๋ฃฐ ์ˆ˜ ์žˆ๋Š” ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์˜ ๋ฐœ์ „์ด ์š”์ฒญ๋œ๋‹ค. ๋…์ผ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์˜ ํ˜•์„ฑ๊ธฐ ๋…ผ์˜์— ๊ด€ํ•œ ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ทธ ์ž์ฒด๋กœ ๊ณผ๊ฑฐ์™€ ํ˜„์žฌ๋ฅผ ์—ฐ๊ฒฐํ•˜๋Š” ์—ญ์‚ฌ์  ๊ธฐ๋Šฅ์„ ๊ฐ€์ง„๋‹ค๊ณ  ๋ณผ ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค. ๋˜ํ•œ ํ•™์„ค๊ณผ ํŒ๋ก€ ์‚ฌ์ด์˜ ์ƒํ˜ธ ์กด์ค‘๊ณผ ์ดํ•ด๋ฅผ ํ†ตํ•œ ๋ฐœ์ „์  ์ƒ๊ด€๊ด€๊ณ„๊ฐ€ ํ˜•์„ฑ๋  ์ˆ˜ ์žˆ๊ธฐ ์œ„ํ•ด์„œ, ๋ณธ ์—ฐ๊ตฌ๊ฐ€ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์˜ ํ˜„์žฌ๋ฅผ ๋ฐ˜์„ฑํ•˜๊ณ  ๋ฏธ๋ž˜๋ฅผ ๊ณ„ํšํ•˜๋Š” ๋ฐ์— ์กฐ๊ธˆ์ด๋‚˜๋งˆ ๋ณดํƒฌ์ด ๋  ์ˆ˜ ์žˆ๊ธฐ๋ฅผ ๊ธฐ๋Œ€ํ•ด ๋ณธ๋‹ค.๊ตญ๋ฌธ ์ดˆ๋ก ์•ฝ์–ดํ‘œ(Abkรผrzungsverzeichnis) ์—ฐ๊ตฌ์˜ ๋ชฉ์  1 ์—ฐ๊ตฌ์˜ ๋ฒ”์œ„์™€ ๋ฐฉ๋ฒ• 3 ์ œ1์žฅ ์˜ˆ๋น„์  ๊ณ ์ฐฐ 7 ์ œ1์ ˆ ์„œ์„ค 7 ์ œ2์ ˆ ์žฌ๋Ÿ‰๊ฐœ๋…์˜ ๋ณ€์ฒœ 8 ์ œ3์ ˆ ์ž์œ ์žฌ๋Ÿ‰ ๋…ผ์˜์˜ ์‹œ๋ฐœ์  9 โ… . ํ–‰์ •์žฌํŒ์†Œ ์„ค๋ฆฝ ๋ฐฐ๊ฒฝ 10 โ…ก. ํƒ€ํ˜‘์˜ ์‚ฐ๋ฌผ 11 โ…ข. ์ž์œ ์žฌ๋Ÿ‰์— ๋Œ€ํ•œ ์žฌํŒ๊ด€ํ•  12 1. ์˜ค์ŠคํŠธ๋ฆฌ์•„ ๋“ฑ 12 2. ํ”„๋กœ์ด์„ผ ๋“ฑ 14 ์ œ4์ ˆ ์žฌ๋Ÿ‰์ด๋ก ์˜ ์—ญ์‚ฌ 16 โ… . ์ž…ํ—Œ๊ตฐ์ฃผ์ œ ์‹œ๋Œ€ 16 โ…ก. ๋ฐ”์ด๋งˆ๋ฅด ๊ณตํ™”๊ตญ 20 โ…ข. ๋‚˜์น˜ ์‹œ๋Œ€ 23 โ…ฃ. ์ œ2์ฐจ ์„ธ๊ณ„๋Œ€์ „ ์ดํ›„ 25 ์ œ5์ ˆ ์†Œ๊ฒฐ 30 ์ œ2์žฅ ์š”๊ฑด์žฌ๋Ÿ‰์ด๋ก ์˜ ์ •๋ฆฝ: ๋ฒ ๋ฅด๋‚˜์น˜ํฌ(Bernatzik) โ€• ๋ฒ•๋ฅ ์š”๊ฑด์— ๋Œ€ํ•œ ์ œ3์ž์˜ ์‹ฌ์‚ฌ๋ถˆ๊ฐ€๋Šฅ์„ฑ์œผ๋กœ์„œ์˜ ์žฌ๋Ÿ‰ โ€• 34 ์ œ1์ ˆ ๋ฒ ๋ฅด๋‚˜์น˜ํฌ์˜ ์ƒ์•  34 ์ œ2์ ˆ ์ด๋ก ์˜ ์ฃผ์š” ๋‚ด์šฉ 35 โ… . ์ž์œ ์žฌ๋Ÿ‰์˜ ์˜์˜ 35 1. ํ–‰์ •์žฌ๋Ÿ‰๊ณผ ์‚ฌ๋ฒ•์žฌ๋Ÿ‰ 35 2. ์ž์œ ์žฌ๋Ÿ‰์˜ ์ด์ค‘์  ์˜๋ฏธ 37 3. ์ž์œ ์žฌ๋Ÿ‰๊ณผ ๊ฐœ์ธ์˜ ์ž์œ  38 4. ๊ธฐ์ˆ ์  ์žฌ๋Ÿ‰(technisches Ermessen)์˜ ์ œ์•ˆ 40 โ…ก. ์ž์œ ์žฌ๋Ÿ‰๊ณผ ์‚ฌ๋ฒ•ํ†ต์ œ 41 1. ์ž์œ ์žฌ๋Ÿ‰๊ณผ ๋ฒ•๊ธฐ์†์˜ ๊ด€๊ณ„ 41 2. ์žฌ๋Ÿ‰์ด ์ธ์ •๋˜๋Š” ๊ฒฝ์šฐ 44 3. ์žฌ๋Ÿ‰์— ๋Œ€ํ•œ ์‚ฌ๋ฒ•ํ†ต์ œ ๊ฐ€๋Šฅ์„ฑ 47 4. ํ–‰์ •์˜ ๋ฒ•์ ์šฉ๊ณผ ์‚ฌ๋ฒ•(ๅธๆณ•)์ž‘์šฉ์˜ ๋น„๊ต 49 5. ํ–‰์ •์žฌํŒ์†Œ์˜ ์žฌ๋Ÿ‰ํ†ต์ œ์— ๊ด€ํ•œ ์ž…๋ฒ•๋ก  50 ์ œ3์ ˆ ๋ถ„์„๊ณผ ์˜ํ–ฅ 51 โ… . ์ด๋ก ์— ๋Œ€ํ•œ ๋น„ํŒ 51 1. ๋น„ํŒ์˜ ์š”์ง€ 51 2. ๊ฒ€ํ†  53 โ…ก. ๋ฒ ๋ฅด๋‚˜์น˜ํฌ์˜ ์š”๊ฑด์žฌ๋Ÿ‰์ด๋ก ์˜ ๊ฐ€์น˜์™€ ์˜ํ–ฅ 54 1. ์˜๋ฌด์— ํ•ฉ๋‹นํ•œ(pflichtmรครŸig) ์žฌ๋Ÿ‰์˜ ์ œ์‹œ 54 2. ๋ฒ•ํ•™์  ๋…ผ์ฆ ๋ฐฉ๋ฒ• ๋„์ž… 55 3. ํ›„์„ธ์˜ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์— ๋Œ€ํ•œ ์˜ํ–ฅ 57 ์ œ3์žฅ ํšจ๊ณผ์žฌ๋Ÿ‰์ด๋ก ์˜ ๋“ฑ์žฅ: ํ…Œ์ธ ๋„ˆ(Tezner)โ€• ๋ฒ•๋ฅ ํšจ๊ณผ ์„ ํƒ์˜ ์ž์œ ๋กœ์„œ์˜ ์žฌ๋Ÿ‰ โ€• 59 ์ œ1์ ˆ ํ…Œ์ธ ๋„ˆ์˜ ์ƒ์•  59 ์ œ2์ ˆ ์ด๋ก ์˜ ์ฃผ์š” ๋‚ด์šฉ 59 โ… . ์žฌํŒ๊ด€์˜ ๋ฒ•๋ฅ ์š”๊ฑด์˜ ํ•ด์„โ€ค์ ์šฉ ์˜๋ฌด 59 1. ์ „ํ†ต์  ์ž„๋ฌด์ธ ๋ฒ•ํ•ด์„๊ณผ ๋ฒ•์ ์šฉ 60 2. ๋ฒ•๊ฐœ๋…์œผ๋กœ์„œ์˜ ๋ถˆํ™•์ •๊ฐœ๋… 61 3. ์žฌํŒ๊ด€์˜ ์—ญํ•  62 โ…ก. ๋ฒ•๋ฅ ํšจ๊ณผ ์„ ํƒ์˜ ์ž์œ ๋กœ์„œ์˜ ์žฌ๋Ÿ‰ 64 1. ์žฌ๋Ÿ‰์— ๋Œ€ํ•œ ๋ฒ•์  ์ œํ•œ 64 2. ์žฌ๋Ÿ‰์˜ ์ธ์ •์˜์—ญ์˜ ์ˆ˜์ • 67 3. ๊ฐ๊ด€์  ๋ฒ•์œ„๋ฐ˜์˜ ํ•˜์ž 73 4. ์‹ฌ์‚ฌ๊ฐ•๋„ 74 5. ํ–‰์ •์ ˆ์ฐจ 76 ์ œ3์ ˆ ๋ถ„์„๊ณผ ์˜ํ–ฅ 77 โ… . ์ด๋ก ์— ๋Œ€ํ•œ ๋น„ํŒ 77 1. ๋น„ํŒ์˜ ์š”์ง€ 78 2. ๊ฒ€ํ†  78 โ…ก. ํ…Œ์ธ ๋„ˆ์˜ ํšจ๊ณผ์žฌ๋Ÿ‰์ด๋ก ์˜ ๊ฐ€์น˜์™€ ์˜ํ–ฅ 80 1. ํ–‰์ •์žฌํŒ๊ถŒ์˜ ๊ด€ํ•  ํ™•์žฅ 80 2. ๋ฒ•๋ฅ ํšจ๊ณผ๋กœ์˜ ์ค‘์‹ฌ์ถ• ์ด๋™ 80 3. ์‹ค๋ฌด์ โ€ค์†Œ์†ก๋ฒ•์  ์ ‘๊ทผ๋ฐฉ๋ฒ• 82 4. ์ด์ƒ์ ์ธ ํ–‰์ •์žฌํŒ๊ด€ 83 5. ํ›„์„ธ์˜ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์— ๋Œ€ํ•œ ์˜ํ–ฅ 83 ์ œ4์žฅ ํšจ๊ณผ์žฌ๋Ÿ‰์ด๋ก ์˜ ์ฒด๊ณ„ํ™”: ๋ผ์šด(v. Laun)โ€• ๋‹ค์–‘ํ•œ ๋ชฉ์  ์„ ํƒ์˜ ์ž์œ ๋กœ์„œ์˜ ์žฌ๋Ÿ‰ โ€• 86 ์ œ1์ ˆ ๋ผ์šด์˜ ์ƒ์•  86 ์ œ2์ ˆ ์ด๋ก ์˜ ์ฃผ์š” ๋‚ด์šฉ 86 โ… . ์ž์œ ์žฌ๋Ÿ‰๊ณผ ๋ฒ•์ ์šฉ์˜ ์—„๋ณ„ 86 1. ํ–‰์ •๊ธฐ๊ด€์˜ ํ–‰ํƒœ 87 2. ์ž์œ ์žฌ๋Ÿ‰๊ณผ ๋ฒ•์ ์šฉ 87 โ…ก. ๊ธฐ์†์žฌ๋Ÿ‰(gebundenes Ermessen)์˜ ๋„์ž… 89 1. ๊ธฐ์†๊ณผ ์žฌ๋Ÿ‰์˜ ๊ตฌ๋ณ„ 89 2. ๊ธฐ์†์žฌ๋Ÿ‰์˜ ๊ฐœ๋… 89 โ…ข. ๋ชฉ์ ์„ ํƒ(Zweckwahl)์˜ ์ž์œ ๋กœ์„œ์˜ ์žฌ๋Ÿ‰ 91 1. ์ž์œ ์žฌ๋Ÿ‰ ๋ถ€์—ฌ์˜ ๊ทผ๊ฑฐ์™€ ์ทจ์ง€ 91 2. ์ž์œ ์žฌ๋Ÿ‰์˜ ๋ณธ์งˆ๊ณผ ์ธ์ •์˜์—ญ 92 3. ๊ณต์ต์— ๋Œ€ํ•œ ์˜ˆ์™ธ์  ์ทจ๊ธ‰ 