117 research outputs found

    ๋Œ€์กฐ ํ‘œํ˜„ ํ•™์Šต์—์„œ ์ƒํ˜ธ ์ •๋ณด์˜ ์ดํ•ด

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์œตํ•ฉ๊ณผํ•™๊ธฐ์ˆ ๋Œ€ํ•™์› ์œตํ•ฉ๊ณผํ•™๋ถ€(๋””์ง€ํ„ธ์ •๋ณด์œตํ•ฉ์ „๊ณต), 2023. 2. Wonjong Rhee.Contrastive learning has played a pivotal role in the recent success of unsupervised representation learning. It has been commonly explained with instance discrimination and a mutual information loss, and some of the fundamental explanations are based on mutual information analysis. An analysis based on mutual information, however, can be misleading. First of all, an exact quantification of mutual information over a real-world dataset is challenging. It has not been solved because we cannot access the true joint distribution function of real-world dataset before. Second, previous studies have equated the limitations of contrastive learning with them of mutual information estimation in the absence of the rigorous investigation for a relationship between them. Third, what information is actually being shared by the two views is overlooked. Without carefully examining what information is actually being shared, the interpretation can be completely misleading. In this work, we develop new methods that enable rigorous analysis of mutual information in contrastive learning. We also evaluate the accuracy of variational MI estimators across various data domains, including images and texts. Using the methods, we investigate three existing beliefs and show that they are incorrect. Based on the investigation results, we address two issues in the discussion section. In particular, we question if contrastive learning is indeed an unsupervised representation learning method because the current framework of contrastive learning relies on validation performance for tuning the augmentation design.Chapter 1. Introduction 1 1.1 Contributions 6 Chapter 2. Background 9 2.1 Contrastive representation learning 9 2.1.1 Previous works to understand contrastive learning 11 2.2 Mutual Information 12 2.3 Variational Mutual Information Estimators 15 2.3.1 Critic function 18 2.3.2 Limitations of the variational MI estimators 19 Chapter 3. Same-class Sampling for Positive Pairing 21 Chapter 4. Understanding the Accuracy of Variational Mutual Information Estimators 27 4.1 Datasets 29 4.1.1 Gaussian dataset 30 4.1.2 Definitions of ds, dr, and Z 30 4.1.3 Details of generating datasets 31 4.2 Experimental setup 33 4.3 Experimental results 34 4.3.1 Critic architecture 34 4.3.2 Critic capacity 38 4.3.3 Choice of the variational MI estimator 39 4.3.4 Number of information sources 39 4.3.5 Representation dimension 40 4.3.6 Nuisance 41 4.3.7 Deep representations 41 4.4 Discussion: How can we make use of MI with practical datasets? 44 4.5 Conclusion 48 Chapter 5. Examining Three Existing Beliefs on Mutual Information in Contrastive Learning 49 5.1 Method 50 5.1.1 Post-training MI estimation 50 5.1.2 CDP dataset 52 5.2 Experimental setups 56 5.2.1 Training 56 5.2.2 Post-training MI estimation 57 5.3 Results 59 5.3.1 A small batch size is a limiting factor for MI estimation but not for contrastive learning. 59 5.3.2 Augmentation-based MI and other metrics are not effective, but MI class is effective. 62 5.3.3 Minimizing task-irrelevant information (InfoMin) is not always necessary. 70 5.4 Discussion 77 5.5 Conclusion 83 Chapter 6. Conclusion 84 6.1 Limitations 86 6.2 Future works 86 Bibliography 88 Appendices 99๋ฐ•

