The Relationship Between Government and Nonprofit Sector in China: A Network Perspective

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Good afternoon, good evening, and good 

morning from Asia. Welcome, welcome to  

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the UCLA Asia Pacific Center Global Chinese 

Philanthropy public lecture series. My name is  

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Min Zhou. I am the Distinguished Professor 

of Sociology and Asian American Studies,  

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Walter and Shirley Wang Endowed Chair in U.S 

China Relations and Communications, and Director  

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of the Asia Pacific Center at UCLA. Today's public 

lecture is by Professor Ji Ma of the University of  

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Texas at Austin on the relationship between the 

government and the non-profit sector in China.  

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Before starting today's program, I would 

like to say a few words about the Center  

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I serve as director. The UCLA Asia Pacific Center 

promotes greater knowledge and understanding of  

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Asia and the Pacific region on campus and in the 

community. Through Innovative research, teaching  

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public programs, and international collaborations, 

we focus on Asian and trans-Pacific connections  

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from historical, contemporary, and comparative 

perspectives and encourage interdisciplinary  

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work on cross-border and supra-national 

issues on language and culture, politics,  

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economy, and society and the sustainability 

in ongoing processes of globalization.  

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Our Center runs the Taiwan Studies program, the 

program on Central Asia, and the Global Chinese  

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Philanthropy Research and Training program and 

we are trying to raise funds to rejuvenate our  

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Hong Kong studies program. We serve as the 

U.S. Department of Education Title VI East  

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Asia National Research Center and the Foreign 

Languages and Area Studies FLAS Fellowship.  

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We also have other fellowships. We also provide a 

range of fellowships and small grants to support  

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UCLA faculty students including the Taiwan Studies 

faculty including the Taiwan Studies fellowship  

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the J. Yang fellowships, Wagatsume 

fellowships, and Steiner fellowships.  

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Our center's Global Chinese Philanthropy Research 

Teach and Training Program is built on the Global  

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Chinese Philanthropy Initiative funded by the 

Long Family Foundation, now funded by the Cyrus  

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Tang Foundation. The current GCP program aims 

at integrating network building research and  

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training to bridge intellectual inquiry and 

professional practices in the field of GCP.  

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We aim at fostering passion, interests, 

volunteerism, stimulating innovative research,  

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and sharing with practices in GCP. Our GCP 

program includes three main components. First  

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is to maintain and expand our Global 

Chinese Philanthropy Research Network.  

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Second is to organize a quarterly public lectures 

series like this one. Today's lecture is the third  

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public lecture in the series this academic year. 

The first one was given by Dr. Marina Tan Harper  

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of UC Davis on Philanthropy Action of the Chinese 

Diaspora. The second one was by Professor Mark  

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Sidel of the University of Wisconsin Madison and 

the third one is this one. And then we will also  

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have our Annual Training Workshop. This is our 

third component. Our Training Workshop is designed  

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for undergraduate and graduate students in and 

from China with the primary focus on inspiring  

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their minds, fostering interests, and nurturing 

the culture of philanthropy and civic engagement.  

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So we will have our training workshop 

with a panel discussion on Thursday  

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June 8th. So please visit our website and 

watch out for our email announcements.  

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Our GCP program is led by UCLA Asia Pacific 

Center. We currently have eight institutional  

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partners in mainland China, Hong Kong, Singapore, 

Malaysia, and the United States, and will welcome  

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other institutions in the U.S China and 

other parts of the world to partner with us.

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Together we want to promote and develop 

the view of global Chinese philanthropy.  

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Now please keep yourself muted at all times. If 

you have any questions or comments please write  

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them down briefly in the Q&A box after the 

presentation. I'm going to select questions  

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for Professor Ma. The event will end at 

6:00 PM but if we have more questions we  

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could extend it until 6:15 pm today. Now is my 

great pleasure to introduce Professor Ji Ma.  

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Professor Ma received his Ph.D. in 

philanthropic studies from Indiana University  

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and he is currently assistant professor 

in non-profit and philanthropic studies  

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at the Lyndon B. Johnson School of Aublic 

affairs at the University of Texas at Austin.  

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He is also an affiliated faculty member at 

the Center for East Asian Studies and School  

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of Information at UT Austin. His main areas 

of research and teaching focus on State Civil  

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Society relationship knowledge production and 

computational social science methods with an  

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emphasis on non-profits and philanthropy. 

Professor Ma today will talk about China's  

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non-profit sector and the relationship between 

states and non-profits. So without further ado,  

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let's welcome Professor Ji Ma. 

Professor Ma, please go ahead.

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Thank you very much, thank you very so 

much. Professor Zhou and the Asian Centers.  

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UCLA, it is my great honor to be here to present 

something I know a little bit about to share  

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some of my studies and some of 

the knowledge on this topic.

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Okay, so everything's fine with the shared screen.

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Yes, everything is fine.

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Cool. So today I will focus on talking about 

the government and non-profit relations in China  

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especially focusing on the network perspective. 

The reason for focusing on the network perspective  

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is, I think it's a kind of general trend and I 

will elaborate on this later, but first a few  

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conceptual definitions and distinctions. 

I want to clarify the very beginning.  

