This is the final draft before the publisher's proofreading.

Cross-National and Longitudinal Survey

Cultural Manifold Analysis
on National Character
Methodology of Cross-National and Longitudinal Survey

Content
Preface
1 History of the Japanese National Character Survey (JNCS)
1 Postwar Democracy--- From Statistics for War to Statistics for Peace
1.1 Birth of “Statistical Mathematics” --- Philosophy of Statistics
1.2 New Mission for Democracy
1.2.1 Reorganization of Official Statistics
1.2.2 Japanese Literacy Survey
1.2.3 Establishment of Public Opinion Poll
1.2.4 Resident Surveys under the 1945-1952 Occupation by USA
2 The Japanese National Character Survey (JNCS) since 1953
2.1 History, Theory and Practice2.1.1 Kameda’s Simple Random Sampling Theory
2.1.2 Multi-Stage Stratified Sampling of JNCS
2.1.3 Installment of JNCS
Summary of Chapter 1
2 Findings of the Japanese National Character Survey (JNCS)
1 Start of a Longitudinal Survey
2 Early Data Analysis on Surveys1953-1978
3 Data Analysis as of 2005
4 Overview for 65 Years (1953-2018)
4.1 Overview
4.2 Gender
4.3 Life Style
4.4 Humans and Nature
4.5 Worry about Nuclear Power Plant Accidents1[ここに入力]

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4.6 Self-identified Social Stratums
4.7 Reward for one’s Serious Efforts
4.8 Japanese People's Fundamental Religious Consciousness andBelief in the Existence of Soul
4.9 “Obake Chosa” (Ghost Survey) -- “Rational” and “Non-Rational” Types
Summary of Chapter 2
3 Cross-National Comparative Survey of People’s Consciousness
1 History and Tasks of Our Cross-National Survey
1. 1 New Development of JNCS
1.2 Translation and Back-Translation
1.3 Sampling Methods
1.3.1 Various Sampling Methods
1.3.2 Face-to-Face Survey and Survey Culture
2 Paradigm of Cross-National Comparison
2.1 Cultural Link Analysis (CLA) and Cultural Manifold Analysis (CULMAN)
2.2 People’s Way of Thinking
2.3 Hayashi’s Quantification Method III (QM III)2.3.1 QM III for Cross-National Comparison
2.3.2 Uni-dimensional Scaling & QM III
3 Procedure of Cross-National Survey--- Designing a Questionnaire & Sampling, Pretest, Nationwide Survey, Data
Cleaning, and Data Analysis
4 People’s General Response Tendencies
4.1 Some Observations on Response Tendency
4.2 Cross-National Difference of Choice of Middle Categories
4.3 Degrees of Self-Disclosure – National Difference and Gender Difference
Summary of Chapter 3
4. Development of CLA & CULMAN
1 Early Comparative Analysis of Japanese, overseas Nikkei, and Westerners
1.1 “Giri-ninjyo” Scale: Measurement of Japanese-ness
1.2 Tradition versus Modernization
1.3 Leadership1.4 Science and Heart/Mind
1.5 Nature
2 Interpersonal Trust, Institutional Trust and Other Social Values
2.1 Trust and People2[ここに入力]

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2.2 Sense of Interpersonal Trust of the Japanese
2.3 Cross-National Comparison of Trust, and Universal Social Values
2.3.1 Sense of Interpersonal Trust
2.3.2 Trust of Social Institutions and Systems
2.4 Sense of Trust among Japanese Immigrants and Ethnic Differences
2.5 Universal Social Values on Human Bonds
2.6 For Future Study of Trust
Summary of Chapter 4
5 Further Development of CULMAN: Extension of Comparability
1 Recategorizations of Responses to Reduce Biases of General Response Tendencies
2 Connection between Overlapping Local Charts Across Time Differences
3 Universality of Values
4 Resolution of Intrinsic Difference of Religion in East and West
5 QMIII on GSS 3 Items of Trust
6 Local Charts of International Political Relationships
7 For Future Development -- Some Discussion on Survey Cooperation Rates
Summary of Chapter 5
6 Conclusion -- For Future Development
1 Survey Research for the Mutual Understanding for the World
2 Global Cultural Manifold
3 Democracy3[ここに入力]