    ์—ฌ๊ฐ€ํ†ต์น˜์„ฑ ์žฅ์น˜ ๊ฐœ๋…์„ ๋ฐ”ํƒ•์œผ๋กœ

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    ๋„์‹œ์— ์—ฌ๊ฐ€๊ณต๊ฐ„์ด ๊ธ‰๊ฒฉํžˆ ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๋‹ค. ํŠนํžˆ ์ง€๋ฐฉ์ž์น˜์ œ ์‹ค์‹œ ์ดํ›„ ๊ฐ ์ง€๋ฐฉ์ •๋ถ€๋Š” ์—ฌ๊ฐ€๊ณต๊ฐ„ ์กฐ์„ฑ์‚ฌ์—…์„ ์ ๊ทน ์ถ”์ง„ ์ค‘์ด๋‹ค. ์ด๋Š” ๊ณต๊ณต์ด ์ฃผ๋กœ ๊ฐœ๋ฐœ ์šฉ๋„๋กœ ํ† ์ง€์ด์šฉ์„ ๊ณ„ํšํ–ˆ๋˜ ๊ทผ๋Œ€ ํŒจ๋Ÿฌ๋‹ค์ž„๊ณผ ๋‹ค๋ฅธ ์ ์ด๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” โ€˜์™œ, ์–ด๋–ค ํ”„๋กœ์„ธ์Šค๋กœ ํ˜„๋Œ€ ์ง€๋ฐฉ์ •๋ถ€๊ฐ€ ์—ฌ๊ฐ€๊ณต๊ฐ„์„ ์กฐ์„ฑํ•˜๋Š”๊ฐ€โ€™๋ผ๋Š” ๋‘ ๊ฐ€์ง€ ์—ฐ๊ตฌ์งˆ๋ฌธ์œผ๋กœ๋ถ€ํ„ฐ ์‹œ์ž‘ํ–ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์€ ์ด ๋‘˜์„ ๋ฐํž˜์œผ๋กœ์จ ์ง€๋ฐฉ์ •๋ถ€์˜ ์—ฌ๊ฐ€๊ณต๊ฐ„ ์ƒ์‚ฐ๊ธฐ์ œ๋ฅผ ๋„์ถœํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ์ง€๋ฐฉ์ •๋ถ€๊ฐ€ ์—ฌ๊ฐ€๊ณต๊ฐ„์„ ์ƒ์‚ฐํ•˜๋Š” ๊ธฐ์ œ๋ฅผ ๋ฐํžˆ๊ธฐ ์œ„ํ•ด์„œ๋Š” ๋„์‹œ ๋‚ดยท์™ธ๋ถ€ ํ™˜๊ฒฝ ๋ฐ ํ–‰์œ„์ž, ์‚ฌํšŒ๊ตฌ์กฐ, ๊ฒฝ๊ด€ ๊ฐ„ ์ƒํ˜ธ์ž‘์šฉ์„ ์ข…ํ•ฉ์ ์œผ๋กœ ์„ค๋ช…ํ•  ์ˆ˜ ์žˆ๋Š” ์ด๋ก ํ‹€์ด ํ•„์š”ํ•˜๋‹ค๊ณ  ๋ณด์•˜๋‹ค. ์ด์— ์ฒซ์งธ, ์ง€๋ฐฉ์ •๋ถ€์˜ ๊ณต๊ฐ„์ƒ์‚ฐ โ€˜์˜๋„โ€™์— ๋Œ€ํ•ด ํ‘ธ์ฝ”์˜ ํ†ต์น˜์„ฑ(governmentality) ์ด๋ก ์„ ์ฒซ ๋ฒˆ์งธ ์—ฐ๊ตฌ๊ฐ€์„ค๋กœ ์„ค์ •ํ•ด ์ง€๋ฐฉ์ •๋ถ€๊ฐ€ ๊ณต๊ฐ„์„ ์ƒ์‚ฐํ•˜๋Š” ์˜๋„๋Š” ํ†ต์น˜์„ฑ ์ˆ˜ํ–‰์ด ์ „์ œ๋˜์–ด ์žˆ๋‹ค๊ณ  ๊ฐ€์ •ํ•˜์˜€๋‹ค. ํŠนํžˆ ์™œ โ€˜์—ฌ๊ฐ€โ€™๊ณต๊ฐ„์„ ์ƒ์‚ฐํ•˜๋Š”์ง€ ๊ทธ ์˜๋„๋ฅผ ๊ทœ๋ช…ํ•˜๊ธฐ ์œ„ํ•ด ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” โ€˜์—ฌ๊ฐ€ํ†ต์น˜์„ฑโ€™(Leisure-governmentality)์ด๋ผ๋Š” ์ƒˆ๋กœ์šด ๊ฐœ๋…์„ ์ œ์‹œํ•˜์˜€๋‹ค. ๋‘˜์งธ, ์ฒซ ๋ฒˆ์งธ ๊ฐ€์ •์„ ์ „์ œ๋กœ ์ง€๋ฐฉ์ •๋ถ€์˜ โ€˜๊ณต๊ฐ„์ƒ์‚ฐโ€™ ํ”„๋กœ์„ธ์Šค๋ฅผ ํ†ต์น˜์„ฑ โ€˜์žฅ์น˜โ€™์ธ ๊ถŒ๋ ฅ-์ง€์‹, ๋‹ด๋ก , ๊ฒฝ๊ด€์˜ ํ˜•์„ฑ๊ณผ์ •์œผ๋กœ ๋ณด์•˜๋‹ค. ์ด์— ๋ณธ ์—ฐ๊ตฌ๋ถ„์„ํ‹€๋กœ ๊ถŒ๋ ฅ-์ง€์‹, ๋‹ด๋ก , ๊ฒฝ๊ด€ ํ˜•์„ฑ๊ณผ์ •์„ ๋ถ„์„ํ•จ์œผ๋กœ์จ ๋‘ ์—ฐ๊ตฌ์งˆ๋ฌธ์„ ๊ทœ๋ช…ํ•˜๊ณ ์ž ํ–ˆ๋‹ค. ๋ถ„์„๋Œ€์ƒ์€ ์„œ์šธ์‹œ๊ฐ€ ์กฐ์„ฑํ•œ ๋„์‹œ๊ณต์›์„ ์—ฐ๊ตฌ๋Œ€์ƒ์œผ๋กœ ํ•˜์˜€๋‹ค. ๋„์‹œ๊ณต์›์€ ๊ทผ๋Œ€์‚ฌํšŒ ์ดํ›„ ํ†ต์น˜์ฃผ์ฒด๊ฐ€ ์—ฌ๊ฐ€๋ฅผ ํ†ตํ•ด ํ†ต์น˜์„ฑ์„ ์ˆ˜ํ–‰ํ•˜๋Š” ์ˆ˜๋‹จ(์žฅ์น˜)์œผ๋กœ ์กฐ์„ฑํ–ˆ์Œ์„ ๋ฌธํ—Œ๊ณ ์ฐฐ์„ ํ†ตํ•ด ํ™•์ธํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ง€์ž์ฒด ์‹ค์‹œ ์ดํ›„ ์กฐ์„ฑ๋œ ์„œ์šธ์‹œ ๋„์‹œ๊ณต์›์ธ ์„ ์œ ๋„๊ณต์›๊ณผ ๋ฌธํ™”๋น„์ถ•๊ธฐ์ง€๋ฅผ ํ˜„๋Œ€ ์ง€๋ฐฉ์ •๋ถ€์˜ ์—ฌ๊ฐ€๊ณต๊ฐ„ ์ƒ์‚ฐ๊ธฐ์ œ๋ฅผ ๊ทœ๋ช…ํ•  ์ˆ˜ ์žˆ๋Š” ๋Œ€ํ‘œ์‚ฌ๋ก€๋กœ ์„ ์ •ํ–ˆ๋‹ค. ๋ถ„์„๋ฐฉ๋ฒ• ๋ฐ ์ž๋ฃŒ๋Š” ๊ถŒ๋ ฅ-์ง€์‹์€ ๋ฐ˜๊ตฌ์กฐํ™” ์‹ฌ์ธต์ธํ„ฐ๋ทฐ๋กœ ์ „์‚ฌํ•œ ๊ตฌ์ˆ ์ฑ„๋ก, ๋‹ด๋ก ๋ถ„์„์€ ์–ธ๋ก ๊ธฐ์‚ฌ ์›น์Šคํฌ๋ž˜ํ•‘ ๋ฐ ๋„์‹œ๊ธฐ๋ณธ๊ณ„ํš ์ž๋ฃŒ์˜ ์ •์ฑ…๋‚ด๋Ÿฌํ‹ฐ๋ธŒ ๋ฐฉ๋ฒ•, ๊ฒฝ๊ด€๋ถ„์„์€ ํ˜„์žฅ๋‹ต์‚ฌ์™€ ๋ฌธํ—Œ๋ถ„์„์„ ํ†ตํ•œ ๋‚ด๋Ÿฌํ‹ฐ๋ธŒ ๋ฐฉ๋ฒ•์„ ์‹ค์‹œํ–ˆ๋‹ค. ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋ฅผ ์š”์•ฝํ•˜๋ฉด ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, ์ง€๋ฐฉ์ •๋ถ€๊ฐ€ ์—ฌ๊ฐ€๊ณต๊ฐ„์„ ์ƒ์‚ฐํ•˜๋Š” ์˜๋„๋Š” ์—ฌ๊ฐ€ํ†ต์น˜์„ฑ์„ ์ˆ˜ํ–‰ํ•˜๊ธฐ ์œ„ํ•œ ๊ฒƒ์ด์—ˆ๋‹ค. ์ฒซ ๋ฒˆ์งธ ์—ฌ๊ฐ€ํ†ต์น˜์„ฑ์€ ์ง€๋ฐฉ์ •๋ถ€์˜ ์„ ์ถœ์ง ์‹œ์žฅ์ด ์ž์‹ ์˜ ์‹œ์ •์ฒ ํ•™์„ ๊ณผ์‹œํ•˜์—ฌ ๊ตญ๋‚ด์™ธ๋กœ๋ถ€ํ„ฐ ์ •์น˜์  ์ง€์ง€๋ฅผ ๋ฐ›๊ธฐ ์œ„ํ•œ ๋ชฉ์ ์—์„œ ์—ฌ๊ฐ€(๊ณต๊ฐ„)์„ ์ƒ์‚ฐํ•œ๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. ์„ ์œ ๋„๊ณต์›์˜ ๊ฒฝ์šฐ ๋‹น์‹œ ์„ ์ถœ์ง ์‹œ์žฅ๊ณผ ๊ณ ์œ„๊ด€๋ฃŒ๋Š” ํ™˜๊ฒฝ๋ณด์กด์„ ์ค‘์‹œํ•˜๋Š” ์„ธ๊ณ„์  ์ถ”์„ธ์™€ ๋„์‹œ ๋‚ด๋ถ€์  ์œ„๊ธฐ์— ์ง๋ฉดํ–ˆ๋‹ค. ์ด์— ํ™˜๊ฒฝ์ƒํƒœ ์ฒ ํ•™์„ ์‹œ์ •๊ฐ€์น˜๋กœ ๋‚ด์„ธ์›€์œผ๋กœ์จ ๋Œ€๋‚ด์™ธ์ ์œผ๋กœ ์ •์น˜์  ์ง€์ง€๋ฅผ ๋ฐ›๊ณ ์ž ํ•˜์˜€๋‹ค. ๊ทธ๋ž˜์„œ ์—ฌ๊ฐ€๊ณต๊ฐ„์„ ํ™˜๊ฒฝ์ƒํƒœ ๋‹ด๋ก ์˜ ํ‘œ์ƒ์œผ๋กœ ํ™œ์šฉํ•˜์˜€์œผ๋ฉฐ, ํŠนํžˆ ๋„์‹œ๊ณต์›์„ ํ†ตํ•ด ์ด๋ฅผ ํ‘œ์ถœํ•˜์˜€๋‹ค. ๋งˆํฌ๋ฌธํ™”๋น„์ถ•๊ธฐ์ง€์˜ ๊ฒฝ์šฐ ์„ ์ถœ์ง ์‹œ์žฅ์€ ์„œ์šธ์‹œ์žฅ ์žฌ์„ ์—์„œ ๋‹น์„ ๋˜๊ธฐ ์œ„ํ•ด ๊ทธ๊ฐ€ ๊ฐ–๊ณ  ์žˆ๋Š” ์‹œ์ •์ฒ ํ•™์„ ๋Œ€๋‚ด์™ธ์ ์œผ๋กœ ์–ดํ•„ํ•˜๊ณ ์ž ํ–ˆ๋‹ค. ๋งˆํฌ๋ฌธํ™”๋น„์ถ•๊ธฐ์ง€๋Š” ์„ ์ถœ์ง ์‹œ์žฅ์˜ ์ฒ ํ•™์„ ํ‘œ์ƒํ•ด ๊ทธ์˜ ์ •์น˜์  ์ž…์ง€๋ฅผ ๊ฐ•ํ™”์‹œํ‚ค๋Š” ์ˆ˜๋‹จ์œผ๋กœ ๊ธฐํš๋œ ๊ฒƒ์ด์—ˆ๋‹ค. ๋‘ ๋ฒˆ์งธ ์—ฌ๊ฐ€ํ†ต์น˜์„ฑ์€, ํ˜„๋Œ€ ์‹ ์ž์œ ์ฃผ์˜ ์ง€๋ฐฉ์ •๋ถ€๊ฐ€ ์ฒ˜ํ•œ ๋Œ€๋‚ด์™ธ์  ํ™˜๊ฒฝ์„ ์ˆ˜์›”ํžˆ ํ†ต์น˜ํ•˜๊ธฐ ์œ„ํ•œ ์˜๋„์—์„œ ์—ฌ๊ฐ€(๊ณต๊ฐ„)์„ ์ƒ์‚ฐํ•œ๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. ์ง€๋ฐฉ์ •๋ถ€๋Š” ๊ทผ๋Œ€๊ตญ๊ฐ€์˜ ํ†ต์น˜๋ชฉ์ ๋ณด๋‹ค ๋” ๋‹ค์–‘ํ•œ ํ†ต์น˜๋ชฉ์ ์„ ๋‹ฌ์„ฑํ•ด์•ผ ํ–ˆ๋‹ค. ์ง€๋ฐฉ์ •๋ถ€๋Š” ๋„์‹œ์˜์—ญ ๋‚ด ์ž์›์ˆœํ™˜๊ณผ ์ฐฝ์ถœ ๋ฟ ์•„๋‹ˆ๋ผ ๋Œ€๋‚ด์™ธ์ ์œผ๋กœ ์ง๋ฉดํ•œ ์ •์น˜, ๊ฒฝ์ œ, ์‚ฌํšŒ๋ฌธํ™”์  ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•ด ๋„์‹œ๋ฅผ ์œ ์ง€์‹œํ‚ค๋ฉฐ, ๊ทผ๋Œ€๊ตญ๊ฐ€๋ณด๋‹ค ๋ถˆ์•ˆํ•œ ์žฌ์ • ์•ˆ์ •์„ฑ์„ ๊ทน๋ณตํ•˜๊ณ ์ž ๋„์‹œ๋ฏผ๋“ค์˜ ์ดํƒˆ์„ ๋ง‰๊ณ  ์„ธ์ˆ˜๋ฅผ ํ™•๋ณดํ•ด์•ผ ํ•˜๊ณ , ๋„์‹œ ๊ฐ„ ๊ฒฝ์Ÿ์—์„œ ์‚ด์•„๋‚จ๊ธฐ ์œ„ํ•ด ์™ธ๋ถ€์—์„œ ์ธ๊ตฌ์™€ ์ž๋ณธ์„ ์œ ์ž…์‹œ์ผœ ํŒŒ์‚ฐํ•˜์ง€ ์•Š๋„๋ก ํ•ด์•ผ ํ•œ๋‹ค. ์ด์— ์ง€๋ฐฉ์ •๋ถ€๋Š” ์ฃผ๊ถŒ, ์ž์œจ, ์‚ฌ๋ชฉ, ์ƒ์‚ฐ๋‹ด๋ก ์„ ๋งŒ๋“ค์–ด ์ด๋ฅผ ์—ฌ๊ฐ€(๊ณต๊ฐ„)์— ํˆฌ์˜์‹œ์ผœ ํ†ต์น˜์„ฑ์„ ์ˆ˜ํ–‰ํ•จ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ฃผ๊ถŒ, ์ž์œจ, ์‚ฌ๋ชฉ, ์ƒ์‚ฐ ๋‹ด๋ก ์ด๋ž€ ๊ฐ๊ฐ ๋‹น๋Œ€ ์ง€๋ฐฉ์ •๋ถ€ ํ†ต์น˜์ฒด์ œ์˜ ์ •๋‹น์„ฑ์„ ๊ฐ•ํ™”ํ•˜๊ธฐ ์œ„ํ•œ, ์‹œ๋ฏผ๋“ค์ด ํ†ต์น˜๋‹นํ•˜๊ณ  ์žˆ๋‹ค๊ณ  ๋Š๋ผ์ง€ ์•Š๊ฒŒ ํ•˜๋Š” ์ง„ํ™”๋œ ๊ทœ์œจ๋ฐฉ์‹์„ ์ˆ˜ํ–‰ํ•˜๊ธฐ ์œ„ํ•œ, ์‹œ๋ฏผ์˜ ์‚ถ์„ ๋ณด์‚ดํŽด์•ผ ํ•  ์˜๋ฌด๋ฅผ ์ดํ–‰ํ•˜๊ธฐ ์œ„ํ•œ, ๋„์‹œ๋ฅผ ์„ฑ์žฅ์‹œ์ผœ ์ง€๋ฐฉ์ •๋ถ€๊ฐ€ ํŒŒ์‚ฐํ•˜์ง€ ์•Š๋„๋ก ํ•˜๊ธฐ ์œ„ํ•œ ์˜๋„๋กœ ํ˜•์„ฑํ•œ ๋‹ด๋ก ์„ ๋งํ•œ๋‹ค. ํ˜„๋Œ€ ์ง€๋ฐฉ์ •๋ถ€๊ฐ€ ํŠนํžˆ ์—ฌ๊ฐ€๋ฅผ ํ†ตํ•ด ํ†ต์น˜์„ฑ์„ ์ˆ˜ํ–‰ํ•˜๋Š” ์ด์œ ๋Š” ์—ฌ๊ฐ€๊ฐ€ ๊ฒฝ์Ÿ ์›๋ฆฌ ๋ฐ ์ž๊ธฐํ†ต์น˜๋ผ๋Š” ์‹ ์ž์œ ์ฃผ์˜ ์ฃผ์ฒดํ™”๋ฅผ ์ˆ˜ํ–‰ํ•˜๋Š” ๋ฐ ์šฉ์ดํ•œ ์ „๋žต์ด ๋˜๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๋˜ ์—ฌ๊ฐ€๋Š” ํ›„๊ธฐ์‚ฐ์—…์‚ฌํšŒ ๋ฐ ์„ธ๊ณ„์‹œ์žฅ์—์„œ ์™ธ๋ถ€์ž๋ณธ ๋ฐ ์ธ๋ ฅ ์œ ์น˜ ๋“ฑ ๋„์‹œ ๊ฐ„ ๊ฒฝ์Ÿ์— ์‚ด์•„๋‚จ๋Š” ๋ฐ ์ข‹์€ ์ „๋žต์ด๋‹ค. ํ•œํŽธ ์ง€๋ฐฉ์ •๋ถ€๊ฐ€ ํ†ต์น˜ ์ •๋‹น์„ฑ์„ ๊ฐ•ํ™”ํ•˜๊ณ ์ž ๋„์‹œ์ •์ฒด์„ฑ์„ ์ฃผ์ž…ํ•˜๊ณ  ๊ธฐ์กด ํ†ต์น˜์ฒด์ œ๋ฅผ ๋น„ํŒํ•˜๋Š” ๋ฐ ์—ฌ๊ฐ€(๊ณต๊ฐ„)์„ ํ™œ์šฉํ•˜๋Š” ๊ฒƒ์ด ์‹œ๋ฏผ์„ ๊ฐ•์••ํ•˜์ง€ ์•Š์œผ๋ฉด์„œ ํšจ๊ณผ์ ์ด๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๋‘˜์งธ, ์ง€๋ฐฉ์ •๋ถ€์˜ ์—ฌ๊ฐ€๊ณต๊ฐ„ ์ƒ์‚ฐ ํ”„๋กœ์„ธ์Šค๋Š” ๋„์‹œ๊ณต์› ์กฐ์„ฑ ํ–‰์œ„์ž์˜ ๊ถŒ๋ ฅ-์ง€์‹ ์—ฐํ•ฉ์ด ๋‹ด๋ก ์ด ๋˜๊ณ  ๋‹ด๋ก ์ด ์ œ์‹œํ•˜๋Š” ๊ทœ๋ฒ”์ด ๊ฒฝ๊ด€์— ์žฌํ˜„, ์‹ค์ฒœ๋˜๋Š” ๊ณผ์ •์œผ๋กœ ์š”์•ฝํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ถŒ๋ ฅ-์ง€์‹ ํ˜•์„ฑ๊ณผ์ •์—์„œ๋Š” ํ–‰์œ„์ž ๊ฐ„ ์—ฐํ•ฉ๊ณผ ๊ถŒ๋ ฅ์—ญํ•™(์—ฐํ•ฉ, ๊ฐˆ๋“ฑ, ๋ฐฐ์ œ)์ด ๋‚˜ํƒ€๋‚œ๋‹ค. ์ฃผ์š” ํ–‰์œ„์ฃผ์ฒด์ธ ์„ ์ถœ์ง ์‹œ์žฅ์€ ์ž์‹ ์˜ ๊ถŒ๋ ฅ์„ ๊ฐ•ํ™”์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š” ํ–‰์œ„์ž์ธ ์ „๋ฌธ๊ฐ€ ์ง‘๋‹จ์„ ๋™์›ํ•ด ์—ฐํ•ฉํ•œ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๊ด€๋ฃŒ์ง‘๋‹จ, ์ง€์‹์ธ ์ง‘๋‹จ, ์„ ์ถœ์ง ์‹œ์žฅ, ๋ฏผ๊ฐ„ ์‹œ๋ฏผ์‚ฌํšŒ ์ง‘๋‹จ ๋“ฑ ์ฃผ์š” ํ–‰์œ„์ž ๊ฐ„ ํ˜‘์ƒ๊ณผ์ •์—์„œ ๊ถŒ๋ ฅ-์ง€์‹์ฒด๊ณ„ ๊ฐ„ ์—ฐํ•ฉ์„ ํ†ตํ•ด ์žฅ์†Œ์„ฑ ๊ฐ„ ๊ฒฝํ•ฉ์ด ์ผ์–ด๋‚œ๋‹ค. ์ด๋Š” ๊ถŒ๋ ฅ์—ญํ•™์— ์˜ํ•ด ํ•˜๋‚˜์˜ ์žฅ์†Œ์„ฑ์ด ์—ฌ๊ฐ€๊ณต๊ฐ„ ๋‹ด๋ก ์œผ๋กœ ์„ ํƒ๋œ๋‹ค. ํ•œํŽธ ์ง€๋ฐฉ์ •๋ถ€ ์ฐจ์›์—์„œ ๋‹น๋Œ€ ๋„์‹œ์‚ฌํšŒ ๋Œ€๋‚ด์™ธ์  ์ƒํ™ฉ์„ ํ†ต์น˜ํ•˜๊ธฐ ์œ„ํ•ด ์ฃผ๊ถŒ, ์ž์œจ, ์‚ฌ๋ชฉ, ์ƒ์‚ฐ๋‹ด๋ก ์„ ๋งŒ๋“ค์–ด๋‚ธ๋‹ค. ๋‘ ๋ฐฉํ–ฅ์˜ ์ž‘์šฉ์ด ํ•ฉ์ณ์ ธ ์—ฌ๊ฐ€๊ณต๊ฐ„ ๋‹ด๋ก  ํ‚ค์›Œ๋“œ์™€ ๊ทœ๋ฒ”(์ฃผ์ฒดํ™”) ์ƒ์ด ์ •ํ•ด์ง„๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๋‹ด๋ก ์ด ๋“œ๋Ÿฌ๋‚˜๋„๋ก ๊ฐ€์‹œ์ , ํ–‰์œ„, ๋ฏธ๋””์–ด ๊ฒฝ๊ด€์„ ์กฐํ˜•ํ•˜๊ณ  ํ†ต์ œ, ๊ฐ์‹œ, ์ œ์•ˆ, ๋ช…๋ นํ•˜๋Š” ๋ฐฉ์‹์„ ํ†ตํ•ด ํ”ผํ†ต์น˜์ฃผ์ฒด์ธ ์‹œ๋ฏผ์„ ๋‹ด๋ก ์ด ์ œ์‹œํ•˜๋Š” ๋ชจ์Šต์œผ๋กœ ์œ ๋„ํ•œ๋‹ค. ๊ทธ๊ฐ„ ์—ฌ๊ฐ€๊ณต๊ฐ„ ์ƒ์‚ฐ๊ณผ ๊ด€๋ จํ•œ ์—ฐ๊ตฌ๋Š” ํ–‰์œ„์ž, ๊ตฌ์กฐ, ๊ฒฝ๊ด€ ์ธก๋ฉด์—์„œ ๋ณ„๊ฐœ๋กœ ๋…ผ์˜๋˜์—ˆ๋‹ค. ํŠนํžˆ ์—ฌ๊ฐ€๊ณต๊ฐ„์— ๋Œ€ํ•œ ์‚ฌํšŒ๊ณต๊ฐ„๋ก ์  ๋…ผ์˜๋Š” ๋ถ€์กฑํ•˜์˜€๊ณ  ์ฃผ๋กœ ์‹ค์šฉ์  ๋ชฉ์ ์ด๋‚˜ ๋ฐฉ๋ฒ• ์œ„์ฃผ๋กœ ์—ฐ๊ตฌํ•ด์™”๋‹ค. ์ด ์—ฐ๊ตฌ์˜ ์˜์˜๋Š”, ์—ฌ๊ฐ€๊ณต๊ฐ„ ์ƒ์‚ฐ ๊ธฐ์ œ๋ฅผ ๊ถŒ๋ ฅ, ์ง€์‹- ๋‹ด๋ก - ๊ฒฝ๊ด€์˜ ๊ด€๊ณ„๋ฅผ ํ†ตํ•ด ํ–‰์œ„-๊ตฌ์กฐ-๊ณต๊ฐ„์„ ์—ฐ๊ณ„ํ•ด ์„ค๋ช…ํ•  ์ˆ˜ ์žˆ๋Š” ์—ฐ๊ตฌ๋ฐฉ๋ฒ•๋ก ์„ ์ œ์‹œํ•˜์˜€๋‹ค๋Š” ์ ์ด๋‹ค. ๋˜ ํ†ต์น˜์„ฑ์˜ ํ•˜์œ„๊ฐœ๋…์ธ โ€˜์—ฌ๊ฐ€ํ†ต์น˜์„ฑโ€™ ๊ฐœ๋…์„ ์ƒˆ๋กญ๊ฒŒ ์ œ์‹œํ•˜์—ฌ, ์‹œ๋Œ€๋ฅผ ๊ด€ํ†ตํ•˜๋Š” ํ†ต์น˜์ฃผ์ฒด์˜ ์—ฌ๊ฐ€๊ณต๊ฐ„ ์ƒ์‚ฐ์˜๋„๋ฅผ ์„ค๋ช…ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•™์ˆ ์  ์ง€ํ‰์„ ์—ด์—ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์—ฌ๊ฐ€๊ณต๊ฐ„์ด ํ•ฉ๋ฆฌ์  ๊ณ„ํš์„ ํ†ตํ•ด ์กฐ์„ฑ๋œ ๊ฐ€์น˜์ค‘๋ฆฝ์  ๊ณต๊ณต์žฌ๊ฐ€ ์•„๋‹ˆ๋ผ, ์ง€๋ฐฉ์ •๋ถ€์™€ ๊ฐ™์€ ํ†ต์น˜์ฃผ์ฒด์˜ ํ†ต์น˜์„ฑ ์ˆ˜๋‹จ์ผ ์ˆ˜ ์žˆ์Œ์„ ๋ฐฉ์ฆํ•˜์˜€๋‹ค. ํŠนํžˆ ๋„์‹œ๊ณต์›์„ ํ†ต์น˜์„ฑ ์ˆ˜๋‹จ(์žฅ์น˜)์ด๋ผ๋Š” ์‚ฌํšŒ๊ณต๊ฐ„๋ก  ๊ด€์ ์—์„œ ์„ค๋ช…ํ•จ์œผ๋กœ์จ ๊ธฐ์กด ๋„์‹œ๊ณต์› ์—ฐ๊ตฌ์— ์ฐธ์‹ ์„ฑ์„ ์ œ๊ณตํ•œ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ณต๊ฐ„์€ ํ†ต์น˜์„ฑ ์ˆ˜๋‹จ(์žฅ์น˜)๋กœ์„œ ํ†ต์น˜์„ฑ ์ˆ˜ํ–‰๊ณผ์ •์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ๋ ฅ์„ ๊ฐ•์กฐํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๊ฐ€ ํ–ฅํ›„ ํ†ต์น˜์„ฑ ์—ฐ๊ตฌ๋ถ„์•ผ์—์„œ ์ง€๋ฆฌํ•™์  ๋…ผ์˜๊ฐ€ ํ™œ์„ฑํ™”๋˜๋Š” ๋ฐ ์ผ์กฐํ•  ๊ฒƒ์ด๋‹ค. ํ–ฅํ›„ ์‹œ์žฅ, ๋ฏผ๊ฐ„์กฐ์ง, ๊ตญ๊ฐ€, ์‹œ๋ฏผ ๋“ฑ ๋‹ค์–‘ํ•œ ํ–‰์œ„์ž๊ฐ€ ์ƒ์‚ฐํ•˜๋Š” ์—ฌ๊ฐ€๊ณต๊ฐ„ ์‚ฌ๋ก€ ํ›„์†์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด, ๋ณธ ์—ฐ๊ตฌ๊ฐ€ ์ œ์‹œํ•œ ์—ฌ๊ฐ€ํ†ต์น˜์„ฑ ์žฅ์น˜๋กœ์„œ ์ƒ์‚ฐ๋˜๋Š” ์—ฌ๊ฐ€๊ณต๊ฐ„ ์ƒ์‚ฐ๊ธฐ์ œ ๋ชจํ˜•์„ ์‹ค์ฆํ•  ์ˆ˜ ์žˆ๋Š” ์ง€๋ฆฌํ•™์  ์—ฐ๊ตฌ๊ฐ€ ๋”์šฑ ํ™œ์„ฑํ™”๋  ๊ฒƒ์ด๋ผ ๊ธฐ๋Œ€ํ•œ๋‹ค.Space for leisure is rapidly increasing in cities, especially after implementing local government systems. As a result, the local governments are actively promoting the policy of making these leisure spaces. This is different from the modern paradigm in which the public decides to use the land mainly for development purposes. Therefore, this study began with two questions: "Why?" and "by what processes can the post-modern local governments create?" This study aims to clarify the local governments' leisure space-producing mechanisms by examining these two questions. In order to find the mechanism by which local governments construct leisure spaces, a theoretical framework that comprehensively explains the interaction between the internal and external environments and actors of the city, its social structures, and landscapes were needed. First, Foucault's governmentality theory was set as the first research hypothesis for the 'intention' of local governments to create space, assuming the intent of producing these spaces as conducting governmentality. In particular, this study coined a concept of' leisure-governmentality' to clarify the purpose of producing a 'leisure' space. Second, based on the first assumption, the local government's 'space production' process was viewed as forming power-knowledge, discourse, and landscape, the 'dispositif' (device) for governmentality. Therefore, two questions were studied by analyzing the process of power-knowledge, discourse, and landscape formation, an analysis framework for this research. The urban parks created by the Seoul Metropolitan Government were the subject of analysis. The literature review confirmed that urban parks were created as a dispositif for the governing people for governmentality through post-modern leisure society. In addition, Seonyudo Park, an urban park in Seoul created after the implementation of the local government, and the Mapo Culturetank was created as a representative policy that can clarify the leisure space production mechanism of current local governments. For analysis and data, power-knowledge as an oral record transcribed through semi-structured in-depth interview, discourse analysis by web scraping of media articles and policy narrative methods for urban master planning documents, and landscape analysis by conducting a narrative through field visits and literature analysis. The results of this study are summarized as follows. First, the intention of the local government to produce leisure space was to carry out leisure-governmentality. The first leisure-governmentality exhibited by the elected mayor of the local government is creating leisure (space) to gain political support at home and abroad by exhibiting his political philosophy. Faced with a global trend to emphasize environmental preservation and an internal crisis within the city, the elected mayor and officials close to the mayor collaborated to shape Seonyudo Park. Accordingly, they put an environmentally friendly philosophy forward as representative policies to gain internal and external political support. This represented environmental and ecological discourse, which was especially expressed through Seonyudo parks. In Mapo Culturetank, the elected mayor wanted to appeal his philosophy through this park both internally and externally to be re-elected in the next election. Thus, the mayor designed Mapo Culturetank to strengthen his political position by representing his philosophy to this urban park. The second leisure-governmentality is that leisure (space) is created to conveniently govern the internal and external environments of the neoliberal local government. Local governments have to achieve more diverse objectives to govern than those of the modern state. Local governments must circulate and create resources within the urban area and maintain the city by solving internal and external political, economic, and socio-cultural problems. The economy is somewhat insecure compared to the modern state; thus, the local government must secure tax revenue and citizens from leaving. Moreover, to survive intercity competition, it is crucial to ensure an influx of population and capital increase from the outside, not going bankrupt. Consequently, it was found that local governments created discourses by doing sovereignty, autonomy, pastoring, and production and projected them into leisure (space) to execute governmentality. Sovereignty, autonomy, pastoring, and production discourses have been formed to strengthen the legitimacy of the local government system of the time, to implement an evolved method of discipline that makes citizens feel that they are not being governed, to fulfill their duty to take care of the lives of the citizens to enlarge cities and prevent local governments from going bankrupt. Local governments in post-modern society especially exercise governmentality through leisure because leisure is an easy strategy to carry out the subject of neoliberalism of the principle of competition and self-governing. Furthermore, leisure is a good strategy for surviving competition between cities, such as attracting external capital and human resources in the post-industrial and global markets. Meanwhile, it