Understanding the Drivers of Trust in Government Institutions in Korea

Annex B. Methodology

Objectives

This methodological annex has three key objectives: 1) to describe the sampling frame used to generate the quantitative evidence collected through the OECD-KDI questionnaire; 2) to display the weights used to construct the composite indicators on institutional and political trust; and 3)present the detailed results of the econometric analyses conducted to generate the results of this case study.

Sampling frame

The OECD-KDI survey examined perceptions of the Korean population regarding their level of trust in government institutions. As defined in the instructions accompanying the survey, the main focus was on administrative agencies of central and local government that develop and execute public policy for education, public health, security, defence, transportation and other areas that provide related public services. The survey was structured around eight different sections.1

As the questions focused primarily on administrative institutions, respondents were asked not to take into account their subjective feelings about political organisations (e.g. the National Assembly, local councils or political parties) or about the president, the prime minister, cabinet ministers, National Assembly members, local government heads, or city council members when giving their responses to the various sections of the survey, except when specifically mentioned.

In total, 3 000 citizens were surveyed from all 17 of Korea’s administrative divisions. The sample is representative of the Korean population and follows the sampling frame of the Korean census. Regarding the geographical distribution, 46.6% of respondents were from urban metropolitan areas, 43.8% from mid- and small-sized cities (suburban), and 9.5% from rural areas. The sample was gender balanced, and age distribution was as follows: 18% in their 20s, 21% in their 30s, 22% in their 40s, 18% in their 50s, and 21% 60 and above. The majority of respondents shared a household with their spouse (74%) and with their children (59 %) (multiple responses possible). The vast majority (71%) of respondents were married, while 26% were single (never married) and only 1.4% were divorced.

The survey asked respondents to state their highest level of education: 2% followed a master or a PhD, 32% had graduated from a four-year university programme, while 31% had graduated from high school and 16% from a vocational college. Almost 40% of respondents were permanent employees (with a contract for more than a year), 20% were full time homemakers, while 14% were self-employed. Around 56% of respondents reported earnings between KRW 12 million and KRW 48 million (EUR 9 000 to 36 000) a year. More than half (54%) described themselves as having no religion, 20% were Buddhist, 20% Protestants, and 7% Catholic. For political views, almost 30% considered themselves progressive, 46% neutral and 24% conservative. See Box A B.1 for the survey sample frame.

Box A B.1. OECD-KDI survey sample frame

Subjects and time period

• Population: all citizens over 20 years old

• Sampling size (number of respondents): 3 000 people

• Time period: 20 January to 22 February 2016.

Sampling design and sampling

• Sampling frame: Korea Census 2010

• Sampling method: stratified random sampling

• Stratification criteria: region, gender, age

• Data collection method: face-to-face interview using a structured questionnaire

• Interviewers’ comments: no specific observations on the survey were reported except for the prolonged length of questionnaire.

Table A B.1. Sample structure

Region	Population (as of 2010)			Sample size (per region, gender, and age)
				20-29		30-39		40-49		50-59		Over 60
	Total	Male	Female	M	F	M	F	M	F	M	F	M	F
Whole country	36 765 374	17 974 239	18 791 135	280	258	320	316	336	334	265	271	266	354
Seoul	7 640 942	3 693 583	3 947 359	64	66	70	69	63	66	53	59	51	62
Busan	2 688 226	1 292 297	1 395 929	20	19	20	20	22	24	22	24	21	27
Daegu	1 857 618	897 765	959 853	14	13	15	16	17	18	14	14	13	18
Incheon	1 996 647	985 734	1 010 913	16	15	18	18	20	20	14	14	12	16
Gwangju	1 076 346	521 693	554 653	10	9	9	10	10	10	7	7	7	9
Daejeon	1 113 295	548 034	565 261	10	9	10	10	10	10	8	8	7	9
Ulsan	794 357	401 874	392 483	6	5	8	7	9	9	6	6	4	5
Gyeongi	8 348 377	4 124 682	4 223 695	63	60	82	82	85	83	57	55	50	64
Gangwon	1 131 797	560 975	570 822	8	6	8	7	11	10	9	9	10	14
Chung-buk	1 138 889	561 343	577 546	9	7	10	9	10	10	8	8	9	13
Chung-nam	1 527 623	762 167	765 456	12	9	13	12	13	12	10	11	14	19
Jeon-buk	1 346 471	648 665	697 806	9	8	10	10	11	10	10	10	13	19
Jeon-nam	1 337 622	641 679	695 943	7	6	9	9	11	10	10	10	15	22
Gyeong-buk	2 013 413	982 586	1 030 827	14	11	15	14	17	16	15	16	19	27
Gyeong-nam	2 365 348	1 162 847	1 202 501	15	13	20	20	23	22	19	17	18	26
Jeju	388 403	188 315	200 088	3	2	3	3	4	4	3	3	3	4