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Preface“Cross-National Comparative Survey is a treasure trove of social surveys.”(Chikio Hayashi, 1984a [2011 reprint, p.158]. Translated by the present author.)
The late Chikio Hayashi (1918-2002), a leading figure of Japanese statistics since the postwar period,
once mentioned this after a long experience of survey research. As a key member of the Institute of
Statistical Mathematics (ISM), he has initiated and developed a longitudinal and international
comparative survey by ISM for more than half a century. The present author has been a member ofthe survey team for the past three decades.
In this book, I will explain about our past surveys and a paradigm called “Cultural Manifold
Analysis (CULMAN)” that have been developed for the longitudinal and cross-national comparative
research under the statistical philosophy of “Data Science.”
Some explanation is needed here to distinguish the “ Data Science “ from the “data science” recently
used in the fields such as AI, IT, or big data technologies. This term was coined by Hayashi in the
1980s. At a keynote speech by the International Classification Society (IFCS) held in Kobe in 1996,
Hayashi explained that conventional hypothesis testing, numerical models, and statistical models were
not suitable to the study of complex and ambiguous phenomena such as human science and social
science. And he proposed to construct “ Data Science “ based on a data-driven, exploratory andholistic approach that deals with such complex and ambiguous phenomena (Hayashi, 1998a; Osumi,2003).
In the postwar period (1945-1955), the members of ISM worked for reorganizing statisticalsystems of the government and civil sections including mass media polls and marketing research inorder to recover national economy and develop post-war democracy in the devasted country. Among
various works, Hayashi started the Japanese National Character Survey (JNCS) with his colleagues,
Hiroshi Midzuno, Hirojiro Aoyama and Shigeki Nishihira in 1953. This survey has lasted now morethan 60 years. To my knowledge, this is the longest lasting statistically random sampling survey ofpeople's consciousness. And Hayashi and Nishihira expanded it into cross-national research in the
1970s, when Japan was close to the peak of rapid industrial development. Meanwhile Hayashi had
been the leader of the Japan Statistical Society, contributed to the cabinet policymaking of several
prime ministers, and served as presidents of many national and international academic communities.
Not surprisingly, all these experiences are closely linked to the birth of the “ Data Science “ (Hayashi,
1998a, 2001b), which is expected to contribute mainly to the practical solution of various social
problems.
Scientific measurements can be thought of as the interaction between the observer, the observed
object, and the representation of the measurement system (i.e., as models, theories, statistical graphs,4[ここに入力]

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and tables). No matter how good a model or theory is, it cannot be considered a reality in itself. It's
just one of the possible expressions of reality. The model or theory is the “finger pointing to themoon” in Zen teaching. The finger itself is not the “moon”, but it helps others understand what andwhere the moon is. We have created “Cultural Manifold Analysis (CULMAN)” as a “finger” forothers to understand our survey research.
JNCS include dozens of questions. Here is an example of question in JNCS. “If you were born
again, would you like to be born as boy or girl?” Figure A shows the stability of Japanese men’s
response “boy” (some 90%) as well as the significant change of the Japanese women’s response from“boy” to “girl,” in the past 60 years. This question is directly related to the issue of gender equality.
But among other questions, it may seem to symbolize the steady change in social situations since thepostwar period in Japan (See Chapter 2 for details).

However, before jumping to any particularinterpretation on the distribution of response data, it is better to understand and the holistic changes inthe social systems, social values, and international relations behind the survey data. For reference,
see Figure B1 and B2 of the Asia-Pacific Values Survey.

Countries seem to exhibit their own

modalities closely related to their history and politics.
*** Figure A Japanese Answers

Boy or Girl ? ***’*** Figure B1 Men’s Answers in APVS ***’*** Figure B2 Women’s Answers in APVS ***’
Another example shows the change of Japanese social values. The question is” What is the mostimportant thing for you? (Open-ended question).” As shown in Figure C, the response rates of “life”,“health”, “oneself,” “love”, and “child(ren)” show relative stability; the rate of “family” shows the
rapid increase.
*** Figure C Most important thing for yuo ***’The data may have several possible interpretations. It would be even more interesting if it could becompared to cross-national data. However, scientific comparison between countries is not a simple
matter of comparing response distributions superficially. Due to differences in sampling methods,
languages, history, culture and ways of thinking, some essential problems must be overcome. The
obvious problem is to translate the question into different languages without losing semantic
equivalence.

Another issue is that due to differences in social survey infrastructure (including

political restrictions), countries need to use different statistical sampling techniques.
5

This is not[ここに入力]