is effective for local governments to use leisure (space) to instill urban identity, strengthen the legitimacy of governing, and criticize the existing government system without coercing citizens. Second, the local government's leisure space creation process can be summarized as a process in which the power-knowledge association of the actors who make the urban park policies produce discourses, and the norms suggested by the discourses are shaped and practiced to the landscape. In associating between power and knowledge, the negotiation process according to the coalition between actors and the power dynamics (collaboration, conflict, exclusion) appears. The elected mayor, the leading actor, gathers and unites specific experts who can strengthen the mayor's power. In the meantime, in the negotiation process among main actors such as bureaucracies, intellectuals, the elected mayor, and civil society groups, arguments about what knowledge for placeness is acceptable between them occur. This is because placeness for urban parks(leisure space) is selected by power dynamics discourse. Meanwhile, it creates sovereignty, autonomy, pastoring, and production discourses to govern contemporary urban society's internal and external conditions at the local government level. Thus, the two action directions are combined to determine the keyword, leisure space discourses, and the social norms(subjectivization). Furthermore, by shaping the hardware, software, and media landscape to reveal the discourses, the landscape conducts the citizens, the governed subjects, through the discourses presented by how the landscape controls, monitors, proposes, and commands the users of the leisure space. Research related to producing leisure spaces has been discussed separately from the actors, structures, and landscapes. In particular, discussion on socio-spatial theory on leisure space was lacking, and research has been mostly focused on practical purposes and methods. The significance of this study is that it suggests a research methodology that can explain the mechanism of creating leisure space by linking action-structure-space through the relationship between power-knowledge, discourse, landscape. In addition, the concept of 'leisure governmentality,' a sub-concept of governmentality, was newly presented, opening an academic horizon to explain the intention of the governing body to create leisure space throughout time. Furthermore, it was proved that leisure space is not a value-neutral public good created through rational planning but can be a means of governmentality for governing people by a local government. In particular, it provides novelty to existing urban park research from a social space theory perspective as a dispositif of governmentality. Finally, this study emphasized the influence of space as a dispositif for conducting governmentality. This study is expected to contribute to revitalizing geographical discussions in governmentality research in the future. Through follow-up studies on leisure space created by various actors such as the business sector, civic organizations, the state, and citizens, geographic research demonstrating the model of leisure space creation mechanisms produced as a leisure governmentality dispositif presented in this study will be further developed and activated.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ๋Œ€์ƒ ๋ฐ ๋ฒ”์œ„ 4 1. ์„ ์œ ๋„๊ณต์› 9 2. ๋งˆํฌ๋ฌธํ™”๋น„์ถ•๊ธฐ์ง€ 11 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ๋ฐฉ๋ฒ• ๋ฐ ์—ฐ๊ตฌํ๋ฆ„ 14 ์ œ 2 ์žฅ ์ด๋ก ์  ๊ณ ์ฐฐ ๋ฐ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  26 ์ œ 1 ์ ˆ ์ง€๋ฐฉ์ •๋ถ€์˜ ์—ฌ๊ฐ€๊ณต๊ฐ„ ์ƒ์‚ฐ ์˜๋„ 27 1. ํ˜„๋Œ€ ์‹ ์ž์œ ์ฃผ์˜ ์ง€๋ฐฉ์ •๋ถ€์˜ ํ†ต์น˜์„ฑ ์ˆ˜ํ–‰ ์˜๋„์™€ ํŠน์„ฑ 29 2. ์—ฌ๊ฐ€ํ†ต์น˜์„ฑ: ํ†ต์น˜์ฃผ์ฒด์˜ ์—ฌ๊ฐ€๋ฅผ ํ†ตํ•œ ํ†ต์น˜์„ฑ ์ˆ˜ํ–‰ 34 ์ œ 2 ์ ˆ ์ง€๋ฐฉ์ •๋ถ€์˜ ๊ณต๊ฐ„์ƒ์‚ฐ ํ”„๋กœ์„ธ์Šค 41 1. ํ†ต์น˜์„ฑ ์ˆ˜๋‹จ์ธ โ€˜์žฅ์น˜โ€™ (dispositif)๋กœ์„œ ๊ณต๊ฐ„ 41 2. โ€˜์žฅ์น˜โ€™ ๊ตฌ์„ฑ์š”์†Œ: ๊ถŒ๋ ฅ-์ง€์‹, ๋‹ด๋ก , ๊ฒฝ๊ด€ 44 1) ๊ถŒ๋ ฅ(power)-์ง€์‹(knowledge) 45 2) ๋‹ด๋ก (discourse) 47 3) ๊ฒฝ๊ด€(landscape) 49 ์ œ 3 ์ ˆ ์ง€๋ฐฉ์ •๋ถ€๊ฐ€ ์ƒ์‚ฐํ•˜๋Š” ์—ฌ๊ฐ€๊ณต๊ฐ„ ์‚ฌ๋ก€: ๋„์‹œ๊ณต์› 54 1. ์—ฌ๊ฐ€ํ†ต์น˜์„ฑ ์ˆ˜๋‹จ(์žฅ์น˜)์œผ๋กœ์„œ ๋„์‹œ๊ณต์› 54 2. ์„œ์šธ์‹œ ๋„์‹œ๊ณต์› ๊ณ„๋ณด 58 ์ œ 4 ์ ˆ ๋ถ„์„ํ‹€ 62 ์ œ 3 ์žฅ. ๋„์‹œ๊ณต์› ์กฐ์„ฑ ํ–‰์œ„์ž ๊ฐ„ ๊ถŒ๋ ฅ-์ง€์‹ ํ˜•์„ฑ๊ณผ์ • 64 ์ œ 1 ์ ˆ. ์„ ์œ ๋„๊ณต์›์˜ ๊ถŒ๋ ฅ-์ง€์‹ ์—ฐํ•ฉ๊ณผ ๊ฒฝํ•ฉ 65 1. ํ–‰์œ„์ž ๊ตฌ์„ฑ ๋ฐ ํ–‰์œ„์ž ๊ฐ„ ๊ถŒ๋ ฅ์—ญํ•™ 66 1) ์‹œ์žฅ ๋ฐ ๊ณ ์œ„๊ด€๋ฃŒ์˜ ์ฃผ๋„์  ์ถ”์ง„ 67 2) ์‹œ์žฅ(๊ณ ์œ„๊ด€๋ฃŒ)-๊ธฐ์ˆ ์ง€์‹์ธ ์ง‘๋‹จ ๊ฐ„ ์—ฐํ•ฉ 70 3) ๊ด€๋ฃŒ์ง‘๋‹จ ๋ฐ ๋ฏผ๊ฐ„ ์ „๋ฌธ๊ฐ€์ง‘๋‹จ ๋ณด์กฐ, ์‹œ๋ฏผ์‚ฌํšŒ ์ฐธ์—ฌ ๋ถ€์žฌ 72 2. ๊ถŒ๋ ฅ-์ง€์‹์˜ ์—ฐํ•ฉ์„ ํ†ตํ•œ ์žฅ์†Œ์„ฑ ๋„์ถœ๊ณผ ๊ฒฝํ•ฉ 74 1) ์‹œ์žฅ, ๊ณ ์œ„๊ด€๋ฃŒ: ํ•œ๊ฐ• ์—ญ์‚ฌ, ๋„์‹œํ™˜๊ฒฝ ๋ณต์› 74 2) ๊ธฐ์ˆ ์ง€์‹์ธ ์ง‘๋‹จ(๋‹น์„ ์ธ): ์„ ์œ ์ •์ˆ˜์žฅ, ๊ทผ๋Œ€ ์—ญ์‚ฌ, ์‹๋ฌผ์ƒํƒœ 76 3) ๊ธฐํƒ€ ์ „๋ฌธ๊ฐ€ ์ง‘๋‹จ: ์„ ์œ ๋ด‰ ์กฐ์„ ์‹œ๋Œ€ ์—ญ์‚ฌ, ํ’๋ฅ˜, ๋ฌธํ™”์ฐฝ์กฐ 78 ์ œ 2 ์ ˆ. ๋งˆํฌ๋ฌธํ™”๋น„์ถ•๊ธฐ์ง€์˜ ๊ถŒ๋ ฅ-์ง€์‹ ์—ฐํ•ฉ๊ณผ ๊ฒฝํ•ฉ 81 1. ํ–‰์œ„์ž ๊ตฌ์„ฑ ๋ฐ ํ–‰์œ„์ž ๊ฐ„ ๊ถŒ๋ ฅ์—ญํ•™ 82 1) ์‹œ์žฅ์˜ ์ฃผ๋„์  ๊ณต์›ํ™” ๊ฒฐ์ •๊ณผ ์ •๋‹นํ™” 84 2) ์‹œ์žฅ์˜ ์ „๋ฌธ๊ฐ€ ์ง‘๋‹จ ๋™์› 87 3) ๊ด€๋ฃŒ์ง‘๋‹จ์˜ ์‹œ์žฅ-์ „๋ฌธ๊ฐ€ ์ง‘๋‹จ ์—ฐํ•ฉ ๊ฒฌ์ œ 95 2. ๊ถŒ๋ ฅ-์ง€์‹์˜ ์—ฐํ•ฉ์„ ํ†ตํ•œ ์žฅ์†Œ์„ฑ ๋„์ถœ๊ณผ ๊ฒฝํ•ฉ 104 1) ์‹œ์žฅ-์‹œ๋ฏผ์‚ฌํšŒ ์ง‘๋‹จ: ํ™๋Œ€ ์ƒํ™œ์ฐฝ์ž‘ ๋ฌธํ™” 105 2) ๊ฑด์ถ•๊ฐ€ ์ง‘๋‹จ: ๋งค๋ด‰์‚ฐ ์ง€ํ˜•, ํƒฑํฌ ๊ฑด์ถ•๋ฌผ ์—ญ์‚ฌ 109 3) ๊ด€๋ฃŒ์ง‘๋‹จยท์‚ฌ๋ฌด๊ตญ: ๊ทผ๋ฆฐ๋ฌธํ™”ยท๋Œ€์ค‘ ๋ฌธํ™”์˜ˆ์ˆ  ์‹œ์„ค 112 ์ œ 3 ์ ˆ. ์†Œ๊ฒฐ 116 ์ œ 4 ์žฅ. ์ง€๋ฐฉ์ •๋ถ€์˜ ๋„์‹œ๊ณต์› ๋‹ด๋ก  ํ˜•์„ฑ ๋ชฉ์ ๊ณผ ๋ฐฐ๊ฒฝ 121 ์ œ 1 ์ ˆ. ์„ ์œ ๋„๊ณต์› ๋‹ด๋ก  ํ˜•์„ฑ๊ณผ์ • 122 1. ๋‹ด๋ก  ํ‚ค์›Œ๋“œ ๋ฐ ์ฃผ์ฒดํ™” ๊ทœ๋ฒ” 122 2. ๋‹ด๋ก  ํ˜•์„ฑ์˜ ๋ชฉ์ ๊ณผ ์‚ฌํšŒ์  ๋ฐฐ๊ฒฝ 125 1) ์ฃผ๊ถŒ๋‹ด๋ก : โ€˜ํ™˜๊ฒฝ, ์ƒํƒœ, ๋ณต์›โ€™, โ€˜์—ญ์‚ฌ, ๋ณด์กดโ€™ 125 2) ์ž์œจ๋‹ด๋ก : โ€˜๊ต์œก, ํ•™์Šตโ€™ 130 3) ์‚ฌ๋ชฉ๋‹ด๋ก : โ€˜ํ™˜๊ฒฝ, ์ƒํƒœ, ๋ณต์›โ€™, โ€˜์ •์ , ๋ช…์ƒ, ์‚ฌ์ƒ‰โ€™ 134 4) ์ƒ์‚ฐ๋‹ด๋ก : โ€˜ํ™˜๊ฒฝ, ์ƒํƒœโ€™ 140 ์ œ 2 ์ ˆ. ๋งˆํฌ๋ฌธํ™”๋น„์ถ•๊ธฐ์ง€ ๋‹ด๋ก  ํ˜•์„ฑ๊ณผ์ • 143 1. ๋‹ด๋ก  ํ‚ค์›Œ๋“œ ๋ฐ ์ฃผ์ฒดํ™” ๊ทœ๋ฒ” 143 2. ๋‹ด๋ก  ํ˜•์„ฑ์˜ ๋ชฉ์ ๊ณผ ์‚ฌํšŒ์  ๋ฐฐ๊ฒฝ 147 1) ์ฃผ๊ถŒ๋‹ด๋ก : โ€˜๊ณต๋™์ฒดโ€™, โ€˜์—ญ์‚ฌ, ์žฌ์ƒโ€™ 147 2) ์ž์œจ๋‹ด๋ก : โ€˜ํ˜‘์น˜โ€™ 152 3) ์‚ฌ๋ชฉ๋‹ด๋ก : โ€˜์ „ํ™˜๋„์‹œโ€™, โ€˜์ฐฝ์กฐโ€™, โ€˜๊ณต๋™์ฒดโ€™ 155 4) ์ƒ์‚ฐ๋‹ด๋ก : โ€˜์ฐฝ์กฐโ€™, โ€˜ํ˜‘์น˜โ€™, โ€˜๊ณต๋™์ฒดโ€™ 161 ์ œ 3 ์ ˆ. ์†Œ๊ฒฐ 168 ์ œ 5 ์žฅ. ๋„์‹œ๊ณต์› ๊ฒฝ๊ด€์„ ํ†ตํ•œ ์ง€๋ฐฉ์ •๋ถ€์˜ ์‹œ๋ฏผ ์œ ๋„ 173 ์ œ 1 ์ ˆ. ์„ ์œ ๋„๊ณต์› ๋‹ด๋ก  ๊ทœ๋ฒ”์˜ ๊ฒฝ๊ด€์  ์‹คํ˜„ 174 1. ํ™˜๊ฒฝ์‹œ๋ฏผ ์œ ๋„: ์ž์—ฐ์ƒํƒœ ๋ณต์› 174 2. ์ž์œจ์‹œ๋ฏผ ์œ ๋„: ๊ต์œก๊ณผ ํ•™์Šต 180 3. ์—ญ์‚ฌ์‹œ๋ฏผ ์œ ๋„: ๊ณผ๊ฑฐ ์—ญ์‚ฌ์˜ ๋ณด์กด 186 4. ๋ฌธํ™”์‹œ๋ฏผ ์œ ๋„: ์ •์  ๋ช…์ƒ๊ณผ ์‚ฌ์ƒ‰ 189 ์ œ 2 ์ ˆ. ๋งˆํฌ๋ฌธํ™”๋น„์ถ•๊ธฐ์ง€ ๋‹ด๋ก  ๊ทœ๋ฒ”์˜ ๊ฒฝ๊ด€์  ์‹คํ˜„ 199 1. ํ™˜๊ฒฝ์‹œ๋ฏผ ์œ ๋„: ์ž์›์ˆœํ™˜๊ณผ ์—๋„ˆ์ง€ ์ ˆ์•ฝ 199 2. ์ž์œจ์‹œ๋ฏผ ์œ ๋„: ํ˜‘์น˜์™€ ๊ณต๋™์ฒด ์ฐธ์—ฌ 205 3. ์—ญ์‚ฌ์‹œ๋ฏผ ์œ ๋„: ์—ญ์‚ฌ์˜ ๋ฏธ๋ž˜์  ์žฌ์ƒ 215 4. ๋ฌธํ™”์‹œ๋ฏผ ์œ ๋„: ๋™์  ์ฐฝ์กฐ์™€ ์ƒ์‚ฐ 221 ์ œ 3 ์ ˆ. ์†Œ๊ฒฐ 227 ์ œ 6 ์žฅ. ๊ฒฐ๋ก  229 ์ฐธ ๊ณ  ๋ฌธ ํ—Œ 239๋ฐ•