Composite indicators on political and institutional trust

The objective of the research is to identify trusting patterns among different population groups and to analyse some of the key drivers of trust in government institutions. The questionnaire’s design was based on the measurement and policy framework developed by the OECD, which in turn is based on a comprehensive literature review of the main drivers of institutional trust.

An important challenge is analysing the wealth of information available in a way that is amenable to policy recommendations; in other words, to construct a robust dependent variable that could be tested against respondents’ individual characteristics; the policy drivers identified by the framework; and exogenous factors that could shape trusting patterns. A first step was to evaluate the variability among observed correlated variables and whether or not they can be synthetised into fewer underlying variables. A common data reduction methodology is factor analysis.

The OECD-KDI includes a set of perception questions about trust in several public institutions. After conducting factor analysis, two different factors were identified that captured common data patterns: Factor 1 on institutional trust, and Factor 2 on political trust or trust in the elected leadership.

After identifying variables that capture the same underlying pattern, the question was how to aggregate them into a single measure (i.e. how to weight and combine them). Based on the results of the factor analysis differentiating between two factors (i.e. political and institutional trust) a neutral solution is to mathematically calculate the weights or scoring coefficients. The scoring coefficient identifies the relative weight of each variable within the selected factor, based on the explanatory power of each variable represented by the factor loading. The larger the value of the coefficient, the more important the corresponding variable in calculating the component. Table A B.2 presents the normalised weights for each of the variables within the factor on institutional trust, derived from the mathematical approach described above. Based on these weights, a composite measure for trust in institutions was constructed at the individual level. This is the main dependent variable in our analysis.

Table A B.2. Normalised weights for the institutional trust factor

Factor 1: Institutional trust	Normalised weights
Government employees	0.084632711
Courts	0.107098743
Prosecutors	0.111676233
Public corporations	0.112112185
Police	0.140528954
Education system	0.161643537
Health system	0.174772942

A similar approach was followed to calculate the second factor on political trust. Table A B.3 presents the normalised weights for each of the variables within Factor 2, derived from the mathematical approach described above. Based on these weights a composite measure for trust in political institutions was constructed at the individual level.

Table A B.3. Normalised weights for the Political trust factor

Factor 2: Political trust	Normalised weights
National Assembly	0.233441
Members of the National Assembly	0.278289
Local council	0.249619
Members of the local council	0.238651

Source: OECD analysis

Econometric analyses

The econometric analyses conducted as part of this case study took into account three main channels that may influence trust: 1) an individual’s characteristics, including their preferences and expectations; 2)  the individual’s socio-economic characteristics; 3) the institutional environment the individual acts in (e.g. policy drivers). Both short and long-term factors, as well as micro and macro-level aspects, are thus comprehensively addressed.

At the individual level, a person’s expectations of other people’s behaviour and the future development of the economy, as well as general socio-economic and demographic characteristics, are connected with trust.

Preferences and expectations

An individual’s beliefs about how secure the future will be in terms of income and job conditions, and how accessible are opportunities for social mobility, are linked to whether government institutions afford these. People who consider themselves most at risk of future financial problems or job loss display low trust in public institutions not able to provide security (Bouckaert et al., 2002; Inglehart and Norris, 2016). In turn, a perceived lack of equality and mobility may be another source of frustration among those who do not reap the benefits of economic growth and feel left behind in increasingly unequal societies (Alesina et al, 2017). In turn, volunteering and civic engagement is positively associated with trust in government, even though the direction of causality is debated (Myong and Seo, 2015).