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negligible for cross-national comparisons. Among them, one of the most difficult problems is thedifference in general response tendency. People in countries like the United States usually answer
clearly with “yes” or “no,” while people in other countries like Japan often give ambiguous answers.
Scientific cross-national research must overcome these problems. However, our past studies lead us
to the recognition that studying these issues themselves reveals important national characteristics
beyond the superficial comparison of response data.
The world in 2020 began with the coronavirus turmoil from China. Differences in government
behavior, media coverage, scientist activity, and people's panics clearly reflect differences in values
and attitudes towards life, science, and the political system.
Over the past 65 years, our research team has collected statistical random sampling data of people's
awareness and opinions with development of our paradigm to justify longitudinal and cross-national
research. The purpose of our research is to promote mutual understanding of people's attitudes,
behavioral manners, religion, and values. Although our work is still under construction, an overview
of past work may give the reader some ideas for further development. I am a survey statistician witha background in mathematical psychology and psychometrics, but I'm not an expert in anthropology,sociology, or international relations. Therefore, I may need to refrain from developing substantive
discussions for those empirical sciences. However, I believe that experts in a variety of disciplines,
such as economics, politics, religion, sociology, and international relations, can use our data to find
new ways to advance their own research.
The ancient Chinese martial artist Sunji said, “If you know the enemy and you know yourself, you
are not in danger of 100 battles. It is best to win without fighting.” To the people of other countries,
the Japanese attitude may often seem vague. This may be derived from the principles that are deeply
ingrained in the Japanese (self-restraint of behavior, self-restraint of freedom). Mutual understandingis the key to avoiding unnecessary conflicts between countries. To that end, it is important to strive
to make other countries understand our values and ideas.
I hope this book will help expedite empirical social science and evidence-based policy making forworld peace and prosperity.
Acknowledgement
I would like to thank the many collaborators who have guided me in many surveys and carried out
the surveys with me over the past thirty years. I am deeply grateful to Akinori Okada for giving me
the opportunity to publish this book. I would like to thank Chikio Hayashi, Tatsuzo Suzuki, Fumi
Hayashi, Kazue Yamaoka, Masamichi Sasaki, Yoshiyuki Sakamoto, and Zheng Yuejun for developing
the survey research.
I am deeply grateful to my advisors when I was a graduate student at the University of California,
Irvine. Tarow Indow, William H. Batchelder, Louis E. Narens, Donald D. Hoffman and Bruce M.
Bennett influenced me to develop the philosophy on the methods of empirical science, theory6

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construction, and measurement theory in mathematical psychology. My old friends, Paul Shirey,
Scott Simpson, Nancy Mear, Vincent Brown, Frank Pollick, Gregory B. Pollock, Kimberly A. Jameson,
and Eri Tatekawa also supported me.
I cordially appreciate Mr. Yutaka Hirachi, Ms. Shinko Mimura and Mr. Sridevi Purushothaman at
Springer Nature for their assistance for publishing this volume.
This book is dedicated to my parents, Mitsu Yoshino and Kinjiro Yoshino, and to my brother Kotaro
Yoshino.
Note) This book introduces various survey data collected by the Institute of Statistical Mathematics(ISM). For details of the questionnaire, survey method, and total of each survey, please refer to theseries of ISM Survey Reports and related websites.
1) http://www.ism.ac.jp/editsec/kenripo/index.html (ISM Survey Research Reports in Japanese).
2) http://www.ism.ac.jp/editsec/kenripo/index_e.html (ISM Survey Research Reports in English)3) http://www.ism.ac.jp/ism_info_j/kokuminsei.html (JNCS in Japanese)4) http://www.ism.ac.jp/ism_info_e/kokuminsei_e.html (JNCS in English)5) http://www.ism.ac.jp/~yoshino/ap2/index.htm (ISM Cross-National Studies in Japanese)6) http://www.ism.ac.jp/~yoshino/index_e.html (ISM Cross-National Studies in English)
Among the cross-national data, the following data are frequently used in this book..
7) The Seven Country Survey (1987-1993) (Hayashi et al., 1998).
https://www.ism.ac.jp/editsec/kenripo/contents_e.html (ISM Survey Report, No.63, 64, 70-73, 7582)
https://www.ism.ac.jp/~yoshino/arito/eg/top_e.htm (Website 1)
https://www.ism.ac.jp/~yoshino/data/1_e.html(Website 2)8) The East Asian Value Survey (EAVS) (1992-1995) (Yoshino, 2006)
https://www.ism.ac.jp/~yoshino/sr/index.html (Summary Report)
https://www.ism.ac.jp/~yoshino/ea/index_e.html (Website)9) The Pacific-Rim Value Survey (PRVS) (2004-2009) (Yoshino 2010).
https://www.ism.ac.jp/~yoshino/sr/index.html (Summary Report)
https://www.ism.ac.jp/~yoshino/pr/index_e.html (Website)10) The Asia-Pacific Value Survey (APVS) (2010-2014) (Yoshino, Shibai & Nikaido, 2015).
https://www.ism.ac.jp/editsec/kenripo/pdf/kenripo117.pdf (Summary Report)
https://www.ism.ac.jp/~yoshino/ap2/index_e.html (Website)
For a detailed list of publications11) https://www.ism.ac.jp/~yoshino/references_e.html
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Chapter 1 History of the Japanese National Character Survey (JNCS)
All survey studies are woven by the trinity of history, and theory and a practical method of theresearch, and should not be described only by superficial data. Therefore, I start this book by abrief history.
Most of today's statistics sampling survey systems for Japanese official and private sectors havebeen established as joint research by experts from various fields, led by the Institute of Statistical
Mathematics in the decade after WWII.

Those experts gathered to work for post-war national

economic recovery and peace.