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although I don't think I will be able to make a 

very clear distinction between them. But I just  

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want to give people a sense. We should be aware of 

these differences and sometimes they're related,  

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they are different but sometimes they are 

interchangeable, sometimes they are not. So many  

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concepts and definitions vary by discipline. They 

vary by discipline and background disciplinary  

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background and the context for example non-profit. 

Sometimes we call them non-permanations  

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non-profit sector but sometimes we call them 

non-governmental organizations like NGOs as well.  

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Sometimes you even call it civil society. 

Sometimes there are when you read a paper, they  

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are interchangeable in the paper so, and sometimes 

there is also another definition clarification  

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about government party-state, right? So since 

China is a one-party state, the government and  

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the party are tightly connected with each 

other. Sometimes when we talk about State  

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it refers to the government and party. Sometimes 

people like to use party-state altogether. Just be  

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aware of their of these definitions. Most of the 

time we can use them according to the context that  

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we can change them. Throughout the presentation, 

I will primarily use government and non-profit  

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relations because this term is more concrete 

and more from a functional perspective. It's  

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more concrete, right, they can have political 

or sociological implications but the term here  

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we are using is more concrete. There are a few 

waves of paradigms from the English scholarship  

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about the series. Theoretical paradigms about the 

relationship between government and non-profit.  

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The first paradigm is a conflicting paradigm. 

It just originally from the early 1990s.  

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As you can see it's just after the Tiananmen 

Square Incident. So at that moment,  

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the prediction about China's Civil Society 

is pretty pessimistic. This perspective,  

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all these sociological paradigms theorize the 

relationship between the state and Civil Society  

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is in direct conflict. And this is also a popular 

view about the relationship in Western countries.  

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It's not only about China but even about 

the Western countries. People try to use  

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these primary kinds of a cervical lens 

to examine the relationship between the  

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government and Civil Society. A second kind of 

theoretical paradigm emerged in the mid-200s.  

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So this kind of Paradigm is called Contingent 

Paradigm. So in this Paradigm nonprofits are  

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treated as service arms of the state. So you see 

there are more possibilities for these non-profits  

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to grow. There is more room for them to grow. They 

are not totally dictated by the government and  

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their position is not in a totally conflicting 

position with the government as well. However,  

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although they have rooms to survive, their 

survival was seen as contingent upon them focusing  

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on non-politically sensitive areas so they 

have to be focusing on those areas that are not  

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very clinically sensitive. If it is politically 

sensitive, the government will censor them. We all  

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give them a lot of pressure or assign government 

officials to their board members, right. So  

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there are many ways and there are to control 

these sensitive numbers of these non-profits  

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working in a sensitive area like human rights. 

Yeah especially always think this contingent  

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Paradigm progress a little bit and gives more 

room support the non-profits to function.

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The third Paradigm, which I have 

been working on and focusing on,  

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is about Network Paradigm. So these originated in 

the late 2010s. These Paradigms give more focus  

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on the roles of nonprofits and it focuses 

on the mutual imbalance and interactions  

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between non-profits and the government. If you 

have been living in China, you will know that  

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in China there are a lot of interactions between 

non-profit founders, a number of nations, and  

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government employees. The government officials. So 

before coming to this Academia world, I actually  

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founded a non-profit focusing on Rural education 

in China in 2010. So at that moment, as a founder  

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of that nonprofit, I have a lot of interactions 

with the government and we also had a government  

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supervisor. So they give us the radio title pieces 

so you need those things to get everything done  

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and a lot of interesting interaction 

with them. It's not, in one word,  

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it's not that kind of a region, it's a more 

dynamic interaction between all these spaces.  

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Yeah, so that's all from the English word. 

So all these different perspectives from  

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the English scholarship. What about the domestic 

perspectives? There are many studies actually in  

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the early year 2000 but since then, the control 

of this kind, of research space is tight,  

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so it's not easy to get a lot of research down 

in on this topic since 2010. One of the very  

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influential articles on this topic in Chinese is 

a system of differential control, a Study of State  

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Society Relationship in Contemporary China. I 

guess many of them probably have already read  

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this paper written by Kan Xiao-huang and they 

actually have an English-translated version.

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So in this study, they try to frame that the 

government is using a kind of differentiated  

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strategy to control non-profits if they are 

working on public service like education,  

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not politically sensitive it's okay for them 

to do anything as long as they don't touch  

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the touch of the pre-quality sensitive issues for 

those number of nations working on, say advocacy.  

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They have a tighter control strategy so it's a 

differential control. The second study is about  

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control and support a study of two independent 

relationships between the state and the society  

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so here this paper cites the relationship between 

a government and non-profit as control but also  

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there are some supporting relationships as well. 

So you see there this study does not actually  

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does not theorize the relationship between the 

two actors in a directly conflicting position.  

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Another study is an interesting alignment and 

analytical framework for the state-society  

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relationship during China's transitional 

period so this paper is still authorized.  

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If the government wants to survive they need 

to align their interest with the government  

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and also sometimes the government will outline 

their interest uh with the nonprofit as well.  

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So if there is that alignment between the 

interests of the nonprofit and the government,  

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there will be more room for the non-public 

nations to survive and or even survive  

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like many of the educational nonprofits in China, 

they are doing really, really well. Like one  

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Foundation, right, so they are doing a lot of work 

in disaster relief, they're serving the public and  

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they are not working on many kinds of politically 

sensitive issues. So they are working great.  