Socio-economic background

Individual demographic and socio-economic characteristics have been consistently found to be highly correlated with trust, including age, gender, education, income level and labour force status (Alesina and La Ferrara, 2002; Algan and Cahuc, 2013). There is a positive relationship between interpersonal and institutional trust and educational status (and to a weaker degree, income levels) (Stolle et al., 2008; Helliwell and Wang, 2010; Carl and Billari, 2014). People that are better off financially and higher educated are likely to enjoy more opportunities and channels to take part in society (e.g. through volunteering and political participation), helping to develop and maintain larger and more diverse social networks (Helliwell and Putnam, 2007; OECD, 2015b). The cognitive skills gained through education also allow for a better understanding of government functions, translating into higher trust of public institutions (Christensen and Laegreid, 2005).

Personal values

A person’s values about how society should be organised is also connected with trust in other people in that society, as well as with trust in the institutions that guard the organisational rules. For instance, religious observance is a strong correlate of social ties, and this correlation is generally observed across religious affiliations (Schoenfeld, 1978; Traunmüller, 2011). Furthermore, one’s political orientation is likely a mitigating factor when formulating judgements about public institutions: in the United States for instance, trust in government is always higher for members of the party of the sitting President (Pew, 2015).

Institutional determinants

The institutional context or the system of bodies, rules, regulation, policies procedures and processes in which people operate is crucial to foster co‑operation as well as inspire trust in the institutions themselves. Both the competence of institutions to carry out their role and the values and intentions that guide government action are key components of the institutional determinants of trust (OECD, 2017; Bouckaert and Van der Walle, 2003; Nooteboom, 2007; Bouckaert, 2012).

Government competence

Government competence encompasses the ability to deliver quality public services, to respond to citizen needs and to effectively manage social, economic and political uncertainty. Trust in government institutions responds to shocks in government performance, as measured by scandals in government agencies (Keele, 2004). Moreover, citizens’ evaluations of government services they encounter regularly have been found to be quite accurate (Van Ryzin, 2007) and feed into the advocacy by the “new public management” literature for greater emphasis on improving customer service to strengthen trust (Aberbach, 2007). Nevertheless, the direction of causality between public service performance and trust is not straightforward, since existing levels of trust in institutions might also impact perceptions of quality of services received (Bouckaert and Walle, 2013).

Government values

The notion of government values revolves around norms of integrity: low corruption and high standards of accountability; openness of the policy process to citizen participation; and fair and equal treatment of all population groups.

People are less likely to trust institutions whose effectiveness is limited by corruption, and there is a robust cross-country correlation between trust in institutions and perceptions of corruption (Anderson and Tverdova, 2003; OECD, 2013). At the same time, low institutional and interpersonal trust are likely to reinforce institutions’ weakness: low institutional trust may hinder government efforts to improve integrity, and a society with weak interpersonal trust and norms of low co‑operation is likely to be more tolerant of non-compliance with regulations and laws (Morris and Klesner, 2010; Aghion et al, 2010). When it comes to the connection between fairness and institutional trust, experiences of discrimination have been found to harm perceptions of trustworthiness of government actors (Wang, 2016).

Linear regression results

In order to test the relationship between trust in public institutions, its main drivers and the impact of other contextual variables, the study carried out an analysis based on linear regressions. In all regressions, independent variables are normalised, meaning that the coefficients reported represent the change in the dependent variable as a result of one standard deviation increase in the explanatory variable. Results from linear regressions are presented for trust in government institutions and trust in political institutions.

The policy and contextual drivers of trust in government are presented in Table A B.4, while those of trust in political institutions are presented in Table A B.5. Both trust in government institutions and trusts in political institutions are regressed using the three broad categories presented in the conceptual framework: preferences and expectations (Column I), socioeconomic background (Column II) and government competence and values (Column III). Each of the individual categories is first regressed on the dependent variable, first including the full set of variables, and in the following using a selection determined by a stepwise regression. In the final column (Column IV), all three categories are grouped together, and the significant variables are retained (using the same methodology).