1 Postwar Democracy--- From Statistics for War to Statistics for Peace
1.1 Birth of “Statistical Mathematics” – Philosophy of Statistics“Statistical mathematics” is a philosophy that began in the field of Japanese statistics since the early
1940s. Traditional “mathematical statistics” rely on the mathematical assumptions of probability
distribution theory which are almost impossible to verify directly. Several groups of statisticians
criticized this and aimed to develop new statistical approaches to solving social problems in a practicalway (Midzuno, 2003, pp.191-192).

Since then, this idea has successively developed as a

“Quantification Method” in the 1950s and 1960s, “Multidimensional Data Analysis”,“Behaviormetrics”, and “Science of Survey” in the 1970s and 1980s, and “Science of Data” since the1990s (Hayashi, 1998a, 2001b, Yoshino, 2001b; Yoshino & Hayashi, 2002; Yoshino, Hayashi &Yamaoka, 2010).
Unfortunately, this new philosophy of statistics was once incorporated into war in the course of thetimes. In 1943, during the war, the Academic Research Council established the Institute of Statistical
Sciences with a focus on statistical mathematics. After the Cabinet's decision in 1944, the Instituteof Statistical Mathematics, under the control of the Minister of Education, took charge of the study ofmathematics and its applications related to probability and promoted the research. Soichi Kakeya,
professor at Tokyo Imperial University at the time, served the post of director-general.
It was the era when universities and research institutes all over Japan were incorporated into awartime system called total war.

For my generation born after the war, the details of what theInstitute did at the time are almost unknown. But it is said that they were engaged in decryption orwhat is now called operations research (Inose, 1983; Kimura, 2002; Yoshino, in press).
1.2 New Mission for Democracy
1.2.1 Reorganization of Official Statistics
Under the US occupation after the war, the institute was reorganized into the 1st Research Department(basic theory), the 2nd Research Department (natural science statistical theory), and the 3rd research
department (statistical theory social science) in April 1946. This reorganization was related to Rice8

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Statistics Mission's recommendation from the United States in December 1946.
ISM members reportedly believed that the institute created for strategic research would be abolishedunder the post-war occupation.

Therefore, when the people from GHQ / SCAP (Headquarters

General, Allied Supreme Commander) arrived, they thought the institute would soon be abolished(Hiroshi Midzuno, 1991 [Personal Communication]). However, the United States had a detailed
understanding of human resources in various areas of Japan, including information from interrogating
Japanese prisoners of war (Nakata, 2010). And they used Japanese experts from various fields tocreate a new democracy and restore the economy and industry. Thus, the institute was given a new
mission to take the lead in reorganizing official (governmental) statistics and in establishing a methodof scientific opinion polling as the basis for the development of postwar democracy.
Chikio Hayashi, later a director-general of ISM but a then young member, was dispatched with
Hiroshi Midzuno to the Ministry of Finance as a member of the Institute of Statistical Mathematics.
There they handled a variety of large data. Midzuno was a senior to Hayashi in the Department ofMathematics at the University of Tokyo. And he inspired his intimate life-long friend Hayashi todevelop new statistics.
Through this experience at the Ministry of Finance, Hayashi and Midzuno confirmed that real data
could not always be on normal distribution even if the sample size of the data is large. This can be
an important basis for criticizing the armchair theory of mathematical statistics.

Then, in theprocesses of solving real-world problems such as market research, personnel management, andcriminal law issues, Hayashi collaborated with Midzuno to build “Hayashi's Quantification Theory.”
The most striking feature of the theory is that it does not assume a priori probability distribution ofvariables. This frees us from mathematical assumptions that cannot be checked directly (Hayashi,
1993a; Midzuno, Hayashi & Aoyama, 1953; Morimoto, 2005, 2012; Takahashi , 2002b).
Incidentally, after the war, Hayashi obtained the US military OR (operations research) textbook“Methods of Operations Research” (Morse & Kimball, 1946). And he found that Americans had
thought the same in their military operational studies and had reached similar conclusions as theJapanese (Maruyama, 2015).
In this way, Japanese researchers took off military uniforms, began reorganization of government
statistics, developed statistical marketing surveys for economic recovery for the reconstruction ofdestroyed land, and established a scientific opinion poll system for democracy. On the other hand,
the U.S. government, ending the occupation in 1953, believed that a reliable and rigorous statisticalsystem had been established so that they could constantly monitor Japan from Washington and respond
immediately in the event of an emergency (Kondo, 1953, p.15). In those days, the US government
did not seem to believe democratization of the Japanese. Besides, in the start of cold war, they needed
to monitor people’s movements including residents near the US military bases in Japan. During theVietnam War, the US military bases faced severe opposition from the residents.
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1.2.2 Japanese Literacy Survey
In the history of postwar surveys, it is important to explain about the “Japanese Literacy Survey” as
the first nationwide statistical random sampling.
In policymaking during the US occupation, there was some argument in the US government andmilitary that Japanese use of esoteric kanji (Japanese version of Chinese characters) prevent them fromdeveloping their academic abilities and democracy. On this matter, in 1948, a nationwide statisticalrandom survey was conducted to investigate the literacy of Japanese people. The result turned out thatJapanese people had sufficient literacy to develop democracy. Thus, the Japanese language was saved(Hidano, 2018; Yomi-kaki-nouryoku-tyousa-iinnkai, 1951).
“Romanization” (abolishment of “kanji” and use of alphabet) has been strongly insisted by Major
Robert King Hall of the GHQ Civic Information and Education Agency (CIE) without any
coordination with the US government.