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In general, we see this domestic perspective give 

more focus on the interactions give more focus  

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on complexities between the non-profit and the 

government. So some general Trends. Firstly is  

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context. I think one of the general Trends 

in recent studies on this topic is they're  

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rejecting simplified and dynamic views about the 

relationship. They're also emphasizing the nuances  

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and interactions and complexities of methods. 

Originally the first wave of a study you see  

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most of the Articles, they are conceptual pieces, 

and then it progressed to testing pre-core but  

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simplified hypotheses. So many of the studies were 

published in the year 2000. Around the year 2000,  

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they are in paper studies but the hypotheses in 

those studies are very simple and they are using  

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some simple case studies. I call these simple 

cases not because they are case studies. They are  

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simple but they are using simple case studies. 

They just want to make that clarification here  

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and then it progressed to studying the 

interactions and the complexities with  

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formal methods such as network analysis. Also, 

there are more studies using in-depth qualitative  

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or quantitative studies. Either case studies 

or large-scale surveys or using archival data  

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and also data availability become much much 

better than 10 years ago. There are many  

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platforms that now release all the non-profit 

annual reports and those annual reports can be  

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scraped by these researchers for research 

purposes. So today I will present three  

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studies. Three previous studies I published in the 

past five years all from a Network perspective.  

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So the personal study is a state power and 

elite autonomy in a networked Civil Society.  

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Let me use a laser pen here. The 

board interlocks Chinese nonprofits.  

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So a few findings from the study. The first one is 

that Chinese foundations have connected together  

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by sharing board members in a structural parallel 

to what is said in corporate corporations in the  

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United States and Europe. This is not surprising 

but it's the first time we see this. We have some  

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evidence about it. The second Advantage is the 

board interlocking leads to the emergency release  

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groups associated with a business, with privileged 

and autonomous Network oppositions so all those  

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Networks, all those Elite groups have autonomy in 

the network and also many of these groups stay led  

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by business events. Certain findings of government 

officials are much less common in these Elite  

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groups of Foundations. Actually, they are actually 

excluded from this number. In these groups,  

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we will see some of the improved oil say some 

data the emergence of this structural autonomous  

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sphere is associated with major political and 

social events in the state Society relationship.

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So what is a board interlocking network? First 

some background about the research setting. Okay,  

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so we have all these boards here all these boys 

about comedy and they're uh connected. They have  

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some board members serving on this board, 

right? So we can draw a network graph like  

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this with the board here and the bottom number 

here, right? So through sharing board members,  

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if we're just focusing on Boeing 3M Manpower and 

this MGM, we can redraw this graph as a kind of a  

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boarding clocking Network. This is a transcribed 

Network graph like Boeing and Manpower. They are  

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connected through this board member and also MGM 

is connected to Manpower through this bar member.  

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However, MGM and Manpower are not connected 

because the two companies do not share board  

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members right. So why this is important? Because 

boards of multiple relations, share members in  

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common and then they will share values and it is 

also possible for them to solve the coordination  

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problems in this in a decentralized patient right 

also there are plenty of studies on business and  

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corporations but a number of offices and not a lot 

of them. So in an authoritarian country in country  

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like China, we can expect that this kind of board 

interlocking network has political implications.  

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There are two questions. For example, they can be 

utilized by the state to control the non-profit  

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sector, right. So they can assign government 

officials to the sport and makeup and they can  

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assign other government officials on this board 

right. So they try they can assemble a network and  

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they can utilize networks to efficiently 

co-opt or control the non-profit space.  

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However, as I said before, the number of nations 

is not a passive reaction right. They can also  

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utilize these government officials as assess 

points to power assess points to the political  

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arena. Otherwise, they have no approach to assess 

those political spaces right. So they can also be  

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utilized by nonprofits to reduce state control. T 

has published a paper in 2018 I shoot that paper  

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before you can. When you get the slides, you can 

take a look at that paper published in governance  

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and talk about how these non-profits actively 

use these political Elites as sales points to  

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political power which is a fascinating study. 

So some evidence about the claims of the body  

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interlocking network of Chinese foundations. 

There is a network like this so all these nodes  

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in this network are foundations node size 

represents PageRank. You can think of the  

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page rank as the important when you talk about 

the importance. There are many ways to Define. I  

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will skip the details but a way we can measure 

the importance of the node in the network.  

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The node color represents community so there are 

all these blue colors all these light blue colors.  

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They represent some of the Nations, they are in 

the same Community, they're in the same camp.

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So what we can get from this graph. Some 

statistics here. So here we present all these  

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in clusters and this size means that how many 

nodes are there in one of the clusters? And also  

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the average degree measure they are connectedness. 

So if the degree is higher being there on average.  

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Each node, for example. So in this cluster one, 

there are 91 nodes in cluster one and on average  

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each node has about 5.4 connections with each 

other, right or with other nodes and the page rank  

00:24:34.380 --> 00:24:41.220

percentage is about 11. And the government which 

means their importance if you compare the number  

00:24:41.220 --> 00:24:47.040

with others you will see the central cluster. The 

largest cluster is very important in terms of page  

00:24:47.040 --> 00:24:55.140

ranking and their government presence is low, they 

only have about 2.1 percent government credits.  

00:24:57.120 --> 00:25:09.780

As you see, if we see these clusters as the 

Clusters grow or diminish not grow, as a cluster  

00:25:09.780 --> 00:25:15.720

size diminishes, most of the Clusters will be 

in the peripheral positions on this network  

00:25:15.720 --> 00:25:21.780

and we see their connectedness decreasing, 

their importance is decreasing. However,  

00:25:21.780 --> 00:25:28.260

their governance presence is increasing, which 

means if we take the reversal logic is mean which  

00:25:28.260 --> 00:25:33.840

means in the center of the network, actually, 

there are low credits of common officials but  

00:25:33.840 --> 00:25:38.640

in the periphery of the network there are 

a high presence of the government officials  

00:25:40.080 --> 00:25:45.180

which we can say possibly say government 

officials are marginalized in this network.

00:25:47.760 --> 00:25:52.740

So let's run some statistics, and run some 

regression. There are probably some kind  

00:25:52.740 --> 00:25:58.560

of confounding variables right. So uh what 

we can do is we can put those invulnerable,  

00:25:58.560 --> 00:26:06.060

those alternative examinations into a regression 

model and see how the government officials perform  

00:26:06.060 --> 00:26:11.700

right. So this network, I omitted some of 

the control variables, I just assure you  

00:26:11.700 --> 00:26:16.440

the independent variable over here, are this 

current government official and the retired  

00:26:16.440 --> 00:26:24.780

senior government official on board. These are the 

variables we use to operationalize state power. We  

00:26:24.780 --> 00:26:30.000

are using two data sets here. One is reporting 

data set from my annual report because of the  

00:26:30.000 --> 00:26:36.300

accuracy issue we're also hand-coding manually 

coding some of the subset data set to try to  

00:26:36.300 --> 00:26:42.780

verify and try to do a robustness test. So from 

this there, we are using the presence they say  

00:26:42.780 --> 00:26:49.080

power to predict the connectedness of nodes in the 

network, in different networks, public networks,  

00:26:49.080 --> 00:26:56.160

and non-public Networks. There are two types 

of organic foundations in China: non-public the  

00:26:56.160 --> 00:27:00.720

non-public foundations in China sometimes. They 

were called private foundations but they are not  

00:27:01.320 --> 00:27:06.120

the private foundations that we are talking about 

in the United States. They are non-public because  

00:27:06.120 --> 00:27:13.620

they are not allowed to do public fund ratings 

so that's why they are called non-public and most  

00:27:13.620 --> 00:27:21.780

of these non-profit Nations are foundations. They 

are organized by those business leads, thank you.  

00:27:22.380 --> 00:27:28.860

So what we can get from these results, you see 

the common official, have a negative coefficient  

00:27:28.860 --> 00:27:37.380

which means there are more common officials on the 

board of Foundations. The foundation will be less  

00:27:37.380 --> 00:27:43.500

connected in the network right especially this is 

especially true for the non-public foundations.  

00:27:44.580 --> 00:27:54.360

The network is a network organized by non-common 

foundations for the public network. We see some  

00:27:54.360 --> 00:28:01.740

signal from the reporting data set because there 

are more data points here so for the public that  

00:28:01.740 --> 00:28:07.200

most of them are government control relations so 

it's not surprising but here we get some direct  

00:28:07.200 --> 00:28:12.480

evidence to show you the non-public foundations 

are preferentially excluding these current  

00:28:12.480 --> 00:28:16.620

government officials from the highest degree 

notes even when controlling for other variables.  

00:28:18.420 --> 00:28:25.620

So next we want to see how these kind 

of influenced how these coefficients  

00:28:25.620 --> 00:28:32.700

are influenced by some historical event. We select 

several events in the past two decades. One is the  

00:28:32.700 --> 00:28:40.200

TMS Square per test. The second one is a fourth 

world conference on Women which was assembled  

00:28:40.200 --> 00:28:46.980

which was organized in 1995. In 2004, there is 

the first regulation on management foundations.  

00:28:46.980 --> 00:28:53.640

This is the first regulation on how to establish a 

foundation which means now there's a way everyone  

00:28:53.640 --> 00:29:01.800

has the possibility to establish a foundation 

of Their Own. In 2008, after the earthquake,  

00:29:02.880 --> 00:29:08.820

a lot of non-profits in China, 

self-organized to help with disaster relief.  

00:29:09.900 --> 00:29:19.680

So the last one is the 12th Five-Year Plan, this 

kind of national plan dictates the development  

00:29:19.680 --> 00:29:25.080

of the entire country for the next five 

years in social, economic, and political,  

00:29:25.080 --> 00:29:32.640

all kinds of areas in Chinese. We say so for 

this Five-Year Plan one of the most important  

00:29:32.640 --> 00:29:37.200

kinds of policy planning tools in China 

right now. So for the 12th Five-Year Plan,  

00:29:37.200 --> 00:29:43.800

there is one entire chapter talking about social 

management Innovation as a key government Target.

00:29:45.480 --> 00:29:51.480

So still here we have this regression 

here we see this negative coefficient  

00:29:51.480 --> 00:29:57.540

here right. So if we visualize 

this negative coefficient by year,  

00:29:57.540 --> 00:30:05.760

then we can see how these coefficients have 

been evolving in the past two decades right.  