Table A B.4. Determinants of institutional trust

The dependent variable is a composite measure of institutional trust

	I. Preferences and expectations		II. Socio-economic background		III. Government competences and values		VI. Full model
VARIABLES	All	Selection	All	Selection	All	Selection
Satisfaction with standard of living	-0.0774***
	(0.0215)
Satisfaction with safety from crime	0.0341
	(0.0335)
Satisfaction with feeling part of a community	0.0416*	0.0336					0.0991***
	(0.0249)	(0.0241)					(0.0131)
Satisfaction with safety from accidents	0.0131
	(0.0413)
Satisfaction with safety from disasters	0.167***	0.201***
	(0.0368)	(0.0226)
Satisfaction with future security	0.0706***	0.0371
	(0.0255)	(0.0241)
Satisfaction with your job	0.00410
	(0.0170)
Importance of family wealth	0.0741***	0.0691***
	(0.0214)	(0.0205)
Importance of having an aspiration	-0.000541
	(0.0255)
Importance of working hard	0.151***	0.148***
	(0.0232)	(0.0209)
Importance of having a personal network	-0.0837***	-0.0979***
	(0.0257)	(0.0229)
Importance of school ties	-0.0260
	(0.0317)
Importance of having a regional connection	0.000931
	(0.0289)
Importance of having a political connection	0.0810***	0.0721***
	(0.0248)	(0.0220)
Interpersonal trust	0.227***	0.218***
	(0.0208)	(0.0205)
Gender			-0.0311	-0.0379**
			(0.0212)	(0.0180)
Civil status			0.0439*	0.0440*
			(0.0240)	(0.0231)
Income level			-0.00146
			(0.0232)
Age			0.0783***	0.0803***
			(0.0238)	(0.0235)
Employment status			0.0148
			(0.0219)
Regional growth rate			0.113***	0.112***			0.0847***
			(0.0167)	(0.0166)			(0.0127)
Recent interaction with a civil servant			0.0935***	0.0930***			0.0718***
			(0.0179)	(0.0179)			(0.0127)
Political orientation (conservativeness)			0.0587***	0.0597***
			(0.0190)	(0.0189)
Expected satisfactory answer to a complaint					0.0284
					(0.0264)
Expected capacity to innovate for civil servants					0.143***	0.154***	0.140***
					(0.0285)	(0.0271)	(0.0241)
Expected government response to dissatisfaction with a service					0.0920***	0.107***	0.0941***
					(0.0290)	(0.0280)	(0.0241)
Expected effectiveness of disaster management plans					0.0881***	0.105***	0.106***
					(0.0268)	(0.0261)	(0.0225)
Expected stability of conditions for starting a business					0.0911***	0.106***	0.110***
					(0.0282)	(0.0264)	(0.0218)
Expected provision of food and shelter in case of a disaster					0.0380
					(0.0278)
Expected prosecution of a corrupt high-level officer					0.0661***	0.0701***	0.0624***
					(0.0206)	(0.0205)	(0.0168)
Expected availability of information					0.0984***	0.108***	0.103***
					(0.0237)	(0.0231)	(0.0182)
Expected consultation when a decision affecting the community is to be taken					-0.0238
					(0.0287)
Expectation incorporation of an opinion following a consultation process					0.0414
					(0.0330)
Expected action in case of discrimination					0.0747***	0.0836***	0.0848***
					(0.0267)	(0.0262)	(0.0228)
Expected fairness in sharing the burden of a tax reform					0.108***	0.111***	0.109***
					(0.0255)	(0.0252)	(0.0220)
Constant	-2.35e-09	-1.30e-09	-0.00191	-0.00189	-7.55e-10	-8.99e-10	-0.00140
	(0.0165)	(0.0165)	(0.0179)	(0.0179)	(0.0129)	(0.0129)	(0.0127)
Observations	3 000	3 000	2 990	2 990	3 000	3 000	2 990
R-squared	0.191	0.186	0.043	0.043	0.503	0.502	0.524