He seems to have conceived this idea through his own

difficult experiences of learning Japanese at the time of Princeton University and the Naval Academy.
However, Gordon T. Bowles, Advisor to the Education Mission of the State Department, believed that
language reforms should be left to Japan and should not be enforced externally. And Hall was left
out of this matter.

After all, the results were in agreement with the report from Tokyo Imperial

University Educational System Research Committee to President Shigeru Nambara (Kayashima,
2000; Unger pp.79-81, 1996). In fact, there was a complicated background, such as censorship under
the occupation and conflicting views within the U.S. government and the military. However, at leaston the surface, it provided a model for policy-making based on a scientific survey of stakeholder intent.
In addition, this provided a model to check statistical random sampling theory and its practice.
Prior to this survey, an exhaustive survey (almost 100% valid return rate from the target population of
more than 20,000) was conducted in some cities such as Odawara City of Kanagawa Prefecture.
Because each city of Japan has almost complete list of the residents (then a list of Food Distribution
Books made for governmental control of distribution of food during WWII), so they used the list fora certain statistical random sample from the total population (stratified multi-stage sampling). Next,
the distribution of literacy scores across the population was compared to the estimated distribution ofscores obtained from statistical random samples. The estimated score was close to the true score within
the theoretical sampling error calculated according to the sample size (eg, 1000 or 3000 respondents
from the total population). After this confirmation, this sampling method was extended to apply tothe nationwide survey (For more details, see Yomikaki-nouryoku-iinnkai [1951]).
1.2.3 Establishment of Public Opinion Poll
The method invented for the Japanese Literacy Survey provided a model for later rigorous statisticalsurveys, including resident survey, marketing survey, public poll survey, surveys to forecast election
10

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outcomes, etc. (Later, they began to use a list of registered residents or voters rather than a list offood distribution books.) Of course, the governmental surveys started to use the method.
Usually an ordinary public poll cannot be directly checked as to whether it is conducted statisticallyadequate or not. Therefore, it is important to stick to a rigorous statistical method validated by theory
and practice, such as the Japanese Literacy Survey. But an exception that we can directly checkvalidity of a survey method is on prediction of election outcome based on public poll.
During the occupation, anthropologist John Perzel worked for the CIE (Civil Information Education
Section), which was in charge of public opinion polling in Japan. In 1947, he was surprised to knowthat a Japanese survey company, Yoron Kagaku Kyokai (Public Opinion Scientific Research Center[POSRC]), successfully predicted the winner of the highly competitive election of the governor ofTokyo metropolitan city by a statistical random sampling survey. The sample size was only 500
respondents. He knew American mass media’s failures of public opinion polls on elections such as
the 1938 presidential election. Therefore, he hardly could believe the validity of the Japanese survey
on such a small size sample. In those days, most surveys of major Japanese newspapers collected asample of more than 60,000, sometimes more than 200,000 respondents. He ordered the POSRC to
explain about the details of the survey. Eventually, however, he understood the validity of rigorous
statistical random sampling survey and admired them on the performance.
Meanwhile, Japanese researchers were surprised to learn that a US survey firm mis-predicted thewinner in the 1948 US presidential election. After studying American survey methods (quota
sampling with respect to age, gender and race), people found that Japanese sampling methods weremuch more rigorous in statistics.
The survey research of Japan was under supervision of the US, but the Japanese successfully
performed beyond the US research. However, the Japanese know that the United States, along withJapanese staff, made significant contributions to Japan during the early days of occupation, not only
for survey research but also in realizing an ideal system of social security and medical care that
could hardly have been realized in its own country.
Since the success of literacy surveys or the election predictive survey, statistical random samplinghas become more and more dominant in surveys by governments, mass media, marketing
researchers, academic researchers, and others.
1.2.4 Resident Surveys under the 1945-1952 Occupation by USA
It may be worthwhile writing about some resident surveys in islands such as Amami-Oshima Island
and Okinawa Island in the occupation time.

