Which Civil Society Organizations in Which Countries are Enjoying Policy-Making Processes and Why: Comparing 7 Countries (Japan, Korea, Germany, China, Turkey, Russia, and the Philippines) in JIGS Surveys 2006 Yutaka Tsujinaka, J.Y. Choe, T. Ohtomo, and H. Miwa University of Tsukuba 2 Introduction: Differences in SIS Influential 3 - Enjoy? 2.74 2.60 Philippine, Russia 2.23 Some what 2 SIS (Mean) Not - Manage? 1.74 Germany, Korea, Japan 1.52 1.01 1 0.82 - Suffer? China, Turkey 0 Philippine (PH) Russia (R) Germany (G) Korea (K) Japan (J) China (C) Fig.1 Subjective Influence Score (mean) Turkey (T) Why is SIS different? 3 Subjective influence Score (SIS) When policy problems arise in the geographical areas suggested in Q6 （1．Village, town or city; 2. Prefecture; 3.A collection of prefecture regions; 4. National; 5. Global）, how much influence does your organization have on such problems? Subjective influence Score (SIS) Extremely influential=4, influential=3, Some what influential=2, Not influential=1, Not at all influential=0 SIS (mean): Average score by country/ by sectors 4 ･Overview of CountriesSurveyed in JIGS Table 1 Overview of Countries Surveyed JIGS GDP Freedom NPS per House (CSS) Capita(n.1) rating(n.1) (n.2) （capital city data*） Volunteering NGO Subjective Subjective % Workforce Vitality Influence Influence of (n.2) (n.3) Score(n.4)ranking(n.4) SIS strong(n.4) Germany 22,740 1-1 5.9% 10% - 2.23 3 47.6 Japan 34,010 1-2 4.2% 0.5% Low 1.52 5 16.0 South Korea 9,930 1-2 2.4% 3% High 1.74 4 17.4 Turkey 2,490 3-3 - - - 0.82 7 8.6 Russia 2,130 6-5 - - - 2.60 2 63.3 Philippine 1,030 2-3 1.9% 6% High 2.74 1 62.3 960 7-6 - - Low 1.0１ 6 9.5 U.S. 35,400 1-1 9.8% 22% - - - Brazil 2,830 2-3 1.6% 6% - 380 4-4 - - High China Bangladesh N. 1:Freedom in the world 2005,n.2: Johns Hopkins CNPS Project n.3: Shigetomi 04 n.4: JIGS1(Tsujinaka project) 5 I. Methodology & Hypotheses 1. Main Characteristic of JIGS The International Survey of Civil Society and Interest Groups 1997: Cross-culturally surveys direct the core (associations) of CS in 10 countries :Different from Non Profit Sector Project (L. Salamon) and from Social Capital Group (R. Putnam) 6 Table 2 Overview of JIGS Surveys Country Year Data Source / Survey Method Population 1.Japan `97 2.Korea `97 3.USA `99 4.Germany `00 5.China 6.Turkey 7.Russia 8.Philippine 9.Brazil classified telephone directory / mail classified telephone directory / mail classified telephone directory / mail classified telephone directory, organization directory / mail “Social Groups” officially `01, registered at the Municipal ‘03 or District/Country Civil Affairs Bureau / mail Regional survey investigation ‘03 based on telephone directory / interview Registered Organization ‘03 （NGO） Database / mail Securities and Exchange Commission (SEC), ’04 Philippine Foundation Center (PFC) / interview Brazilian Institute of ‘05 Geography and Statistics (IBGE) / interview 10.Bangladesh ‘06 Telephone books, Directories 23,128 11,521 7,228 4,806 Sample Valid Return Regions (a) Response(b) Rate(%)(b/a) (Valid Return Sample) Tokyo (1,438) 4,247 1,635 38.5 Ibaraki (197) Seoul (371) 3,890 4,93 12.7 Kyonggi (110) Washington, D.C. (748) 5,089 1,492 29.3 North Carolina (752) Berlin (643) 3,074 8,85 28.8 Halle (154) 9,536 8,897 2,858 32.1 Beijing (627), Xianju (1,782), Heilongjiang (449) 15,730 Appr. 1,500 841 - Ankara ( 334 ) Istanbul ( 507 ) 2,974 1,500 711 47.4 Moscow (411) Saint Petersburg (300) 44,051 5,472 1,014 18.5 Manila (855) Cebu (159) 275,895 3,000 (est.) 1,500 (est.) 50 (est.) Brasilia,Recife,Belem (Belo Horizonte) TBC 1,500 (est.) 800 (est.) 50 (est.) Dhaka, Rajshahi 7 2. Various Hypotheses - Civil society structure (sector composition) hypothesis - Resource hypothesis - Political Activism hypothesis - Administration connection hypothesis 8 3. Method of Analysis ・Relation between factors and SIS (mean) - Analysis through Scatter Diagram (Nation Level) ：linear or non-linear - Cross Tabulation Analysis (Nation Level)：χ2-test - Cross Tabulation Analysis (Sector Level)：χ2-test (Profit Sector, Non Profit Sector, Citizen Sector, Other) 9 II. Civil Society Structure (Sector Proposition) Hypothesis ・4 Sectors’ Proportion 0% 20 % Philippine (PH) 5.1 40% 19.7 60 % 80 % 46.6 100% 100 28.7 0.6 Russia (R) Germany (G) 10.9 38.5 7.9 Korea (K) 36.7 18.7 Japan (J) U.S.A. (U) 28.0 41.4 36.0 38.2 8.6 25.8 22.9 Profit Sector 27.5 20.4 35.4 China (C) Turkey (T) 49.9 22.8 7.2 19.5 13.0 22.9 15.5 16.1 Non-profit Sector 15.5 Citizen Sector FIg.2 The Proportion of Four Sectors C.S．(≒50%) -Korea・ Germany (Manage?) N.P.S．(≒40%) -Japan・China (Manage?) 58.4 40.4 -Philippine・ Russia (Enjoy?) 21.1 Other (N.E.C.) P.S．(≒40%) -Turkey (Suffer?) Other (≒60%) 10 ・ 4 Sectors’ Proportion & SIS (mean) 3 3 PH PH R R K J C 1 T 0 0 10 20 30 Fig.3-1 Citizen Sector G SIS (Mean) SIS (Mean) G 2 40 % 50 2 K J C 1 T 0 0 10 20 30 40 % 50 Fig.3-2 Profit Sector -Positive Correlation: Citizen Sector’s % & SIS (mean) -Negative Correlation: Profit Sector’s % & SIS (mean) ⇒ CSS Hypothesis is Valid 11 Ⅲ. Resource Hypothesis 1) Trend in Year Established and SIS 50% Philippine (PH) Russia (R) Germany (G) Korea (K) Japan (J) China (C) Turkey (T) U.S.A. (U) ･Long History CSO J, G, K > R, C, T, PH 40 ･Strong SIS 30 T, C < J, G, K < R, PH 20 10 Fig.4 Year Established '01- '95 '90 '85 '80 2000* * Until 1997 in Japan and Korea. Until 1999 in U.S.A. and Germany. '75 '70 '65 '60 '55 '50 '45 '40 '35 '30 '25 '20 '15 '10 '05 -1900 0 No Relations Between Year Established and SIS 12 ･Profit Sector’s Year Established 60% Philippine (PH) Russia (R) Germany (G) Korea (K) Japan (J) China (C) Turkey (T) U.S.A. (U) ･Large Differences among Countries as well as in Development Paths 50 40 30 ･Developed Countries : Long History (Created 20 before and after WWII) 10 Fig.5-1 Establishment Year: Profit sector '01- '95 '90 '85 2000* * Until 1997 in Japan and Korea. Until 1999 in U.S.A. and Germany. '80 '75 '70 '65 '60 '55 '50 '45 '40 '35 '30 '25 '20 '15 '10 '05 -1900 0 ･Changed Political System & Developing Countries : Short History (since the late ’80s) 13 ･Citizen Sector’s Year Established 50% Philippine (PH) Russia (R) Germany (G) Korea (K) Japan (J) China (C) Turkey (T) U.S.A. (U) ･Sharp Rise in the 90s ：Regime Changes Vulnerability of C.S. 40 30 20 ･Developed Countries (U, G, J) ：Established Earlier 10 Fig.5-2 Establishment Year: Citizen Sector '01- '95 '90 2000* * Until 1997 in Japan and Korea. Until 1999 in U.S.A. and Germany. '85 '80 '75 '70 '65 '60 '55 '50 '45 '40 '35 '30 '25 '20 '15 '10 '05 -1900 0 14 ･Relation between Establishment Year and SIS TABLE 3. Summary of Cross-tabulation analysis: Resource-Establishment Year Country with significance found in cross-tabulation Variables: Country/Sector with significance found in cross-tabulation Country Name (n.1) Ph/R/G/K/J/C/T CN and Sector (n.2) P,NP,C,O Establishment Year: R*G*J* (n.3) G:P,c/ J:o/R: C (n.4) (n.1) Ph：Philippine/ R: Russia /G: Germany/K: Korea/J: Japan/C: China/T: Turkey. (n.2) P: Profit sector/ NP: Non-profit sector/ C: Citizen sector/ O: Other, Not elsewhere classified. (n.3) ＠：under level of significance of 0.01 , * : under level of significance of 0.05. (n.4) large letter under the level of significance of 0.05, small letters under the level of significance of 0.10. ･R, G, J: Relation between Establishment Year and SIS （level of significance (0.05) ） ・Negative Relation: Short History ⇒ Strong SIS 15 2) Organizational Resources TABLE 4. Summary of Cross-tabulation analysis: Organizational Resource Variables Member (individual) Member (organizational) Personnel Finance Nat’l Gov’t Subsidy Country Name (Ph/R/G/K/J/C/Tu) CN and Sector (P,NP,C,O) No significance No significance No significance No significance Ph＠,R＠,G＠ No significance, but Significant but not linear higher SIS confirmed (Correlation unclear) Ph: C,O when resources are small G@Tu@ G: P,O Turkey (and Philippines) Significant but not liner (Correlation unclear) No significance found C:NP,O/Tu:O ･No Relation between Organizational Resources and SIS ⇒ Resource Hypothesis is not Valid (Year Established and SIS, Organizational Resources and SIS) 16 IV. Political Activism Hypothesis ･Relation between CSO’s Activities and SIS (mean) -Contact with Political Parties -Contact Mass Media -Support Election Campaign -Influence Budget Formation -Lobbying (general) -Policy Performance (formulation, blocking/revising) 17 TABLE 5. Summary of Cross-tabulation analysis: Activities and Performance. Country that showed Sector that showed in Linearity Significance in Crosssignificance in respective Tabulation country Variables Name: Ph/R/G/K/J/C/Tu Sectors: P,NP,C,O Pol. Lobbying to Ph@R@G@K@J@C@Tu@ Ph:P,NP,C,O/G:NP,C,O/J:P,NP,C,O The Governments R: P,NP,C/T:O Linear Contact National R@G@K@J@C@ G:P,NP,C,O/J:P,NP,C,O semi-liniear Administration R: P,NP,C/T:P,O (Ph out) Contact Gov.Party R@G@K@J@C@ G:C,O/K:NP/J:P,NP,C,O/C:NP,C,O R: NP,C/T:C,O Non-L Non-linear Ph4.4%;R17.4%;G15.4%;K23.1%;J17.3%;C33.5%;Tu5.6% Contact Oppo.Party R@G@K*J@C@ G:C,O/K:NP,C/J:P,NP,C,O/C:P,NP,C,O R: P,NP,C/T:NP,C,O Non-L Contact Media R@G@K@J@C* G:P,C,O/K:P,NP/J:P,NP,C/C:NP R: P,NP,C/T:NP,O Linear (Ph out) Campaigning El. Ph*J@C*Tu@ G:C/J:P,NP Linear /T:NP,O (G