Note: Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

Source: OECD-KDI survey

Table A B.5. Determinants of political trust

The dependent variable is a composite measure of political trust

	Preferences and expectations		II. Socio-economic background		III. Government competence and values		IV. Full model
VARIABLES	All	Selection	All	Selection	All	Selection
Satisfaction with standard of living	-0.0137
	(0.0221)
Satisfaction with safety from crime	-0.0469
	(0.0334)
Satisfaction with feeling part of a community	-0.0266
	(0.0250)
Satisfaction with safety from accidents	0.0968**
	(0.0392)
Satisfaction with safety from disasters	0.0697**
	(0.0352)
Satisfaction with future security	0.118***	0.146***
	(0.0253)	(0.0199)
Satisfaction with your job	0.0170
	(0.0169)
Importance of family wealth	-0.0151
	(0.0204)
Importance of having an aspiration	0.00397
	(0.0238)
Importance of working hard	0.0315
	(0.0225)
Importance of having a personal network	-0.0641***	-0.0435*
	(0.0246)	(0.0230)
Importance of school ties	-0.109***	-0.110***
	(0.0306)	(0.0265)
Importance of having a regional connection	-0.00280
	(0.0290)
Importance of having a political connection	0.192***	0.185***					0.0577***
	(0.0253)	(0.0222)					(0.0141)
Interpersonal trust	0.263***	0.271***
	(0.0196)	(0.0189)
Gender			-0.00915
			(0.0218)
Civil status			0.0846***	0.0945***			0.0467***
			(0.0243)	(0.0183)			(0.0175)
Income level			-0.0107
			(0.0243)
Age			0.00808				-0.0517***
			(0.0250)				(0.0181)
Employment status			0.0458**
			(0.0219)
Regional growth rate			0.0462***	0.0433**
			(0.0170)	(0.0169)
Recent interaction with a civil servant			0.0402**	0.0369**
			(0.0180)	(0.0180)
Political orientation (conservativeness)			-0.00581				-0.0560***
			(0.0199)				(0.0146)
Expected satisfactory answer to a complaint					0.137***	0.137***	0.135***
					(0.0280)	(0.0269)	(0.0253)
Expected capacity to innovate for civil servants					0.0907***	0.0936***	0.0825***
					(0.0294)	(0.0278)	(0.0258)
Expected government response to dissatisfaction with a service					0.0109
					(0.0301)
Expected effectiveness of disaster management plans					0.103***	0.102***	0.0878***
					(0.0314)	(0.0313)	(0.0246)
Expected stability of conditions for starting a business					0.127***	0.127***	0.114***
					(0.0299)	(0.0299)	(0.0243)
Expected provision of food and shelter in case of a disaster					-0.0753**	-0.0755**
					(0.0301)	(0.0300)
Expected prosecution of a corrupt high-level officer					0.0452**	0.0449**
					(0.0211)	(0.0211)
Expected availability of information					-0.0855***	-0.0869***	-0.0859***
					(0.0240)	(0.0238)	(0.0211)
Expected consultation when a decision affecting the community is to be taken					0.137***	0.136***	0.133***
					(0.0304)	(0.0304)	(0.0281)
Expectation incorporation of an opinion following a consultation process					0.0910***	0.0898***	0.0847***
					(0.0340)	(0.0335)	(0.0299)
Expected action in case of discrimination					-0.0182
					(0.0264)
Expected fairness in sharing the burden of a tax reform					0.178***	0.172***	0.182***
					(0.0296)	(0.0279)	(0.0232)
Constant	0	-2.05e-10	-0.000851	-0.000769	1.52e-09	1.51e-09	-0.000278
	(0.0167)	(0.0168)	(0.0182)	(0.0182)	(0.0140)	(0.0140)	(0.0139)
Observations	3 000	3 000	2 990	2 990	3 000	3 000	2 990
R-squared	0.163	0.150	0.016	0.012	0.416	0.416	0.423

Note: Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

Source: OECD-KDI survey

References

Aberbach, J.D. (2007), “Citizens and Consumers”, Public Management Review, Vol. 7, No. 2, pp. 225-246.

Aghion,P ., Y. Algan, P. Cahuc and A. Shleifer (2010) “Regulation and Distrust” The Quarterly Journal of Economics, Volume 125, Issue 3, Pages 1015–1049, https://doi.org/10.1162/qjec.2010.125.3.10

Alesina, A. and E. La Ferrara (2002), “Who Trusts Others?”, Journal of Public Economics, Vol. 85, pp. 207-34.

Alesina, A., S. Stantcheva, and E. Teso (2017), “Intergenerational Mobility and Preferences for Redistribution”, NBER Working Paper, No. 23027.

Algan, Y. and P. Cahuc (2013), “Trust, growth and well-being: New evidence and policy implications”, IZA Discussion Paper, No. 7464, IZA, Bonn, http://ftp.iza.org/dp7464.pdf.