With Japanese cultural anthropologists, Hiroshi

Midzuno (a member of ISM) was engaged in the survey of Amami-Oshima (Hiroshi Midzuno, private
communication, 1991; Yoshino, Hayashi & Yamaoka, 2010) . The United States did not brief them11

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the real purpose of the survey, but totally relied on credible Japanese statisticians and anthropologists
to conduct the survey. The report was classified and sent to Professor Ishino Iwao, Ohio University,
for the analysis for their own purpose. As a result of the survey, the residents of Amami had an
overwhelming sense of belonging to Japan, but the residents of Okinawa did not. (It may be natural
given cruel actions of the Japanese military to Okinawa residents during the war.) It was the timethat complicated international relations were seen, such as the resident movement and the start of cold
war between the USA and the Soviet Unions. After all, Amami Oshima returned to Japan several
years after the war, whereas the American military base was built in Okinawa and it had been under
the US custody until 1972 (Eldridge, 2003, pp. 106-107; Takahashi, 2002a)
The United States entered the Cold War era and asked many Japanese anthropologists to survey
islands throughout Japan (The Japanese Society of Ethnology, 1952). The nine academic societies
such as anthropology, psychology and sociology were organized as an association for survey researchand they carried out many surveys (Sakano, 2012). This can be thought of as a model of the basic
spirit of intelligence: independence between the information collector and the information analyst. It
can also be said to be a model for policy making based on empirical research data collected by highly
credible local researchers.
After the war, the United States immediately disarmed Japan and demanded to enact a peacefulconstitution. Japan peacefully fulfilled its demands. However, the Soviet Union and China began
targeting the disarmed Japan. Then, the USA changed its policy and demanded Japanese rearmament
in anticipation of the Korean War (Ezaki, 2019). It became the origin of the still lasting subordinationof the Japanese government and the Japanese Self-Defense Force to the United States Military(Suenami, 2012; Tanigawa & Sudo, 2019).
Many documents on survey research during the U.S. occupation were declassified around 1990 and
returned to Japan Association for Public Opinion Research (JAPOR). The documents are currently
kept by Waseda University.
2 The Japanese National Character Survey (JNCS) since 1953
2.1 History and Theory
In 1953, the Institute of Statistical Mathematics started the “Japanese National Character Survey”,
based on the statistical random sampling method developed practically in the “Japanese Literacy
Survey” (Mizuno et al., 1992; Yoshino, 2011a, b, c).

The word “national character” may be a

problem in academics and politics, but it is used as a nickname for our research. In our terminology,“national character” refers to a characteristic that is reflected in the response patterns of people's
consciousness surveys in a country. This is closely related to Inkeles’ (1997) concept of “national
character” regarding the statistical mode of responses of people. Incidentally, as for measurementsof national character, Inkeles (1997) claimed that aspects directly related to economic or political12[ここに入力]

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conditions should not be regarded as part of the “national character.” It is reasonable, however, toassume that people of different countries may respond differently to certain economic or political items
on a questionnaire even under the same economic and political conditions, and that such differencesin response patterns may be closely related to “national character.” For example, in the late 1980s,
Brazilians showed a high degree of life satisfaction and happiness even when their country was
experiencing severe conditions regarding international debt. In contrast, the Japanese did not showa high degree of life satisfaction and happiness even when their economy was close to being the bestperforming one in the world (cf. Easterlin paradox).
Today, this survey is called one of the three major statistical sampling consciousness surveys inJapan, together with the “Shakai-ishiki ni kansuru Chosa [Social Survey on People’s Consciousness]”by the Cabinet Office and the “Nihon-jin no Ishiki Chosa [Japanese Consciousness Survey]” by NHK[Japan Broadcasting Corporation]. The team of JNCS thought that “national character” wouldn’tchange greatly over years, therefore, they didn’t necessarily assume to repeat the survey over years at
first. And many new question items were introduced in the second survey of 1958, five years after
the first survey. However, they found considerable changes in the response distributions for some ofthe same questions, recognizing the importance of conducting a longitudinal survey with the samequestion items. However, from the 8th in 1988, taking into account changes in the times, they created
two types of questionnaires: K type (continuous type) mainly consisting of the same questions and M
type (future-oriented type) which replaced some items with those to capture possible future changes
of Japanese attitudes.
This survey, which has been continuing for over 65 years (Hayashi, 1992a, 1992b; Mizuno et al.,
1992; Sakamoto, 2000; Yoshino, 1997), is a globally unique longitudinal survey supported by the
Ministry of Education. It has subsequently prompted similar types of statistical surveys in othercountries such as ALLBUS (Germany), CREDOC (France), Eurobarometer, the European Values
Survey, and the General Social Survey (GSS) in the USA. Meanwhile, many experimental researchon survey methodologies have been conducted by ISM since the 1950s.
2.1.1 Kameda’s Simple Random Sampling Theory
Regarding the theory of statistical random sampling, Toyojiro Kameda presented a theory of simple
random sampling and applied it to calculate the accuracy of sampling data on the first Japanese Census
Data (1920) in 1923. (See Note 1).

Furthermore, he applied the theory to the work of security

insurance, and also applied to the estimation of damage caused by the Great Kanto Earthquake inTokyo and its surrounding areas in 1923.