    `์„œ๋‹ค`์˜ ์˜๋ฏธ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ

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    ์กฐ์ง๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ, ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ, ์กฐ์ง์„ฑ๊ณผ๋ฅผ ์ค‘์‹ฌ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :ํ–‰์ •๋Œ€ํ•™์› ํ–‰์ •ํ•™๊ณผ(ํ–‰์ •ํ•™์ „๊ณต),2019. 8. ์ „์˜ํ•œ.๋ณธ ์—ฐ๊ตฌ๋Š” ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์งํŠน์„ฑ ๋ฐ ์กฐ์ง์„ฑ๊ณผ์™€์˜ ๊ด€๊ณ„๋ฅผ ๋ฐํžˆ๊ณ , ์ด์— ๋Œ€ํ•œ ๋ณด๋‹ค ์ฒด๊ณ„์ ์ด๊ณ  ์—„๋ฐ€ํ•œ ์—ฐ๊ตฌ ์„ค๊ณ„๋ฅผ ์ง„ํ–‰ํ•จ์œผ๋กœ์จ ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ๊ด€๋ จ๋œ ์ง€์‹ ์ถ•์ ์— ๊ธฐ์—ฌํ•˜๊ณ ์ž ํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ์†Œ์œ ๊ถŒ์  ๊ณต๊ณต์„ฑ, ์žฌ์ •์  ๊ณต๊ณต์„ฑ, ํ†ต์ œ ๊ณต๊ณต์„ฑ ๋“ฑ ์กฐ์ง๊ณต๊ณต์„ฑ์˜ ๋‹ค์–‘ํ•œ ํ•˜์œ„์ฐจ์›๋“ค์„ ํ•˜๋‚˜์˜ ๋ชจํ˜•์—์„œ ๋‹ค๋ฃจ์–ด ์กฐ์ง๊ณต๊ณต์„ฑ์„ ํ†ตํ•ฉ์ ์œผ๋กœ ํƒ๊ตฌํ•˜์˜€์œผ๋ฉฐ, ๋‹ค์–‘ํ•œ ๊ธฐ๋Šฅ์„ ์ˆ˜ํ–‰ํ•˜๋Š” ์•ฝ 300์—ฌ ๊ฐœ์˜ ๊ณต๊ณต์„œ๋น„์Šค ์กฐ์ง์— ๋Œ€ํ•œ 3๋…„๊ฐ„์˜ ๋ฐ์ดํ„ฐ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ์˜ ์ผ๋ฐ˜ํ™”๋ฅผ ๊พ€ํ•˜์˜€๋‹ค. ๋˜ํ•œ ๊ฐ ์ข…์†๋ณ€์ˆ˜์— ์˜ํ–ฅ์„ ๋ฏธ์น  ๊ฒƒ์ด๋ผ๊ณ  ์˜ˆ์ƒ๋˜๋Š” ํ†ต์ œ๋ณ€์ˆ˜๋ฅผ ์—ฐ๊ตฌ ๋ชจํ˜•์— ํฌํ•จ์‹œ์ผœ ์—ฐ๊ตฌ์˜ ํƒ€๋‹น๋„๋ฅผ ๋†’์ด๋Š” ํ•œํŽธ, ์กฐ์ง์„ฑ๊ณผ ๋ฟ ์•„๋‹ˆ๋ผ ์กฐ์งํŠน์„ฑ๊ณผ ์กฐ์ง๊ณต๊ณต์„ฑ์˜ ๊ด€๊ณ„์— ๋Œ€ํ•ด์„œ๋„ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•จ์œผ๋กœ์จ ์กฐ์ง๊ณต๊ณต์„ฑ์˜ ํšจ๊ณผ๋ฅผ ๋‹ค๊ฐ๋„๋กœ ํƒ๊ตฌํ•˜์˜€๋‹ค. ์ด์™€ ๋”๋ถˆ์–ด ์กฐ์ง์„ฑ๊ณผ์˜ ๋‹ค์ฐจ์›์„ฑ์„ ๋ฐ˜์˜ํ•  ์ˆ˜ ์žˆ๋Š” ๋‹ค์–‘ํ•œ ์ธก์ • ์ง€ํ‘œ๋“ค์„ ์‚ฌ์šฉํ•จ์œผ๋กœ์จ ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ ๊ฐ„์˜ ๊ด€๊ณ„๋ฅผ ์ข…ํ•ฉ์ ์œผ๋กœ ๋‹ค๋ฃจ์—ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ํฌ๊ฒŒ ์ฒซ์งธ, ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ ๊ฐ„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ์—ฐ๊ตฌ, ๋‘˜์งธ, ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ ๊ฐ„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ์—ฐ๊ตฌ, ์…‹์งธ, ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ ๊ฐ„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ์—ฐ๊ตฌ ๋“ฑ 3๊ฐœ์˜ ์‹ค์ฆ ์—ฐ๊ตฌ๋กœ ๊ตฌ์„ฑ๋œ๋‹ค. ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ ๊ฐ„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ๋ถ„์„๊ฒฐ๊ณผ์—์„œ๋Š” ์กฐ์ง๊ณต๊ณต์„ฑ์˜ ์„ธ ๊ฐ€์ง€ ํ•˜์œ„์ฐจ์›์ธ ์†Œ์œ ๊ถŒ์  ๊ณต๊ณต์„ฑ, ์žฌ์ •์  ๊ณต๊ณต์„ฑ, ํ†ต์ œ ๊ณต๊ณต์„ฑ ๋ชจ๋‘ ์กฐ์ง๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ๊ณผ๋Š” ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜๋ฏธํ•œ ๊ด€๊ณ„๊ฐ€ ๋‚˜ํƒ€๋‚˜์ง€ ์•Š์•˜๋‹ค. ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ ๊ฐ„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ์—์„œ๋Š” ์ •๋ถ€์†Œ์œ  ์กฐ์ง์ด ๋น„์ •๋ถ€์†Œ์œ  ์กฐ์ง๋ณด๋‹ค ์ƒ๋Œ€์ ์œผ๋กœ ๊ณ„์ธต์  ๋ถ„ํ™” ์ˆ˜์ค€ ๋ฐ ๋ ˆ๋“œํ…Œ์ดํ”„ ์ˆ˜์ค€์ด ๋” ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ํ†ต์ œ ๊ณต๊ณต์„ฑ์˜ ์ธก์ • ์ง€ํ‘œ ์ค‘ ํ–‰์ •์ ˆ์ฐจ๋Š” ๋ ˆ๋“œํ…Œ์ดํ”„์™€์˜ ๊ด€๊ณ„์—์„œ๋งŒ ์œ ์˜๋ฏธ์„ฑ์„ ๋‚˜ํƒ€๋‚ฌ์ง€๋งŒ ๊ทธ ๋ฐฉํ–ฅ์„ฑ์€ ์˜ˆ์ธก๊ณผ๋Š” ๋ฐ˜๋Œ€๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ, ๊ฐ์‚ฌ ๋ฐ ํ‰๊ฐ€ ์ •๋„๋Š” ๊ณต์‹ํ™”์™€ ์ •(+)์˜ ๊ด€๊ณ„๋ฅผ ๋‚˜ํƒ€๋‚ด์—ˆ๋‹ค. ํ•œํŽธ, ์žฌ์ •์  ๊ณต๊ณต์„ฑ์€ ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ์˜ ์–ด๋–ค ์ฐจ์›๊ณผ๋„ ๊ด€๊ณ„๊ฐ€ ์—†๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ ๊ฐ„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ, ํšจ๊ณผ์„ฑ, ํ˜•ํ‰์„ฑ, ์ ˆ์ฐจ์  ๊ฐ€์น˜์™€ ๊ด€๋ จํ•ด์„œ๋Š” ์ •๋ถ€์˜ ์ง€๋„ยท๊ฐ๋… ์ •๋„๊ฐ€ ๋†’์€ ์ˆ˜์ค€์˜ ํšจ๊ณผ์„ฑ ๋ฐ ํ˜•ํ‰์„ฑ๊ณผ ๊ด€๋ จ์ด ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์†Œ์œ ๊ถŒ์  ๊ณต๊ณต์„ฑ์€ ๋‚ฎ์€ ํšจ์œจ์„ฑ๊ณผ ์—ฐ๊ด€๋˜์–ด ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ, ํ†ต์ œ ๊ณต๊ณต์„ฑ์˜ ์„ธ ๊ฐ€์ง€ ์ธก์ • ์ง€ํ‘œ ๋˜ํ•œ ํšจ์œจ์„ฑ๊ณผ ๊ฐ•ํ•œ ๋ถ€(-)์˜ ๊ด€๊ณ„๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์—ˆ๋‹ค. ํ•œํŽธ, ์žฌ์ •์  ๊ณต๊ณต์„ฑ์€ ์„ฑ๊ณผ์˜ ์–ด๋–ค ์ฐจ์›๊ณผ๋„ ๊ด€๊ณ„๊ฐ€ ์—†๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด๋ก ์  ์ธก๋ฉด์—์„œ ๋ณธ ์—ฐ๊ตฌ๋Š” ๋ณธ ์—ฐ๊ตฌ์˜ ์ฃผ์š” ๋…๋ฆฝ๋ณ€์ˆ˜์ธ ์กฐ์ง๊ณต๊ณต์„ฑ์˜ ํ•˜์œ„์ฐจ์›๋“ค์— ๋Œ€ํ•œ ๊ฐœ๋…๊ณผ ์ธก์ •์— ๋Œ€ํ•œ ๊ตฌ์ฒด์ ์ธ ๋…ผ์˜๋ฅผ ์ง„ํ–‰ํ•จ์œผ๋กœ์จ, ์กฐ์ง๊ณต๊ณต์„ฑ์˜ ํ•˜์œ„์ฐจ์›๋“ค์˜ ๊ฐœ๋…๊ณผ ์ธก์ •์— ๋Œ€ํ•œ ์ง€์‹์— ๊ธฐ์—ฌํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ๋˜ํ•œ ๋ณธ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ, ์กฐ์ง๊ณต๊ณต์„ฑ์˜ ํ•˜์œ„์ฐจ์›๋“ค์ด ๋‹ค์–‘ํ•œ ์กฐ์งํŠน์„ฑ ๋ณ€์ธ ๋ฐ ์กฐ์ง์„ฑ๊ณผ์™€ ๋‹จ์ˆœํ•˜๊ณ  ํš์ผ์ ์ธ ๊ด€๊ณ„๋ฅผ ๋งบ๊ธฐ๋ณด๋‹ค๋Š” ๋ณต์žกํ•˜๊ณ  ์ฐจ๋ณ„์ ์ธ ๊ด€๊ณ„๋ฅผ ๋งบ๊ณ  ์žˆ์Œ์ด ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ, ์ด์— ๊ด€๋ จํ•˜์—ฌ ์ง„ํ–‰ํ•œ ๊ตฌ์ฒด์ ์ธ ๋…ผ์˜๋Š” ์กฐ์ง๊ณต๊ณต์„ฑ์— ๋Œ€ํ•œ ์ดํ•ด์™€ ๋ถ„์„์˜ ๋ฒ”์œ„๋ฅผ ํ™•์žฅ์‹œํ‚ค๋Š”๋ฐ ๊ธฐ์—ฌํ•˜์˜€๋‹ค. ํ•œํŽธ, ๋ณธ ์—ฐ๊ตฌ์˜ ๋ถ„์„๊ฒฐ๊ณผ๋Š” ์ „ํ˜•์ ์ธ ์ •๋ถ€์กฐ์ง ๋ฐ ์ „ํ˜•์ ์ธ ๋ฏผ๊ฐ„ ๊ธฐ์—…์ด๋ผ๋Š” ๋‘ ๊ฐ€์ง€ ๊ทน๋‹จ์ ์ธ ์กฐ์งํ˜•ํƒœ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ์ด๋ฃจ์–ด์ ธ ์˜จ ์กฐ์ง๊ณต๊ณต์„ฑ์„ ๋‘˜๋Ÿฌ์‹ผ ์ด๋ก ์  ๋…ผ์˜๊ฐ€ ํ˜„๋Œ€์˜ ๋ณต์žกํ•œ ์กฐ์งํ˜•ํƒœ(์ค€์ •๋ถ€์กฐ์ง)์—์„œ๋Š” ๊ทธ ์ ํ•ฉ์„ฑ์ด ๋‚ฎ์•„์งˆ ๊ฐ€๋Šฅ์„ฑ์„ ์ œ๊ธฐํ•˜๊ณ  ์žˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ๋ณธ ์—ฐ๊ตฌ์—์„œ ๋‹ค๋ฃฌ ๋‹ค์–‘ํ•œ ์กฐ์งํŠน์„ฑ ๋ณ€์ˆ˜๋“ค(์กฐ์ง๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ ๋ฐ ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ)๊ณผ ์กฐ์ง๊ณต๊ณต์„ฑ ๊ฐ„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ ์‚ฌ์ด์— ์กด์žฌํ•˜๋Š” ๋ธ”๋ž™๋ฐ•์Šค๋ฅผ ๊ทœ๋ช…ํ•˜๋Š” ๊ณผ์ •์— ๊ธฐ์—ฌํ•˜์˜€๋‹ค. ์ •์ฑ…์  ์ธก๋ฉด์—์„œ ๋ณธ ์—ฐ๊ตฌ๋Š” ์กฐ์ง๊ณต๊ณต์„ฑ์ด๋ผ๋Š” ๋‹ค์†Œ ์ถ”์ƒ์ ์ธ ๊ฐœ๋…์ด ์ •์ฑ…์‹ค๋ฌด์ž๋“ค์—๊ฒŒ ์ง๊ด€์ ์œผ๋กœ ๋ฐ›์•„๋“ค์—ฌ์ง€๊ธฐ ์–ด๋ ค์šธ ๊ฒƒ์ด๋ผ๋Š” ์šฐ๋ ค์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ํ–ฅํ›„ ์ •์ฑ…์‹ค๋ฌด์ž๋“ค์ด ์กฐ์ง๊ณต๊ณต์„ฑ์˜ ๋ณ€ํ™”์™€ ์ถ”์ด๋ฅผ ๊ด€์ธกํ•˜๊ณ , ์ด๋Ÿฌํ•œ ์กฐ์ง๊ณต๊ณต์„ฑ์ด ์‹ค์ œ๋กœ ์กฐ์ง์— ์–ด๋– ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€์— ๋Œ€ํ•ด ๊ด€์‹ฌ์„ ๊ฐ€์ ธ์•ผ ํ•จ์„ ๋ณด์—ฌ์ค€๋‹ค. ๋˜ํ•œ, ๋ณธ ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ๋Š” ์ •์ฑ…๊ฒฐ์ •์ž ๋ฐ ์ •์ฑ…์ง‘ํ–‰์ž๋“ค์ด ๋‹ฌ์„ฑํ•˜๊ณ ์ž ํ•˜๋Š” ๋ชฉ์ ์— ๋”ฐ๋ผ ์กฐ์ง๊ณต๊ณต์„ฑ์„ ๋†’์ด๊ฑฐ๋‚˜ ๋‚ฎ์ถ”๋Š” ์ •์ฑ…์ˆ˜๋‹จ์„ ๋‹ฌ๋ฆฌ ์ ์šฉํ•ด์•ผ ํ•จ์„ ์•”์‹œํ•œ๋‹ค. ํŠนํžˆ ๋‹ค๋ฅธ ์กฐ์ง๊ณต๊ณต์„ฑ ์ฐจ์›๋“ค์— ๋น„ํ•ด ํ†ต์ œ๊ณต๊ณต์„ฑ์€ ์กฐ์ง์„ฑ๊ณผ์™€ ๊ธด๋ฐ€ํ•œ ์—ฐ๊ด€์„ฑ์„ ์ง€๋‹ˆ๊ณ  ์žˆ์Œ์„ ํ™•์ธํ•˜์˜€๊ธฐ ๋•Œ๋ฌธ์— ํ†ต์ œ๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ ๊ฐ„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ๋ถ„์„๊ฒฐ๊ณผ๋Š” ๊ณต๊ณต๊ด€๋ฆฌ์ž๋“ค์—๊ฒŒ ์ค‘์š”ํ•œ ์‹œ์‚ฌ์ ์„ ์ค€๋‹ค. ๊ทธ๋™์•ˆ ํ•œ๊ตญ์˜ ๊ณต๊ณต๊ธฐ๊ด€๊ณผ ๊ด€๋ จํ•˜์—ฌ ๊ณต๊ณต๊ด€๋ฆฌ์ž๋“ค์€ ๊ณต๊ณต์„œ๋น„์Šค์˜ ํšจ๊ณผ์ ์ธ ์ œ๊ณต์„ ์œ„ํ•œ ๋…ธ๋ ฅ์„ ๊ฒฝ์ฃผํ•ด ์™”๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๊ทธ๋Ÿฌํ•œ ๋…ธ๋ ฅ์€ ์ฃผ๋กœ ๊ณต๊ณต๊ธฐ๊ด€ ๋‚ด ํ†ต์ œ ๊ณต๊ณต์„ฑ์˜ ์ •๋„๋ฅผ ๋ณ€ํ™”์‹œํ‚ค๋Š” ๋ฐ ๋งž์ถ”์–ด์ ธ ์™”๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋ณธ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋Š” ํ†ต์ œ ๊ณต๊ณต์„ฑ์„ ๋†’์ด๋Š” ๋‹ค์–‘ํ•œ ์ •์ฑ… ์ˆ˜๋‹จ๋“ค์ด ์„œ๋กœ ๋‹ค๋ฅธ ํšจ๊ณผ๋ฅผ ๊ฐ€์งˆ ์ˆ˜ ์žˆ์Œ์„ ๋ณด์—ฌ์ฃผ๋ฉฐ, ๊ณต๊ณต์„œ๋น„์Šค ์กฐ์ง์˜ ๊ด€๋ฆฌ์ž๋“ค์€ ์„ฑ๊ณผ์˜ ๋‹ค์ฐจ์›์„ฑ์„ ๊ณ ๋ คํ•˜์—ฌ, ๊ณผ์—ฐ ๊ทธ ์กฐ์ง์— ์žˆ์–ด ์–ด๋– ํ•œ ๊ฐ€์น˜๊ฐ€ ์ค‘์š”ํ•œ๊ฐ€์— ๋”ฐ๋ผ ์‚ฌ์šฉ๋˜์–ด์•ผ ํ•  ์ˆ˜๋‹จ๋“ค์„ ๋‹ฌ๋ฆฌ ์ ์šฉํ•ด์•ผ ํ•  ํ•„์š”์„ฑ์„ ๋‚˜ํƒ€๋‚ด๊ณ  ์žˆ๋‹ค๊ณ  ํ•ด์„ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ์ด๋ก ์ ใƒป์ •์ฑ…์  ๊ธฐ์—ฌ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ๋ณธ ์—ฐ๊ตฌ๋Š” ๋ช…๋ฃŒํ•œ ์ธ๊ณผ์ด๋ก ์˜ ๋ถ€์žฌ, ์กฐ์ง๊ณต๊ณต์„ฑ ์ธก์ •๋ฐฉ์‹์˜ ์‹œ๊ฐ„์ ใƒป๊ณต๊ฐ„์  ํ•œ๊ณ„, ์ถ”๊ฐ€์ ์ธ ์กฐ์ง๊ณต๊ณต์„ฑ ์ฐจ์›์˜ ์กด์žฌ ๊ฐ€๋Šฅ์„ฑ, ๋‚ด์ƒ์„ฑ์œผ๋กœ ์ธํ•œ ์ธ๊ณผ์„ฑ ํƒ๊ตฌ์˜ ์–ด๋ ค์›€ ๋“ฑ์˜ ํ•œ๊ณ„๊ฐ€ ์กด์žฌํ•˜๋ฉฐ, ์ด์— ๋ณด์™„ํ•  ์ˆ˜ ์žˆ๋Š” ํ›„์†์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค. ์ œ1์žฅ ์„œ๋ก  1 ์ œ1์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ ๋ฐ ์˜์˜ 1 ์ œ2์ ˆ ์—ฐ๊ตฌ์˜ ๋Œ€์ƒ 6 ์ œ3์ ˆ ์—ฐ๊ตฌ์˜ ๊ตฌ์„ฑ 9 ์ œ2์žฅ ์กฐ์ง๊ณต๊ณต์„ฑ์— ๋Œ€ํ•œ ์ด๋ก ์  ๋…ผ์˜์™€ ์ธก์ • 13 ์ œ1์ ˆ ์กฐ์ง๊ณต๊ณต์„ฑ ์—ฐ๊ตฌ์˜ ํ๋ฆ„ 13 ์ œ2์ ˆ ๊ฒฝํ—˜์  ์ ‘๊ทผ๋ฒ•์— ๋”ฐ๋ฅธ ์—ฐ๊ตฌ ์„ค๊ณ„์—์„œ์˜ ๋ฌธ์ œ 20 ์ œ3์ ˆ ๊ฒฝํ—˜์  ์ ‘๊ทผ๋ฒ•์— ๋”ฐ๋ฅธ ์กฐ์ง๊ณต๊ณต์„ฑ์˜ ํ•˜์œ„์ฐจ์›: ์†Œ์œ ๊ถŒ์  ๊ณต๊ณต์„ฑ, ์žฌ์ •์  ๊ณต๊ณต์„ฑ, ํ†ต์ œ ๊ณต๊ณต์„ฑ 23 1. ์†Œ์œ ๊ถŒ์  ๊ณต๊ณต์„ฑ 25 2. ์žฌ์ •์  ๊ณต๊ณต์„ฑ 27 3. ํ†ต์ œ ๊ณต๊ณต์„ฑ 30 ์ œ4์ ˆ ๊ฒฝํ—˜์  ์ ‘๊ทผ๋ฒ•์— ๋”ฐ๋ฅธ ์กฐ์ง๊ณต๊ณต์„ฑ์˜ ์ธก์ • 35 1. ์กฐ์ง๊ณต๊ณต์„ฑ์˜ ์ธก์ •์— ๋Œ€ํ•œ ๋…ผ์˜ 35 2. ์กฐ์ง๊ณต๊ณต์„ฑ์— ๋Œ€ํ•œ ๊ธฐ์ˆ ํ†ต๊ณ„๋ถ„์„ ๊ฒฐ๊ณผ 43 3. ์กฐ์ง๊ณต๊ณต์„ฑ ๋ณ€์ˆ˜ ๊ฐ„ ์ƒ๊ด€๊ด€๊ณ„ ๋ถ„์„ ๊ฒฐ๊ณผ 46 ์ œ3์žฅ ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ 48 ์ œ1์ ˆ ์กฐ์ง๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ 48 ์ œ2์ ˆ ๊ณต๊ณต์กฐ์ง์˜ ๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ๊ณผ ๊ทธ ์›์ธ์— ๋Œ€ํ•œ ๋…ผ์˜ 51 1. ์ •์น˜ํ•™์  ๊ด€์  51 2. ๊ฒฝ์ œํ•™์  ๊ด€์  54 ์ œ3์ ˆ ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง๋ชฉํ‘œํŠน์„ฑ ๊ฐ„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ๊ฒฝํ—˜์  ์—ฐ๊ตฌ 56 ์ œ4์ ˆ ์†Œ์œ ๊ถŒ์  ๊ณต๊ณต์„ฑ, ์žฌ์ •์  ๊ณต๊ณต์„ฑ, ํ†ต์ œ ๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ ๊ฐ„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ๊ฐ€์„ค ์„ค์ • 63 ์ œ5์ ˆ ์—ฐ๊ตฌ ์„ค๊ณ„ 68 1. ์—ฐ๊ตฌ ๋Œ€์ƒ 68 2. ์ž๋ฃŒ์˜ ์›์ฒœ 68 3. ๋ฌด์‘๋‹ต ํŽธ์˜ 70 4. ์ฃผ์š” ๋ณ€์ˆ˜์˜ ์ธก์ • 74 5. ๋ถ„์„์ ˆ์ฐจ 83 ์ œ6์ ˆ ๋ถ„์„๊ฒฐ๊ณผ 88 1. ํƒ์ƒ‰์  ์š”์ธ๋ถ„์„ 88 2. ๊ธฐ์ˆ ํ†ต๊ณ„๋ถ„์„ 91 3. ์ƒ๊ด€๊ด€๊ณ„๋ถ„์„ 93 4. ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ์— ๋Œ€ํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ 94 ์ œ7์ ˆ ๋…ผ์˜ 98 ์ œ4์žฅ ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ 102 ์ œ1์ ˆ ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ 102 ์ œ2์ ˆ ๊ณต๊ณต์กฐ์ง์˜ ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ์™€ ๊ทธ ์›์ธ์— ๋Œ€ํ•œ ๋…ผ์˜ 105 ์ œ3์ ˆ ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ ๊ฐ„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ๊ฒฝํ—˜์  ์—ฐ๊ตฌ 114 ์ œ4์ ˆ ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ ๊ฐ„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ๊ฐ€์„ค ์„ค์ • 124 1. ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ๊ณ„์ธต์  ๋ถ„ํ™” 124 2. ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์ง‘๊ถŒํ™” 125 3. ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ๊ณต์‹ํ™” ๋ฐ ๋ ˆ๋“œํ…Œ์ดํ”„ 126 ์ œ5์ ˆ ์—ฐ๊ตฌ ์„ค๊ณ„ 129 1. ์—ฐ๊ตฌ ๋Œ€์ƒ 129 2. ์ž๋ฃŒ์˜ ์›์ฒœ 129 3. ์ฃผ์š” ๋ณ€์ˆ˜์˜ ์ธก์ • 129 4. ๋ถ„์„์ ˆ์ฐจ 139 ์ œ6์ ˆ ๋ถ„์„๊ฒฐ๊ณผ 140 1. ํƒ์ƒ‰์  ์š”์ธ๋ถ„์„ 140 2. ๊ธฐ์ˆ ํ†ต๊ณ„๋ถ„์„ 142 3. ์ƒ๊ด€๊ด€๊ณ„๋ถ„์„ 145 4. ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ์— ๋Œ€ํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ 146 ์ œ7์ ˆ ๋…ผ์˜ 156 ์ œ5์žฅ ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ 161 ์ œ1์ ˆ ์กฐ์ง์„ฑ๊ณผ์˜ ๋‹ค์ฐจ์›์„ฑ์— ๋Œ€ํ•œ ๋…ผ์˜ 161 ์ œ2์ ˆ ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ ๊ฐ„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ๋…ผ์˜ 167 1. ์žฌ์‚ฐ๊ถŒ ์ด๋ก  168 2. ๊ณต๊ณต์„ ํƒ๋ก  ๋ฐ ์ •๋ถ€(๋˜๋Š” ๋น„์‹œ์žฅ)์‹คํŒจ๋ก  171 3. ๊ณ„์•ฝ์‹คํŒจ ์ด๋ก  173 4. ์ •์ฑ…์ˆ˜๋‹จ๋ก  175 ์ œ3์ ˆ ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ ๊ฐ„ ๊ด€๊ณ„์— ๋Œ€ํ•œ ๊ฒฝํ—˜์  ์—ฐ๊ตฌ 179 1. ์—ฐ๊ตฌ ์„ค๊ณ„ ์ธก๋ฉด 179 2. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ ์ธก๋ฉด 190 ์ œ4์ ˆ ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ ๊ฐ„ ๊ด€๊ณ„์— ๋Œ€ํ•œ ๊ฐ€์„ค ์„ค์ • 206 1. ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ํšจ๊ณผ์„ฑ 206 2. ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ํšจ์œจ์„ฑ 207 3. ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ํ˜•ํ‰์„ฑ 210 4. ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์ ˆ์ฐจ์  ๊ฐ€์น˜ 211 ์ œ5์ ˆ ์—ฐ๊ตฌ ์„ค๊ณ„ 213 1. ์—ฐ๊ตฌ ๋Œ€์ƒ 213 2. ์ž๋ฃŒ์˜ ์›์ฒœ 213 3. ์ฃผ์š” ๋ณ€์ˆ˜์˜ ์ธก์ • 213 4. ๋ถ„์„์ ˆ์ฐจ 226 ์ œ6์ ˆ ๋ถ„์„๊ฒฐ๊ณผ 227 1. ํƒ์ƒ‰์  ์š”์ธ๋ถ„์„ 227 2. ๊ธฐ์ˆ ํ†ต๊ณ„๋ถ„์„ 229 3. ์ƒ๊ด€๊ด€๊ณ„๋ถ„์„ 232 4. ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ์— ๋Œ€ํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ 233 ์ œ7์ ˆ ๋…ผ์˜ 243 ์ œ6์žฅ ๊ฒฐ๋ก  248 ์ œ1์ ˆ ์—ฐ๊ตฌ๊ฒฐ๊ณผ์˜ ์š”์•ฝ 248 ์ œ2์ ˆ ๋ณธ ์—ฐ๊ตฌ์˜ ์ด๋ก ์  ์˜์˜ 250 ์ œ3์ ˆ ๋ณธ ์—ฐ๊ตฌ์˜ ์ •์ฑ…์  ์˜์˜ 254 ์ œ4์ ˆ ๋ณธ ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ ๋ฐ ํ›„์† ์—ฐ๊ตฌ์— ๋Œ€ํ•œ ์ œ์–ธ 257 ํƒ์ƒ‰์  ์š”์ธ๋ถ„์„ ๊ฒฐ๊ณผ: ์ •๋ถ€์˜ ์ง€๋„ใƒป๊ฐ๋… ์ •๋„ 284 ์œ„๊ณ„์  ์„ ํ˜•๋ชจํ˜• ๋ถ„์„ ๊ฒฐ๊ณผ 285 ์กฐ์ง๊ณต๊ณต์„ฑ์— ๋Œ€ํ•œ ์ ‘๊ทผ๋ฒ• ๋น„๊ต 17 ์กฐ์ง๊ณต๊ณต์„ฑ์˜ ์ธก์ • 42 ๊ธฐ์ˆ ํ†ต๊ณ„๋ถ„์„ ๊ฒฐ๊ณผ: ์กฐ์ง๊ณต๊ณต์„ฑ 46 ์กฐ์ง๊ณต๊ณต์„ฑ ๋ณ€์ˆ˜ ๊ฐ„ ์ƒ๊ด€๊ด€๊ณ„ ๋ถ„์„ ๊ฒฐ๊ณผ 47 ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง๋ชฉํ‘œํŠน์„ฑ์— ๋Œ€ํ•œ ์‹ค์ฆ ์—ฐ๊ตฌ 58 ํ•œ๊ตญ ๊ณต๊ณต์„œ๋น„์Šค์กฐ์ง ์กฐ์‚ฌ ์—ฐ๋„๋ณ„ ๊ณต๊ณต๊ธฐ๊ด€ ์‘๋‹ต๋ฅ  70 ์‘๋‹ต์กฐ์ง๊ณผ ๋ฌด์‘๋‹ต์กฐ์ง ๊ฐ„์˜ ์ฐจ์ด์— ๋Œ€ํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ 73 ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ ์—ฐ๊ตฌ์˜ ์ฃผ์š” ๋ณ€์ˆ˜ 80 ์กฐ์ง๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ ๋ฌธํ•ญ ํƒ์ƒ‰์  ์š”์ธ๋ถ„์„ ๊ฒฐ๊ณผ 89 ์—ญํ• ๋ชจํ˜ธ์„ฑ ๋ฌธํ•ญ ํƒ์ƒ‰์  ์š”์ธ๋ถ„์„ ๊ฒฐ๊ณผ 91 ์—ฐ์†ํ˜• ๋ณ€์ˆ˜ ๊ธฐ์ˆ ํ†ต๊ณ„๋ถ„์„ ๊ฒฐ๊ณผ: ์กฐ์ง๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ 92 ์ด์‚ฐํ˜• ๋ณ€์ˆ˜ ๊ธฐ์ˆ ํ†ต๊ณ„๋ถ„์„ ๊ฒฐ๊ณผ: ์กฐ์ง๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ 93 ์ƒ๊ด€๊ด€๊ณ„๋ถ„์„ ๊ฒฐ๊ณผ: ์กฐ์ง๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ 93 ์ผ๋ฐ˜ํšŒ๊ท€๋ถ„์„ ๊ฒฐ๊ณผ: ์กฐ์ง๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ 95 ์œ„๊ณ„์  ์„ ํ˜•๋ชจํ˜• ๋ถ„์„ ๊ฒฐ๊ณผ: ์กฐ์ง๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ 97 ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ ๊ฐ„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ 98 ๊ฒฝ์˜ํ‰๊ฐ€์ œ๋„์˜ ์ ์šฉ์— ๋”ฐ๋ฅธ ๋ชฉํ‘œ๋ชจํ˜ธ์„ฑ(์š”์ธ์ ์ˆ˜) ์ˆ˜์ค€์˜ ์ฐจ์ด์— ๋Œ€ํ•œ t-test ๊ฒฐ๊ณผ 100 ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ์— ๋Œ€ํ•œ ์‹ค์ฆ ์—ฐ๊ตฌ 118 ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ ์—ฐ๊ตฌ์˜ ์ฃผ์š” ๋ณ€์ˆ˜ 137 ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ ๋ฌธํ•ญ ํƒ์ƒ‰์  ์š”์ธ๋ถ„์„ ๊ฒฐ๊ณผ 141 ์—ฐ์†ํ˜• ๋ณ€์ˆ˜ ๊ธฐ์ˆ ํ†ต๊ณ„๋ถ„์„ ๊ฒฐ๊ณผ: ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ 142 ์ด์‚ฐํ˜• ๋ณ€์ˆ˜ ๊ธฐ์ˆ ํ†ต๊ณ„๋ถ„์„ ๊ฒฐ๊ณผ: ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ 144 ์ƒ๊ด€๊ด€๊ณ„๋ถ„์„ ๊ฒฐ๊ณผ: ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ 145 ์ผ๋ฐ˜ํšŒ๊ท€๋ถ„์„ ๊ฒฐ๊ณผ: ๊ณ„์ธต์  ๋ถ„ํ™” 147 ์ผ๋ฐ˜ํšŒ๊ท€๋ถ„์„ ๊ฒฐ๊ณผ: ์ง‘๊ถŒํ™” 148 ์ผ๋ฐ˜ํšŒ๊ท€๋ถ„์„ ๊ฒฐ๊ณผ: ๊ณต์‹ํ™” 149 ์ผ๋ฐ˜ํšŒ๊ท€๋ถ„์„ ๊ฒฐ๊ณผ: ๋ ˆ๋“œํ…Œ์ดํ”„ 151 ์œ„๊ณ„์  ์„ ํ˜•๋ชจํ˜• ๋ถ„์„ ๊ฒฐ๊ณผ: ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ 155 ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ๊ด€๋ฃŒ์ œ์  ์กฐ์ง๊ตฌ์กฐ ๊ฐ„์˜ ๊ด€๊ณ„ ๋ถ„์„ ๊ฒฐ๊ณผ 156 ์ •์ฑ…์ˆ˜๋‹จ์˜ ์†์„ฑ์— ๋”ฐ๋ผ ์˜ˆ์ƒ๋˜๋Š” ์„ฑ๊ณผํšจ๊ณผ 175 ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ์— ๋Œ€ํ•œ ์‹ค์ฆ ์—ฐ๊ตฌ(๊ตญ์™ธ) 183 ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ์— ๋Œ€ํ•œ ์‹ค์ฆ ์—ฐ๊ตฌ(๊ตญ๋‚ด) 189 ์†Œ์œ ๊ถŒ์  ๊ณต๊ณต์„ฑ๊ณผ ํšจ์œจ์„ฑ ๊ฐ„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ์‹ค์ฆ ์—ฐ๊ตฌ 192 ์†Œ์œ ๊ถŒ์  ๊ณต๊ณต์„ฑ๊ณผ ๋‹จ์œ„๋‹น ๋น„์šฉ ๊ฐ„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ์‹ค์ฆ ์—ฐ๊ตฌ 195 ์†Œ์œ ๊ถŒ์  ๊ณต๊ณต์„ฑ๊ณผ ๊ธฐํƒ€ ์„ฑ๊ณผ ์ฐจ์› ๊ฐ„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ์‹ค์ฆ ์—ฐ๊ตฌ(๊ตญ์™ธ) 198 ์†Œ์œ ๊ถŒ์  ๊ณต๊ณต์„ฑ๊ณผ ๊ธฐํƒ€ ์„ฑ๊ณผ ์ฐจ์› ๊ฐ„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ์‹ค์ฆ ์—ฐ๊ตฌ(๊ตญ๋‚ด) 200 ์žฌ์ •์  ๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ์‹ค์ฆ ์—ฐ๊ตฌ 201 ํ†ต์ œ ๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ์‹ค์ฆ ์—ฐ๊ตฌ 204 ์ฃผ๊ด€์  ์กฐ์ง์„ฑ๊ณผ ๋ณ€์ˆ˜๋“ค ๊ฐ„์˜ ์ƒ๊ด€๊ด€๊ณ„ ๋ถ„์„ ๊ฒฐ๊ณผ 217 ์ฃผ๊ด€์  ์„ฑ๊ณผ(๋‚ด๋ถ€) ๋ฐ ๊ฐ๊ด€์  ์„ฑ๊ณผ ๊ฐ„์˜ ์ƒ๊ด€๊ด€๊ณ„ ๋ถ„์„ ๊ฒฐ๊ณผ 220 ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ ์—ฐ๊ตฌ์˜ ์ฃผ์š” ๋ณ€์ˆ˜ 223 ์กฐ์ง์„ฑ๊ณผ ๋ฌธํ•ญ ํƒ์ƒ‰์  ์š”์ธ๋ถ„์„ ๊ฒฐ๊ณผ 228 ์—ฐ์†ํ˜• ๋ณ€์ˆ˜ ๊ธฐ์ˆ ํ†ต๊ณ„๋ถ„์„ ๊ฒฐ๊ณผ: ์กฐ์ง์„ฑ๊ณผ 230 ์ƒ๊ด€๊ด€๊ณ„๋ถ„์„ ๊ฒฐ๊ณผ: ์กฐ์ง์„ฑ๊ณผ 232 ์ผ๋ฐ˜ํšŒ๊ท€๋ถ„์„ ๊ฒฐ๊ณผ: ํšจ๊ณผ์„ฑ 234 ์ผ๋ฐ˜ํšŒ๊ท€๋ถ„์„ ๊ฒฐ๊ณผ: ํ˜•ํ‰์„ฑ 235 ์ผ๋ฐ˜ํšŒ๊ท€๋ถ„์„ ๊ฒฐ๊ณผ: ์ ˆ์ฐจ์  ๊ฐ€์น˜ 236 ์ผ๋ฐ˜ํšŒ๊ท€๋ถ„์„ ๊ฒฐ๊ณผ: ํšจ์œจ์„ฑ(๋น„์šฉ๋Œ€๋น„๋‹น๊ธฐ์ˆœ์ด์ต) 237 ์ผ๋ฐ˜ํšŒ๊ท€๋ถ„์„ ๊ฒฐ๊ณผ: ํšจ์œจ์„ฑ(๋น„์šฉ๋Œ€๋น„๋งค์ถœ์•ก) 239 ์œ„๊ณ„์  ์„ ํ˜•๋ชจํ˜• ๋ถ„์„ ๊ฒฐ๊ณผ: ํšจ๊ณผ์„ฑ, ํ˜•ํ‰์„ฑ, ์ ˆ์ฐจ์  ๊ฐ€์น˜ 242 ์กฐ์ง๊ณต๊ณต์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ ๊ฐ„์˜ ๊ด€๊ณ„ ๋ถ„์„ ๊ฒฐ๊ณผ 243 ๋ณธ ์—ฐ๊ตฌ๊ฒฐ๊ณผ์˜ ์ข…ํ•ฉ 249 ๋ณธ ์—ฐ๊ตฌ์˜ ๋ถ„์„ํ‹€ 11Docto