95 4. ์ƒโ€คํ•˜๊ธ‰ ํ–‰์ •์ฒญ ์‚ฌ์ด์˜ ์ž์œ ์žฌ๋Ÿ‰ 98 5. ํ˜„ํ–‰๋ฒ•์— ๋‚˜ํƒ€๋‚œ ์ž์œ ์žฌ๋Ÿ‰์˜ ํ˜•ํƒœ 98 โ…ฃ. ์ž์—ฐ์  ๋ฒ•์›์น™(natรผrliches Rechtssatz) 100 1. ์ž์œ ์žฌ๋Ÿ‰์˜ ๊ทผ๊ฑฐ๋กœ์„œ์˜ ์ž์—ฐ์  ๋ฒ•์›์น™ 100 2. ์ž์œ ์žฌ๋Ÿ‰์˜ ํ•œ๊ณ„๋กœ์„œ์˜ ์ž์—ฐ์  ๋ฒ•์›์น™ 101 โ…ค. ์ž์œ ์žฌ๋Ÿ‰์˜ ์†Œ์†ก์ƒ ๋ฌธ์ œ 102 1. ์‹ฌ์‚ฌ๋ฒ”์œ„์™€ ์†Œ์†ก์ƒ ์ทจ๊ธ‰ 102 2. ์žฌ๋Ÿ‰์‹ฌ์‚ฌ์— ์žˆ์–ด์„œ์˜ ์ž…์ฆ ๋ฌธ์ œ 103 โ…ฅ. ์ž์œ ์žฌ๋Ÿ‰์˜ ํ•œ๊ณ„ 104 1. ์™ธ๋ถ€์ โ€ค๋‚ด๋ถ€์  ํ•œ๊ณ„์˜ ๊ตฌ๋ถ„ 104 2. ์žฌ๋Ÿ‰์ผํƒˆ(Ermessensรผberschreitung) 105 ์ œ3์ ˆ ๋ถ„์„๊ณผ ์˜ํ–ฅ 107 โ… . ์ด๋ก ์— ๋Œ€ํ•œ ๋น„ํŒ 107 1. ๋น„ํŒ์˜ ์š”์ง€ 107 2. ๊ฒ€ํ†  108 โ…ก. ๋ผ์šด์˜ ์žฌ๋Ÿ‰์ด๋ก ์˜ ๊ฐ€์น˜์™€ ์˜ํ–ฅ 110 1. ์žฌ๋Ÿ‰ ๋ฒ”์œ„์˜ ์‹ค์งˆ์  ์ œํ•œ 110 2. ๊ธฐ์†์žฌ๋Ÿ‰์„ ํ†ตํ•œ ์‚ฌ๋ฒ•์‹ฌ์‚ฌ์˜ ํ™•๋Œ€ 111 3. ํ•ฉ๋ชฉ์ ์„ฑ ํŒ๋‹จ์œผ๋กœ์„œ์˜ ์žฌ๋Ÿ‰ 112 4. ๋‹ค์›์  ๋ฒ•๋น„๊ต ๋ฐฉ๋ฒ•๋ก  112 5. ํ›„์„ธ์˜ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์— ๋Œ€ํ•œ ์˜ํ–ฅ 113 ์ œ5์žฅ ํšจ๊ณผ์žฌ๋Ÿ‰์ด๋ก ์˜ ์ˆ˜์ • โ€• ์š”๊ฑด์žฌ๋Ÿ‰์˜ ์˜ˆ์™ธ์  ์ธ์ •: ๋ฐœํ„ฐโ€ค์˜๋ฆฌ๋„คํฌ(W. Jellinek)โ€• ๋ฒ•๋ฅ ์ด ์˜๋„ํ•œ ๋‹ค์˜์„ฑ์œผ๋กœ์„œ์˜ ์žฌ๋Ÿ‰ โ€• 116 ์ œ1์ ˆ ์˜๋ฆฌ๋„คํฌ์˜ ์ƒ์•  116 ์ œ2์ ˆ ์ด๋ก ์˜ ์ฃผ์š” ๋‚ด์šฉ 117 โ… . ๊ธฐ์†๊ณผ ์žฌ๋Ÿ‰์˜ ๊ตฌ๋ณ„ 117 1. ๊ธฐ์†ํ–‰์ •๊ณผ ์žฌ๋Ÿ‰ํ–‰์ • 117 2. ๊ธฐ์†ํ–‰์ •๊ณผ ์žฌ๋Ÿ‰ํ–‰์ •์˜ ๊ตฌ๋ณ„ ํ•„์š”์„ฑ 118 โ…ก. ๋ฒ•๋ฅ ์ด ์˜๋„ํ•œ ๋‹ค์˜์„ฑ์œผ๋กœ์„œ์˜ ์žฌ๋Ÿ‰ 119 1. ์ž์œ ์žฌ๋Ÿ‰์˜ ๋ณธ์งˆ๊ณผ ์ธ์ •์˜์—ญ 119 2. ์ž์œ ์žฌ๋Ÿ‰๊ณผ ๋ถˆํ™•์ •๊ฐœ๋…์˜ ๊ด€๊ณ„ 121 3. ๊ณต์ต์˜ ์ทจ๊ธ‰ 124 4. ํ•„์š”์„ฑ๊ณผ ํ•ฉ๋ชฉ์ ์„ฑ์˜ ์ทจ๊ธ‰ 125 5. ํ•  ์ˆ˜ ์žˆ๋‹ค ๊ทœ์ •(Kann-Vorschrift)์˜ ์ทจ๊ธ‰ 125 โ…ข. ์ž์œ ์žฌ๋Ÿ‰์— ๋Œ€ํ•œ ์ •์˜(ๅฎš็พฉ) 126 1. ์ •์˜ 126 2. ์š”๊ฑด๋ณ„ ์˜๋ฏธ ๋ถ„์„ 127 โ…ฃ. ๋ชฉ์ โ€ค์ˆ˜๋‹จ ์„ ํƒ์ƒ์˜ ์ž์œ ์žฌ๋Ÿ‰ 129 โ…ค. ์š”๊ฑด์žฌ๋Ÿ‰์˜ ์ธ์ • ๋ฌธ์ œ 130 โ…ฅ. ์ž์œ ์žฌ๋Ÿ‰๊ณผ ๋ฒ•์ ์šฉ ๋ฐ ๋ฒ•์งˆ์„œ์˜ ๊ด€๊ณ„ 132 1. ์ž์œ ์žฌ๋Ÿ‰๊ณผ ๋ฒ•์ ์šฉ์˜ ๋Œ€๋ฆฝ๊ด€๊ณ„ 132 2. ์ž์œ ์žฌ๋Ÿ‰์— ๋Œ€ํ•œ ๋ฒ•์งˆ์„œ์˜ ์˜๋ฏธ 133 โ…ฆ. ์žฌ๋Ÿ‰ํ•˜์ž์˜ ์œ ํ˜•ํ™” 134 1. ์žฌ๋Ÿ‰ํ•˜์ž์˜ ์˜๋ฏธ์™€ ๊ทผ๊ฑฐ 134 2. ์žฌ๋Ÿ‰ํ•˜์ž์˜ ์œ ํ˜• 136 3. ์žฌ๋Ÿ‰ํ•˜์ž๋ก ์˜ ์˜์˜ 139 ์ œ3์ ˆ ๋ถ„์„๊ณผ ์˜ํ–ฅ 140 โ… . ์ด๋ก ์— ๋Œ€ํ•œ ๋น„ํŒ 140 1. ๋น„ํŒ์˜ ์š”์ง€ 140 2. ๊ฒ€ํ†  141 โ…ก. ์˜๋ฆฌ๋„คํฌ์˜ ์žฌ๋Ÿ‰์ด๋ก ์˜ ๊ฐ€์น˜์™€ ์˜ํ–ฅ 142 1. ์žฌ๋Ÿ‰์ด๋ก ์˜ ์‹ฌํ™” 142 2. ๋ถˆํ™•์ •๊ฐœ๋…์˜ ๋ฒ”์œ„ ํ•œ์ • 143 3. ์žฌ๋Ÿ‰ํ•˜์ž๋ก ์„ ํ†ตํ•œ ์ž์œ ์žฌ๋Ÿ‰์˜ ์ถ•์†Œ 143 4. ํ›„์„ธ์˜ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์— ๋Œ€ํ•œ ์˜ํ–ฅ 144 ์ œ6์žฅ ์ข…ํ•ฉ์  ๋ถ„์„ ๋ฐ ์‹œ์‚ฌ์  146 ์ œ1์ ˆ ๋…์ผ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์˜ ํ˜•์„ฑ๊ณผ ๋ณ€์ฒœ 146 โ… . ์„œ์„ค 146 1. ์žฌ๋Ÿ‰์˜ ์œ„์ƒ ๋ณ€ํ™” 146 2. ์ž…๋ฒ•์ž์— ์˜ํ•œ ์žฌ๋Ÿ‰๋ถ€์—ฌ 147 3. ์žฌ๋Ÿ‰๊ณผ ๋ฒ•์ ์šฉ์˜ ๊ด€๊ณ„ 149 โ…ก. ์žฌ๋Ÿ‰์˜ ๋ณธ์งˆ๊ณผ ์ฐฉ์•ˆ์  149 1. ํ•™์ž๋ณ„ ์ฃผ์žฅ๊ณผ ๊ทผ๊ฑฐ 149 2. ๋ถ„์„ ๋ฐ ๊ฒ€ํ†  152 โ…ข. ์žฌ๋Ÿ‰์˜ ์ธ์ •์˜์—ญ๊ณผ ์žฌ๋Ÿ‰์˜ ์œ ํ˜• 152 1. ์žฌ๋Ÿ‰์˜ ์ธ์ •์˜์—ญ 152 2. ๋ถˆํ™•์ •๊ฐœ๋…์˜ ์ทจ๊ธ‰ 156 3. ๋ถ„์„ ๋ฐ ๊ฒ€ํ†  158 โ…ฃ. ์žฌ๋Ÿ‰์˜ ์ธ์ • ๋ฒ”์œ„ 158 โ…ค. ์žฌ๋Ÿ‰์— ๋Œ€ํ•œ ์‚ฌ๋ฒ•ํ†ต์ œ ๊ฐ€๋Šฅ์„ฑ๊ณผ ์žฌ๋Ÿ‰ํ•˜์ž 160 1. ํ•™์ž๋ณ„ ์ฃผ์žฅ๊ณผ ๊ทผ๊ฑฐ 160 2. ๋ถ„์„ ๋ฐ ๊ฒ€ํ†  161 โ…ฅ. ์†Œ๊ฒฐ 162 1. ๊ฐ ํ•™์„ค์˜ ํ•™๋ฌธ์  ์˜์˜ 162 2. ๋…์ผ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ์˜ ๋ณ€์ฒœ ๋ฐฉํ–ฅ 165 3. ๋…ผ์˜์˜ ํ•œ๊ณ„ 166 ์ œ2์ ˆ ์šฐ๋ฆฌ๋‚˜๋ผ ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก ๊ณผ ํŒ๋ก€ 167 โ… . ํ•™์„ค์˜ ํ˜„ํ™ฉ 168 1. ์ „ํ†ต์  ์žฌ๋Ÿ‰ํ–‰์œ„ ์ด๋ก  168 2. ๋ณ€ํ™”์˜ ์‹œ๋„ 177 3. ๊ฒ€ํ†  178 โ…ก. ์šฐ๋ฆฌ๋‚˜๋ผ ํŒ๋ก€์˜ ํƒœ๋„ 180 1. ๊ธฐ์†๊ณผ ์žฌ๋Ÿ‰์˜ ๊ตฌ๋ณ„๊ธฐ์ค€ 180 2. ๊ธฐ์†์žฌ๋Ÿ‰์˜ ์ทจ๊ธ‰ 181 3. ์š”๊ฑด์žฌ๋Ÿ‰์˜ ์ธ์ • 185 4. ์žฌ๋Ÿ‰ํ–‰์œ„ ์‚ฌ๋ก€ 186 5. ๊ฒ€ํ†  188 ์ œ3์ ˆ ์‹œ์‚ฌ์  191 โ… . ์—ญ์‚ฌ์  ๊ด€์  191 โ…ก. ๋ฐ˜์„ฑ์  ๊ด€์  193 โ…ข. ๊ฑด์„ค์  ๊ด€์  196 ์ฐธ๊ณ ๋ฌธํ—Œ 200 Zusammenfassung 206Docto

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