00:30:05.760 --> 00:30:13.440

So what we can see here like this blue color, 

this blue coefficient here which is the common  

00:30:13.440 --> 00:30:24.180

officials on non-public foundations is to become 

significantly negative so it is after, you see,  

00:30:24.180 --> 00:30:31.800

after 2004 after the first regulation on how 

to establish foundations. The two coefficients  

00:30:31.800 --> 00:30:40.380

start to diverge, right, start to diverge 

after this is this trend is very obvious  

00:30:44.700 --> 00:30:55.080

after 2008 the earthquake, and then when progress 

through the year 12th Five-Year Plan you see it's  

00:30:55.080 --> 00:31:03.360

very obvious for government officials to be 

excluded in non-public Networks and for those  

00:31:04.020 --> 00:31:10.560

government officials more likely to be on the 

public network right. So it's the Divergence  

00:31:10.560 --> 00:31:19.140

here is very obvious and they are connected to 

many of the important historical events here.

00:31:23.340 --> 00:31:28.260

So second study. The first study talks 

about the relationship from the structural  

00:31:28.260 --> 00:31:34.440

perspective. The second study talks about, I 

was trying to understand how the results flow  

00:31:35.280 --> 00:31:40.200

between the government and non-profit 

relations. So this study considers  

00:31:40.200 --> 00:31:45.300

the effects of common accounting on 

nonprofits from a network perspective.  

00:31:46.020 --> 00:31:51.960

I found a substantial crosswise crowding in 

effect at the ego Network level and an increase  

00:31:51.960 --> 00:31:57.900

of one Chinese yuan in government funding to 

non-profits neighbor organizations in both  

00:31:57.900 --> 00:32:03.420

interlocking Networks can increase the private 

giving choose a nonprofit by 0.4 Chinese Yuan  

00:32:03.420 --> 00:32:08.700

probably a little bit confusing here. What I'm 

talking about across wise what I'm talking about  

00:32:08.700 --> 00:32:14.460

the neighboring I will elaborate on that later. 

So what is crowding out the private donation?

00:32:17.220 --> 00:32:22.680

Here we see conventionally see the government 

gives money to a non-profit Nation right  

00:32:22.680 --> 00:32:28.020

and as a private donor I would say, okay this 

number of nations get funded from the government  

00:32:28.020 --> 00:32:33.900

and already paid tax for the paid tax to a 

government right so why do I need to still  

00:32:33.900 --> 00:32:40.260

give to the non-profit since the non-profit is 

already supported by me through tax right. So  

00:32:40.260 --> 00:32:46.380

this kind of economic assumption about the 

crowding out effect of government funding.  

00:32:47.220 --> 00:32:55.260

In theory, every one-dollar government gave to 

the non-profit will crowd out one dollar private  

00:32:55.260 --> 00:33:01.560

giving that's, in theory, a lot of improved 

studies say it's not a one-to-one crowding out  

00:33:02.760 --> 00:33:07.920

relationship. This is a conventional 

idea about the relationship here right.  

00:33:08.460 --> 00:33:12.720

It is not considered a social relationship. 

However, if we're considering social relations  

00:33:12.720 --> 00:33:17.760

the director crowding out relationships 

is still here right. But let's say  

00:33:24.900 --> 00:33:33.300

I will not give to the non-profit, but I will give 

to non-profit A and B right I shift my funding to  

00:33:33.300 --> 00:33:37.440

different number relations, to different number 

validations, right. I'm not as reducing my given  

00:33:37.440 --> 00:33:45.180

I just shifted my given to other non-publications. 

So this is how I know there are not five nations,  

00:33:45.180 --> 00:33:49.560

there are these nonfoundations that can be 

connected to some social relations like body  

00:33:49.560 --> 00:33:56.400

interlock right. They're sharing model members so 

if this kind of crosswise crowding or crowding out  

00:33:56.400 --> 00:34:03.960

is supported it means okay the funding can 

be redistributed through social relations.

00:34:09.900 --> 00:34:17.820

So here this graph is considering social 

relations. Now we have the two variables  

00:34:17.820 --> 00:34:23.220

and I'm studying this paper as direct 

crowding out and crosswise crowding out.

00:34:30.540 --> 00:34:31.980

Sorry about that.

00:34:34.980 --> 00:34:39.960

So next we need to use formal 

test to test these hypotheses.

00:34:44.520 --> 00:34:50.640

In this regression table, we are predicting 

the private donation to nonprofits  

00:34:51.180 --> 00:34:55.560

so here we are predicting the private 

donation nonprofits and the explanatory  

00:34:55.560 --> 00:34:59.880

variables are direct Government funding 

and also neighbor Government funding.  

00:35:01.200 --> 00:35:07.620

So for the three columns you see here is 

some baseline analysis. For this Baseline,  

00:35:07.620 --> 00:35:15.300

it's easy to run but the disadvantage of this 

Baseline there are more kinds of compounding  

00:35:15.300 --> 00:35:22.980

variables or alternative explanations here 

cannot be brought out for these three columns  

00:35:22.980 --> 00:35:29.820

we are using organizational-level fixed effect 

to run assets which means we can control more  

00:35:33.300 --> 00:35:40.320

component variables or a third part third-party 

variables or external variables which influence  

00:35:40.320 --> 00:35:44.940

the relationship between both direct to 

government confounding and our dependent variable.  