He reported the results at the 19th Conference of theInternational Statistics Institution (ISI) held in Japan in 1930 (Kawasaki, 2020, Sec.4; Takahashi, 2004,
p.109). Although it was the era of “Taisho democracy”, a peak of democracy before World War II,
his theory had never been applied to opinion polls. (Taisho era is 1912-1926. Democracy movements13[ここに入力]

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peaked in the 1910s and 20s.)
However, in the 1948 Japanese Literacy Survey, Japanese staff did not pay attention to Kameda's
work. They studied American books on statistics borrowed from the CIE library and invented apractical method of nationwide random sampling suitable for Japan.

As mentioned, officiallyregistered “food distribution books” were used to design multi-stage stratified sampling. (In later
public opinion surveys, they started to use list of resident registration or voters that are updated
regularly and are almost complete.

Compared to other countries, this gives Japan a significant

advantage in the precise estimation of sampling error of public opinion survey.)
2.1.2 Multi-Stage Stratified Sampling of JNCS
This section describes the sampling design of Japanese National Character Survey (JNCS). The basic
design has been the same, but the detailed steps have changed slightly over the years. For more
information, please refer to the homepages of Japanese National Character Survey Committee(https://www.ism.ac.jp/kokuminsei/en/page9/page10/index.html), or Mizuno, et. al (1992). The
following is from the explanation of the 13th survey (Nakamura et al., 2017).
In general, the procedure for the 13th survey was the same as for the 8th to 12th surveys. The
selection of samples for each survey was performed by a three-stage stratified stochastic sampling
method. First, we stratified boroughs, cities, towns, and villages, considering population size anddemographic variables. One administrative area was randomly selected from each level so that theprobability of selection was proportional to the size of the population.

In the 13th survey, 400

districts were selected (Stage 1). Second, from each randomly selected district, a small area called
CHO / AZA (the same as the census unit) was selected in the same way (Stage 2).

Finally,

respondents were selected from the resident register of the selected district using systematic random
sampling (Stage 3). In the 13th survey, a total of 6,400 respondents were selected.
In the 12th and 13th surveys, we refined the geographic stratification and increased the number ofsampling points and sample size (number of respondents) compared to the 8th to 11th surveys. We
also used the resident listings in the last two surveys, with some exceptions, instead of voters’ listing
previously used. Thus, the sampling point unit was a voting district in the previous surveys, but“CHO / AZA” in the recent surveys.
The surveys up to 8th one were conducted with the cooperation of many universities. In thesesurveys, districts were assigned to universities, and members of the research committee visited theuniversities and directed student interviewers. However, since the 9th survey in 1993, each survey
has been conducted with the cooperation of a private survey company.
In the case of the 13th survey, prior to the fieldwork survey, the sampling manager randomly
selected respondents from the resident registry according to the designated procedures at the city
hall. An average of 16 respondents were selected for each sampling district. Fieldwork was14[ここに入力]

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conducted from the last 10 days of October to the first 10 days of December 2013. As a result, 3,170(1,591 for the K type and 1,579 for the M type) were completed from the target sample of 6,400, andthe completion rate was 50%. Details of imcompletion rates are summarized in Tables 1 through 5 ofNakamura, et. al. (2017).
2.1.3 Installment of JNCS
In the 13th survey, the installment of the survey was entrusted to the Nippon Research Center(NRC)(Gallup International Association). However, prior to the interview, the Institute of Statistical
Mathematics (ISM) processed some of the respondent sampling from the registered resident card (80out of 400 locations in Tokyo, Osaka and two other prefectures). The researchers of NRC and ISM
responsible for sampling visited the town hall, ward office, and city hall of their town or village andsampled there from the Resident Register using a designated statistical random sampling method.
We then mailed a request form of cooperation to the sampled respondents in advance. Theinterviewer visited each house, met with the respondents directly, handed over the request from theInstitute of Statistical Mathematics, and requested cooperation. If respondents were unavailable due
to absence or other reasons, a new date and time was set for the interviewer to visit again.
When a respondent agreed to cooperate with the survey, the interviewer read the questions on thequestionnaire, and recorded the answers provided by the respondent verbatim on the questionnaire.
For questions indicated with show cards of response choices, the cards were presented to the
respondents.