    Laparoscopic management of asymptomatic ovarian steroid cell tumors, not otherwise specified: A case report and literature review

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    The steroid cell tumor, not otherwise specified, constitutes only 0.1% of ovarian malignancies and was asymptomatic in 3.3-25% In Korea, three reported cases of steroid cell tumors were endocrinologically symptomatic and were managed with laparotomy. However, there was no reports of such case without any endocrinologically symptoms. We present a 17 years old patient with huge pelvic mass that were managed with combined ultrasonographically guided drainage and laparoscopically excision and proven to be an asymptomatic steroid cell tumor of ovary, with brief review of literatureope

    Effect of cholesterol depletion on interleukin-8 production in human respiratory epithelial cells

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    PURPOSE: The lipid entities of cell membranes are components of the immune system and important mediators of inflammation. Despite increasing interest in the function of epithelial cells in inflammation, the role of cholesterol in this process has not been described. Here, we investigated the effect of cholesterol depletion on the inflammatory process in airway epithelial cells via the expression of interleukin (IL)-8 as a marker of inflammation. METHODS: A 549 cells were treated with 0.5% methyl-ฮฒ-cyclodextrin as a selective cholesterol extractor. The IL-8 level was assessed by enzyme-linked immunosorbent assay and reassessed after cholesterol repletion. Mitogen-activated protein kinase (MAPK) inhibitors were used to determine the upstream signaling pathway for IL-8 production in cholesterol-depleted cells. RESULTS: We found a relationship between the amount of cholesterol in A 549 cells and inflammation of the airway. IL-8 production was increased in cholesterol-depleted A 549 cells and restored by cholesterol repletion. IL-8 production was decreased by pretreatment with the extracellular signal-regulated kinase (ERK) inhibitor U0126 but not with JNK inhibitor II or the p38 MAPK inhibitor SB202190. CONCLUSIONS: Our findings suggest that inflammatory responses are increased in cholesterol-depleted epithelial cells via the MAPK signaling system, predominantly by the ERK pathway. We conclude that the lipid components of airwayepithelial cells may play a role in the inflammatory processope

    Production of Egg Yolk Antibodies Specific to House Dust Mite Proteins

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    PURPOSE: House dust mites (HDMs) are an important source of indoor allergens associated with asthma, rhinitis and atopic dermatitis. Chicken immunoglobulin (Ig) Y is known to be a good alternative to mice and rabbit antibody production. In this study, we produced IgYs specific to HDMs and investigated their IgE immunoreactivities. MATERIALS AND METHODS: Total IgYs were isolated from the yolks of White Leghorn hens immunized with either Dermatophagoides pteronyssinus or D. farinae protein extract. Control antibodies were separated from the yolks of immunized hens with phosphate buffered saline. IgYs specific to HDMs were analyzed using enzyme-linked immunosorbent assay and Western blotting analysis. RESULTS: The concentration of egg IgY specific to D. farinae in an immunized hen increased and the highest achieved was 661.3 ug/mg (per an egg) on day 47, compared with 760 ug/mg IgY specific to D. pteronyssinus on day 16. The D. pteronyssinus or D. farinae-specific IgY was detected by binding of each mite proteins, and their immunoreactivities were elevated dependent of the specific IgY concentration. CONCLUSION: IgY specific to HDMs may be a promising antibody for immunological diagnosis as well as identification of possible resistance relating to HDM allergy.ope

    Prognostic factors for predicting spontaneous pregnancy after Laparoscopic surgical treatment of endometriosis

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    Objective: To identify the prognostic factors for predicting spontaneous pregnancy after laparoscopic surgical treatment of endometriosis. Methods: Retrospective analysis was performed in 82 patients who underwent elective laparoscopic surgery with subsequent pathological confirmation of the endometriosis at Gangnam Severance Hospital from January 2003 to March 2008. We investigated the spontaneous pregnancy rate during the 12 months following surgical treatment and administration of Gonadotropin-Releasing Hormone agonist (GnRH agonist). Factors associated with clinical characteristics, blood tests and operative findings were compared with pregnant and non-pregnant women. Results: The number of patients succeed to spontaneous pregnancy was 32 and failed to pregnancy was 50. Cumulative pregnancy rate was 39.02%. Mean pregnancy duration after surgical treatment was 5.96ยฑ3.43 months. r-AFS stage or grouping into two stages (mild/severe) (P=0.018), r-AFS score (P=0.008) and cul-de-sac obliteration (P=0.038) was significantly different between pregnant and non-pregnant group. Complete cul-de-sac obliteration was the independent factor of pregnancy failure in women with endometriosis after laparoscopic surgery. Conclusion: Complete cul-de-sac obliteration may be the important factors for predicting spontaneous pregnancy outcome in women with endometriosis after laparoscopic surgical treatmentope

    The roles of thioredoxin and thioredoxin-binding protein-2 in endometriosis

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    BACKGROUND: Oxidative stress is considered to be involved in the establishment and development of endometriosis. Thioredoxin (TRX) is an endogenous redox regulator that protects cells against oxidative stress, and TRX-binding protein-2 (TBP-2) is a negative regulator of TRX in the biological function and expression. The aim of this study was to investigate the roles of TRX and TBP-2 in the pathophysiology of endometriosis. METHODS: A total of 35 patients with histologically confirmed endometriosis and 31 patients without endometriosis participated in this study. Real-time polymerase chain reaction was used to quantify TRX and TBP-2 mRNA levels, and immunohistochemistry (IHC) was used to assess TRX and TBP-2 protein localization in the endometrium. Serum and peritoneal fluid levels of TRX and TBP-2 were measured using a specific commercial ELISA. RESULTS: There were no significant differences in TRX mRNA levels in the endometrium of patients with endometriosis and the control groups. However, TBP-2 mRNA levels in the endometrium were lower, and the TRX to TBP-2 ratio was higher in patients with endometriosis than in the control group. In particular, the TRX to TBP-2 ratio was significantly higher during late secretory and menstrual phase in patients with endometriosis compared with the control group. IHC studies also showed the decreased TBP-2 immunoreactivity in patients with endometriosis compared with the control group. There was no correlation between TRX and TBP-2 mRNA levels in patients with endometriosis, whereas TRX mRNA levels were positively correlated with TBP-2 mRNA levels in the control group. There were no significant differences between the two groups in TRX and TBP-2 levels in serum or peritoneal fluid. CONCLUSIONS: Aberrant expression of TRX and TBP-2 in the endometrium may be associated with the establishment of endometriosisope

    Involvement of human histamine N-methyltransferase gene polymorphisms in susceptibility to atopic dermatitis in Korean children.

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    PURPOSE: Histamine N-methyltransferase (HNMT) catalyzes one of two major histamine metabolic pathways. Histamine is a mediator of pruritus in atopic dermatitis (AD). The aim of this study was to evaluate the association between HNMT polymorphisms and AD in children. METHODS: We genotyped 763 Korean children for allelic determinants at four polymorphic sites in the HNMT gene: -465T>C, -413C>T, 314C>T, and 939A>G. Genotyping was performed using a TaqMan fluorogenic 5' nuclease assay. The functional effect of the 939A>G polymorphism was analyzed. RESULTS: Of the 763 children, 520 had eczema and 542 had atopy. Distributions of the genotype and allele frequencies of the HNMT 314C>T polymorphism were significantly associated with non-atopic eczema (P=0.004), and those of HNMT 939A>G were significantly associated with eczema in the atopy groups (P=0.048). Frequency distributions of HNMT -465T>C and -413C>T were not associated with eczema. Subjects who were AA homozygous or AG heterozygous for 939A>G showed significantly higher immunoglobulin E levels than subjects who were GG homozygous (P=0.009). In U937 cells, the variant genotype reporter construct had significantly higher mRNA stability (P<0.001) and HNMT enzyme activity (P<0.001) than the common genotype. CONCLUSIONS: Polymorphisms in HNMT appear to confer susceptibility to AD in Korean children.ope
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