00:35:46.980 --> 00:36:00.480

Here these three columns are more robust foreign 

relationships between direct and government  

00:36:00.480 --> 00:36:07.020

funding on the private donation to nonprofits. 

Here this is negative, which means if Government  

00:36:07.020 --> 00:36:13.680

increases funding the private donation will 

decrease which is crowding out the effect  

00:36:13.680 --> 00:36:22.500

right but if we use a more robust analysis here 

we see that negative effector goes away right.

00:36:25.620 --> 00:36:31.380

This is our interest here the neighbor's 

government funding so which means as a  

00:36:31.380 --> 00:36:36.420

nation whether my neighbor in the nation 

getting are getting the government grant.  

00:36:36.420 --> 00:36:43.800

What's our neighbor animation so so if I am 

an organization is my neighbor organization  

00:36:43.800 --> 00:36:48.660

which means I am receiving a government 

grant right. So according to this Theory  

00:36:49.380 --> 00:36:56.460

I will as an organization a should be able to 

receive more private given because the private  

00:36:56.460 --> 00:37:02.160

giving donors will shift their given to me 

instead of giving to him because I already  

00:37:02.160 --> 00:37:05.160

received Government funding and if 

the donors know about that right.

00:37:07.860 --> 00:37:15.960

So let's see the relationship is positive 

which means if my neighbor organization that's  

00:37:15.960 --> 00:37:21.600

all Nation I receive Government funding as an 

alternation I will receive more private donation

00:37:26.280 --> 00:37:31.980

And the coefficient side is almost around 

0.4 right which means if my neighbor gets  

00:37:31.980 --> 00:37:40.380

one dollar from the government as a labor 

operation I will get about 0.4 dollar effect  

00:37:41.100 --> 00:37:45.840

I will get more I'll get 0.4 

more dollars than previously.

00:37:48.300 --> 00:37:58.800

So what we can see is we have direct evidence 

to see here that is a crosswise crowding out  

00:37:58.800 --> 00:38:06.060

across. In fact, this is crowding Inc because 

again moment right okay. The second study talks  

00:38:06.060 --> 00:38:11.340

about money and how this kind of resource flow 

through the network perspective. So the next study  

00:38:12.120 --> 00:38:20.100

um uh I was wondering okay there must be some 

political ideas um sitting um uh non-profit  

00:38:20.100 --> 00:38:28.020

board and they're also government officials right. 

So they are very important channels to negotiate  

00:38:28.020 --> 00:38:36.060

to communicate the two spaces. So that's my 

search study bridging State and nonprofit  

00:38:36.060 --> 00:38:41.040

differentiated in the business of Chinese politics 

at least in charitable foundations. It was in  

00:38:41.040 --> 00:38:46.260

this paper I was wondering how are politically 

disembedded in both civil and critical domains?