If a sampled respondent didn’t agree to cooperate, the interviewer recorded it as”

refusal.” If the interviewer was unable to meet the respondent after visiting many times for somereason, the reason was recorded according to each situation, such as “temporary absence,” “longabsence,” or “moved.”15

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Note of Chapter 1
Note 1) For simple random sampling, the estimated sampling error E at a 95% confidence interval
for the percentage of a statistics in the population (e.g., the response percentage of “yes”) is given
mathematically as
E = + 1.96√（P（1－P））/ ｎ・ (N - n)/(N - 1),
where P is the response percentage in the population (0.0 < P < 1.0), N is the population size and n
is the sample size. For large N (for example, over 10,000), this is approximately equal toE ≑ + 1.96√（P（1－ P））/ ｎ.
If n is large enough, P is approximated by the observed response percentage p in the sample.
E ≑ + 1.96√（p（1－ p））/ ｎ.
This is maximized when p = 0.5. Often, the estimated sampling error is treated roughly asE ≑ + 1.96/√ ｎ.
For example, if the sample size n is 10,000, the sampling error of the estimated response
percentage is + about 2%. If the sample size n is 1,000, the sampling error of the estimatedresponse percentage is + about 6%.
In practice, you should also consider non-sampling errors (a variety of errors, including errors insampling coverage of population, recording responses, processing data, etc.). Non-sampling error
cannot be calculated accurately in theory, but it is sometimes assumed to be approximately at the levelof sampling error (Hayashi, 1984a).
In the early days when modern computers were unavailable, accurate calculations on a set of big
data was very time consuming and costly. As a result, even if a large set of data was generated by
an exhaustive survey, a tentative rough calculation was often done using a small dataset randomly
sampled from the original large set of data. Some researchers insisted that calculating statistics on
random sampling made sense only if exhaustive survey data were available. From the point ofview of modern statistics, it seems strange. It took a long time before random sampling surveys
like today became frequently used.

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Summary of Chapter 1
After World War II (late 1940s to 1950s), the government and private sector statistical systems andinstitutions were intensively reorganized as the basis for regaining national power under Japan's new
democratic regime. In 1958, the Institute of Statistical Mathematics (ISM) launched the “Japanese
National Character Survey” based on the statistically rigorous sampling method devised in the 1948
“Literacy Survey of Japan”. This survey is based on multi-layered and multi-stage statistical random
sampling from a nearly complete list of voters or residents across the country.
JNCS has been in operation for over 65 years. It is also currently known as one of the three major
longitudinal statistical consciousness surveys, together with the “Shakai-ishiki ni kansuru Chosa[Social Survey on People’s Consciousness]” by the Cabinet Office and the “Nihon-jin no Ishiki Chosa[Japanese Consciousness Survey]” by NHK [Japan Broadcasting Corporation].

The survey

motivated other countries to launch similar longitudinal general surveys, such as the General Social
Survey (GSS) in the United States, the Eurobarometer in the EU, and ALLUBUS in Germany.
JNCS was closely linked to the reorganization of official statistics and the establishment ofstatistical public opinion polls to develop Japan's postwar democracy. It also symbolizes thedevelopment of Japanese statistical philosophy such as “Statistical Mathematics”, “Quantification
method”, “Multidimensional Data Analysis”, “Behaviormetrics”, and “Science of Data”.

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Chapter２ Findings of the Japanese National Character Survey (JNCS)
1 Start of the Longitudinal Survey
Initially, the JNCS research team did not intend JNCS as a longitudinal survey because they expected
the “national character” to be stable over the long term. Thus, the second survey in 1958 introduced
many items on various topics that were not covered in the first survey in1953. However, the results
turned out to show significant differences on some of the same items used in both surveys. Thisobservation led the JNCS team to recognize the importance and necessity of conducting a longitudinalsurvey of the same items. Thus, except for some items, the same items were used as in the firstsurvey from the third survey until the fourth survey in 1968.
However, around 1970, Japan's remarkable social change required new items to capture new
aspects of the Japanese people. So, they launched two types of questionnaires: K-type (“Keizoku”[continuous]) and M-type (“Mirai” [future]). The K type consists of almost the same items as a seriesof surveys, but the M type captures new aspects by replacing some items of the K type with new items.
This idea later leads to the CLA (Cultural Link Analysis) research paradigm as it expands to crossnational research in the 1980s. (Unfortunately, the core concepts of K-type and M-type were notnecessarily well maintained, and the distinction between these questionnaire items was confused inlater surveys. Chikio Hayashi had been the leader of JNCS but retired from the Institute of Statistical
Mathematics in 1988.

After retirement from ISM, he began to focus on cross-national survey.

Therefore, the remaining members of the Japanese survey may not have fully recognized theimportance of the distinction of questionnaires in survey design.)
This section summarizes the main findings of JNCS. To understand the findings, it is helpful totake into account historical background and generational features in the Japanese character.
There are many ways to divide the period from after World War II to the present. The followingclassification is an example. (See Table 2.1).
1. GHQ Occupation Period (1945-1952)
2. Postwar Recovery and Rapid Economic Development (1952- 1973)
3. Recession and Stable Development (1973 -1986)
4. Bubbling Economy (1986 -1991)
5. Recession after the End of Cold War (1991-present).
(After collapse of Bubbling Economy)*** Table 2.1 History of Japan ERA & PERIOD **Table 2.2 shows a generational classification of the Japanese. Each generation has a nickname and18