out) Ph17.8％;R15.1;G4.4;K12.8;J15.8;Ch10.8;Tu12.5% Lobbying Budget G@K@J G:NP,C/K:O/J:P,NP,C/ Non-L T:O Lobbying Total Ph@R@G@K@J@C*Tu@ G:P,C,O/K:NP/J:P,NP,C,O/ R: P,NP,C/T:O Semi-linear Ph15.8%;R68.2%;G62.5%;K35.0%;J30.5%;Ch10.0%;Tu53.9% (T,Ph out) Policy Formulation Ph@R@G@K@J@C@Tu@ Ph:C/G:NP,C,O/K:NP/J:P,NP,O/C:C,O Performance R: P,NP,C/T:NP,C Linear Policy Performance R@G@K*J@C*Tu@ Ph:C/G:NP,C,O/J:P,NP,O/C:C Policy influence R: P,NP,C/T:NP,C,O semi-Linear (Ph out) --------------------------------------------------------------------------------------------------------Notes：same as table 3. ･Inference: Strong Relation Between CSO’s Activities and SIS in each country and sector Sector Level Significance Japan, Germany> Turkey, Russia> Korea, China, Philippine 18 ･Relation between Lobbying and SIS (mean) 3 ･ PH R SIS (Mean) G 2 K J C 1 T 0 0 20 40 60 Fig.6-1 Lobbying through Politicians % 80 19 ･Relation between Providing Information (Mass Medias) and SIS (mean) ･ 3 PH R SIS (Mean) G 2 K J C 1 T 0 0 10 20 30 40 50 60 Fig.6-2 Providing Information: Mass Medias % 70 20 ･Relation between Policy Performance (Formulation) and SIS (mean) ･ 3 PH R SIS (Mean) G 2 K J C 1 T 0 0 10 20 30 40 Fig.6-4 Policy Performance (Formulation) % 50 21 V. Administration Connection Hypothesis ･Institutional Relation between Administration Connection and SIS (mean) -Accrediting -Licensing -Administrative Guidance -Policy-Formation Cooperation -Opinion Exchange -Sending Advisory Board Member -Post Offering to the Ex-Bureaucrats ….. 22 ･Relation between Administration Connection and SIS TABLE 6. Summary of Cross-tabulation analysis: Relations with Administration. Adm. Connection Ph@,R@,G@,K*J@ Linear Ph:C,NP,O/G:NP,C,O/J:P,C,NP/R:NP,C,P （National） Ph89.1%;R60.0%;G28.9%;K91.7%;J74.9%;Ch94.1%;Tu97.7% Adm. Connection Ph@,R@,G@,J@ Non-Linear Ph:NP,O/G:NP,C/J:P,C,NP,O/R:NP,C/T:P,NP （Local） Adm. Consultation Ph@R@G@K@J@C@Tu@ G:NP,C,O/K:NP/J:P,NP,C,O/C:P,NP,C,O R: P,NP,C/T:O. Ph24.5%;R52.1%;G30.0%;K40.7%;J33.0%;Ch30.3%;Tu14.8% semi-Linear ･No Relation (Linearity) between the National Administration and SIS (Some Negative Relation) ･Relation between the Local Autonomies and SIS (Weak Relation) 23(24) ･ Relation between Administration Connection and SIS (mean) 3 3 PH PH R R G SIS (Mean) SIS (Mean) G 2 K J C 1 2 K J C 1 T T * China: No distinction between National and Local government in the Questionaire. * China: No distinction between National and Local government in the Questionaire. 0 0 20 40 60 80 Fig.7-1 Relations with National Administration % 100 0 0 20 40 60 80 Fig.7-2 Relations with Local Autonomies % 100 25 Conclusion Results of Tested Hypotheses 1: Civil Society Structure Hyp. is valid (C.S. proportion strongly correlates with SIS) 2: Resource Hyp. is not valid (Neither Y.E. nor Org. Res. Correlates with SIS) 3: Pol. Activism Hyp. is valid (Correlations strong in Japan & Germany) 4: Adm. Connect. Hyp. is unclear 5: “SIS” shows aggressiveness of C.S. as it affect CSO activism and performance (except Philippine)
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