00:38:49.680 --> 00:38:54.360

The political Elites can build horizontal 

connections with foundations helping the  

00:38:54.360 --> 00:39:01.320

party State reach non-profit actors right 

especially for those government officials  

00:39:01.320 --> 00:39:09.000

they were assigned to the non-profit nations 

board they can be the common government's assess  

00:39:09.000 --> 00:39:14.220

points to the Civil Society and also they 

can also build a vertical connection with  

00:39:14.220 --> 00:39:20.460

the political groups helping foundations assess 

political resources right. So these number of  

00:39:20.460 --> 00:39:26.940

actors they can also utilize these political 

ideas through which political assistants  

00:39:28.440 --> 00:39:33.900

so we can call these political IDs they are 

doing really needs right because they are double  

00:39:33.900 --> 00:39:38.280

embedded. They are embedded in the non-profit 

sector and they are also embedded in a political  

00:39:38.280 --> 00:39:45.240

space. We can also theorize that they're connected 

in this with foundations and in poverty varies by  

00:39:45.240 --> 00:39:51.120

their primary positions in the political system 

which we can say Okay CCP members must be tightly  

00:39:51.120 --> 00:39:57.660

connected in both spaces because they are they 

try to keep the focus on everything right. So  

00:39:57.660 --> 00:40:05.880

that's our assumption let's see how it goes yeah 

so visually we can have this in mind here so here  

00:40:05.880 --> 00:40:10.980

this is a political Network right so all these 

nodes the application this this red node they  

00:40:10.980 --> 00:40:15.840

are tightly this window they tightly connected 

in the political Network and also the red node  

00:40:15.840 --> 00:40:21.960

the same node here and the non-profit Network 

they are also connected to other uh actors in  

00:40:21.960 --> 00:40:26.400

The non-profit Network and non-profit space so 

they are double embedded and they are dual relates  

00:40:27.960 --> 00:40:32.280

according to this we can have some a few 

typology of this Dura political release  

00:40:32.820 --> 00:40:39.000

so if if the political release they have strong 

in values in non-profit in a non-profit sector  

00:40:39.000 --> 00:40:45.780

they are State agents they are ideal State agents 

for assessing civil uh Civics resources so if they  

00:40:45.780 --> 00:40:51.480

have strong Connections in political space which 

is mean they are playing like evidence is wrong  

00:40:51.480 --> 00:40:58.200

they can serve as access points to the party state 

right so the number of Asians can utilize these uh  

00:40:58.200 --> 00:41:02.760

these political actors to assess the party 

state if they have weak Connections in the  

00:41:02.760 --> 00:41:08.460

non-profit in Badness uh number if they have weak 

non-profit business they are weak State agents  

00:41:08.460 --> 00:41:14.640

in non-profits if there are weak Connections in 

the political space they are ineffective access  

00:41:14.640 --> 00:41:20.940

points to political resources some examples 

here like uh State agents uh these this node  

00:41:22.260 --> 00:41:27.960

they have strong connection in the non-profit 

space right so the for the government they can  

00:41:27.960 --> 00:41:35.820

assess this non-profit world through this node 

so if they have they have they have uh they can  

00:41:35.820 --> 00:41:40.800

also have high kind of degree Connection 

in the political uh in Badness like this  

00:41:40.800 --> 00:41:45.840

node it is connecting the political Network so 

they can be utilized by non-profits to assess  

00:41:45.840 --> 00:41:51.780

the clinical power like this note there are weak 

Connections in non-profit work so you may not be  

00:41:51.780 --> 00:41:57.420

able to expect the um uh impact of a lot of work 

can be done by these nodes because they are weekly  

00:41:57.420 --> 00:42:03.900

connecting non-profit space and this uh this 

this node uh even they are embedded in clinical  

00:42:03.900 --> 00:42:09.000

Network you see this node is almost isolated from 

others so what you can expect from this node in  

00:42:09.000 --> 00:42:13.020

political Network almost nothing because they're 

isolated by themselves in the political Network

00:42:15.480 --> 00:42:16.200

some evidence

00:42:19.020 --> 00:42:24.300

surprisingly CCP is not connected it's 

not a kind of a embedded here so here  

00:42:24.300 --> 00:42:29.400

what I'm doing is I'm predicting the 

embedness in the nonprofit space and  

00:42:29.400 --> 00:42:35.460

in the political Space by Presidential uh 

by presidential terms like this is a who  

00:42:35.460 --> 00:42:39.900

uh toaster this is a shame in the 

term this is a political investors

00:42:39.900 --> 00:42:48.840

as well so my assumption here is that they are 

connected in this the connectedness of these  

00:42:48.840 --> 00:42:54.780

or these political Elites will vary by their 

primary positions in believable system because  

00:42:54.780 --> 00:42:59.220

you know not all the government officials 

are equally the same in the same space okay  

00:43:00.180 --> 00:43:06.660

so CCP is not surprisingly CCP is not entirely 

connected to both spaces in all presidential terms  

00:43:07.200 --> 00:43:11.400

well which which makes sense because the CCP 

cannot control everything although they expect  

00:43:11.400 --> 00:43:16.620

to conversate but if you see the chapters 

the official chapters uh the ccp's role is  

00:43:16.620 --> 00:43:21.300

try to lead but not control everything 

right and there are they are just more  

00:43:21.300 --> 00:43:27.120

nuanced ways to interact with Society instead 

of directly embedding themselves in the society  

00:43:27.720 --> 00:43:34.680

but for the uh cyl the China Young's League 

um China communist just living here they  

00:43:34.680 --> 00:43:39.420

are tightly connected in both terms they are 

tightly connecting a nonprofit a non-profit  

00:43:39.420 --> 00:43:45.300

sector but they are weekly connected or they are 

excluded from these political political uh World  

00:43:46.380 --> 00:43:50.100

um there are a lot of studies I will not 

mention them here so talking about the cyl  

00:43:50.100 --> 00:43:57.000

uh like the the as you probably know the 

time pay right the the cyr click the the  

00:43:57.000 --> 00:44:03.060

Communist youngsta Clique within the system right 

within the political system and in the political  

00:44:03.060 --> 00:44:08.160

system these cyl leaders they are excluded or 

they are marginalized in the political system  

00:44:09.480 --> 00:44:15.720

some other uh characters uh because of sacred time 

I just highlighted a few like a mass organization  

00:44:16.860 --> 00:44:20.160

um uh well see why I always mess on the 

nation but here the mass organizations  

00:44:20.160 --> 00:44:25.200

are referring to the Leica women 