Anderson, C.J. and Y.V. Tverdova (2003), “Corruption, Political Allegiances, and Attitudes toward Government in Contemporary Democracies”, American Journal of Political Science, Vol. 47, No. 1, pp. 91-109.

Bouckaert, G. (2012), “Trust and public administration”, Administration, Vol. 60/1, pp. 91-115. Wiley-Blackwell, Hoboken, NJ

Bouckaert, G. and S. Van de Walle (2003), “Comparing measures of citizen trust and user satisfaction as indicators of ‘good governance’: Difficulties in linking trust and satisfaction indicators”, International Review of Administrative Sciences, Vol. 69/3, Sage Publications, Thousand Oaks, CA, pp. 329-343, http://journals.sagepub.com/doi/pdf/10.1177/0020852303693003.

Bouckaert, G., S. Van de Walle, B. Maddens, and J.K. Kampen (2002), “Identity vs. Performance: An Overview of Theories Explaining Trust in Government”, Leuven: Public Management Institute.

Carl, N. and F.C. Billari (2014), “Generalized trust and intelligence in the United States”, PLoS ONE, Vol. 9(3).

Christensen, T., and Laegreid, P. (2005). Trust in government: The relative importance of service satisfaction, political factors, and demography. Public Performance & Management Review, 28(4), 487-511.

Helliwell, J.F. and R.D. Putnam (2007), “Education and social capital”, Eastern Economic Journal, Vol. 63(1), pp. 1-19.

Helliwell, J. and R. Putnam (2004), “The social context of well-being”, Philosophical Transactions of the Royal Society B: Biological Sciences, Vol. 359/1449, pp. 1435-1446, http://doi.org/10.1098/rstb.2004.1522.

Helliwell, J. and S. Wang (2010), “Trust and well-being”, NBER Working Paper Series, No. 15911, National Bureau of Economic Research, Cambridge, MA, www.nber.org/papers/w15911.

Inglehart, R. and P. Norris (2016), “Trump, Brexit, and the Rise of Populism: Economic Have-Nots and Cultural Backlash”, HKS Working Paper No. RWP16-026.

Keele, L (2004), “ Social capital, government performance, and the dynamics of trust in government” , American Journal of Political Science 51(2): 241-254

Morris, D. and J. Klesner (2010), “Corruption and Trust: Theoretical considerations an evidence from Mexico”, Comparative Political Studies, Vol 43, No 10 pp 1258-1285

Nooteboom, B. (2007), “Social capital, institutions and trust”, Review of Social Economy, Vol. 65, No. 1, pp. 29 53.

OECD (2017), Trust and Public Policy: How Better Governance Can Help Rebuild Public Trust, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264268920-en.

OECD (2015), Government at a Glance 2015, OECD Publishing, Paris, http://dx.doi.org/10.1787/22214399.

OECD (2015b), Education at a Glance 2015: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2015-en.

OECD (2013), Government at a Glance 2013, OECD Publishing, Paris, http://dx.doi.org/10.1787/gov_glance-2013-enPew Research Center (2015), “Beyond Distrust: How Americans View Their Government”, November 2015.

Schoenfeld, W.N. (1978), “Image of Man: The Effect of Religion on Trust: A Research Note”, Review of Religious Research, Vol. 20, No. 1, pp. 61-67.

Traunmüller, R. (2010), “Moral Communities? Religion as a Source of Social Trust in a Multilevel Analysis of 97 German Regions”, European Sociological Review, Vol. 27, No. 3, pp. 346-363.

Van Ryzin, G. (2007), “Pieces of a puzzle: linking government performance, citizen satisfaction, and trust”, Public Performance & Management Review, Vol. 30, No. 4, pp. 521-535.

Wang, C. (2016), “Government Performance, Corruption, and Political Trust in East Asia”, Social Science Quarterly, Vol. 97, No. 2, pp. 211-231.

Note

← 1.  The eight sections were: 1) life perceptions, experiences and satisfaction; 2) interpersonal trust; 3) trust in institutions and organisations; 4) trust in government (broad sense); 5) capabilities of central government administrative branches; 6) experience with and opinions about policy communication by central government administrative branches; 7) local governments (city, province, country, and district) and the resident participation system; 8) experiences of public conflicts and opinions about administrative capabilities.