Federation and those nominations  

00:44:26.880 --> 00:44:32.400

so they are not tightly connecting the political 

system uh during the whole period but during  

00:44:32.400 --> 00:44:41.280

experience we see um they are connected they're 

connected have increased become positive which um  

00:44:41.280 --> 00:44:47.820

also Echo some of the anecological evidence that 

she says she the president uh put a lot of efforts  

00:44:47.820 --> 00:44:56.880

on um on strengths the stress and the uh capacity 

of this massive relations also schools you see the  

00:44:56.880 --> 00:45:03.600

schools here uh it's positive during the she's 

time so you see as a some unevenola evidence  

00:45:03.600 --> 00:45:09.240

is about the schools are primarily they are 

University principles University principals these  

00:45:09.240 --> 00:45:14.100

universities principles they serve both in uh in 

the previous system and they also see down these  

00:45:14.100 --> 00:45:21.180

number of nations uh uh these foundations boards 

they are connectedness in the political space  

00:45:21.180 --> 00:45:31.260

became more significant positive in streaming's 

Era a notable example is is is a wahoo name who  

00:45:31.260 --> 00:45:36.180

what is a scholar right now is uh is a permanent 

member he's a member in the standing comedy right

00:45:37.800 --> 00:45:44.820

okay that's all my three studies uh I present uh 

for the comments number of relationship in China  

00:45:44.820 --> 00:45:50.580

I probably focus on the network protective from 

structure yeah using the paper title stay power  

00:45:50.580 --> 00:45:55.740

and Lita anatomy in a network of Civil Society 

the boarding clocking of Chinese nonprofits and  

00:45:55.740 --> 00:46:03.000

also I studied the resources founding nonprofits 

in the network Style Network Society toward the  

00:46:03.000 --> 00:46:08.880

network framework of government support and 

also people those purely these ranging State  

00:46:08.880 --> 00:46:13.080

and non-profit differentiated in business of 

Chinese deliveries in charitable foundations  

00:46:14.400 --> 00:46:21.540

a few final results on future studies why 

is about the context so um the reason I put  

00:46:21.540 --> 00:46:26.580

domestic and overseas Scholars here is because 

um sorry about that let's double check the  

00:46:27.900 --> 00:46:35.400

um the chat make sure I'm not going to be on time 

or some reminder here okay okay I'm not seeing any  

00:46:35.400 --> 00:46:43.560

uh warning here so I will keep it going so what's 

up the reason about domestic I overseas here is um  

00:46:44.640 --> 00:46:53.880

I haven't been down any research on China for 

a year or two years already since because I  

00:46:53.880 --> 00:46:59.160

have this kind of this this very kind of strong 

feeling since pandemic I haven't been uh went  

00:46:59.160 --> 00:47:06.960

back to China for about three years I feel I'm 

necessitative to the context to China right now so  

00:47:07.980 --> 00:47:12.900

um all those nuances I originally have a sense 

to have have a sense right now I don't have a  

00:47:12.900 --> 00:47:20.280

sense I feel very unconfident about doing 

research on China and also you see those  

00:47:20.280 --> 00:47:27.780

political Arrangements there they change a lot 

uh before after pandemic right after the uh the  

00:47:27.780 --> 00:47:31.620

last presidential change and not change 

that's Prudential quote-unquote election  

00:47:31.620 --> 00:47:39.420

so I don't have those kind of uh uh those 

those sense of nuances and contexts anymore  

00:47:40.560 --> 00:47:45.660

um I think this is kind of a dilemma especially 

for me as an overseas scholar who have been  

00:47:46.500 --> 00:47:52.080

um not living in that context for a while so I 

think this is very very important for domestic  

00:47:52.080 --> 00:47:57.840

Scholars who who who keep working on this topic 

or who will keep working on related topics as well  

00:47:57.840 --> 00:48:04.080

but as you probably many of you know that it is 

not a as free as what we can do here in the United  

00:48:04.080 --> 00:48:09.780

States on overseas so their research agenda 

that domestic Scholars research gender is not  

00:48:10.380 --> 00:48:17.760

um um it's not a um it's not as free as what 

we can do uh overseas right so that's a I I  

00:48:17.760 --> 00:48:24.900

really feel it's a kind of uh it's it's um as a 

Pity right so um yeah I have no I have no idea  

00:48:24.900 --> 00:48:31.320

about that I don't I don't I'm no way out for 

now I would love to hear more about um uh what  

00:48:31.320 --> 00:48:36.300

Professor Joe will uh share with us and watch 

you as an audience will share with me as well  

00:48:36.960 --> 00:48:42.000

um I think that's a kind of a dilemma for me right 

now the second thing is about messers so I think  

00:48:42.000 --> 00:48:48.420

it's very important to use these methods uh in 

an appropriate way and also novel methods like  

00:48:48.420 --> 00:48:53.520

those computational methods using this in this 

paper I just presented I probably use network  

00:48:53.520 --> 00:49:01.920

analysis message which is not new actually but 

it's novel on this topic so um there need to be  

00:49:01.920 --> 00:49:08.100

more researchers using more normal methods in an 

appropriate way um I think the property is very  

00:49:08.100 --> 00:49:14.520

important instead of normal novelty right so a 

proper ending this is uh is the first is it is a  

00:49:14.520 --> 00:49:20.400

highest principle here if the real question 

require case study we just do case study

00:49:20.400 --> 00:49:28.680

is I did a I did a field work in a 

rural Village uh before pandemic in  

00:49:28.680 --> 00:49:34.860

2019 I really get a lot of kind of uh 

sense of nuances in the rural Village

00:49:37.500 --> 00:49:41.280

um but then there's another pandemic then you 

have been disconnected from that community  

00:49:41.280 --> 00:49:47.400

and the context about three years um you 

you lose that kind of uh sensitivity so  

00:49:48.240 --> 00:49:51.240

um that's kind of a dilemma really 

real dilemma for me right now  

00:49:52.440 --> 00:49:58.200

last point is about data I think it's a great 

opportunity for us right now so there are the  

00:49:58.200 --> 00:50:03.300

data availability is substantially improved ten 

years ago if you found some data about Charlie  

00:50:03.300 --> 00:50:08.820

foundations almost nothing but right now there 

are so many data online um but I need to be in  

00:50:08.820 --> 00:50:16.200

good hands which means um Scholars need to have a 

substantive knowledge on local context and methods  

00:50:17.160 --> 00:50:26.580

um which I feel I'm gradually losing um on 

this front um okay this is among my uh the  

00:50:26.580 --> 00:50:32.640

references mentioned in this study and uh I 

would like to share this slice if you like you  

00:50:32.640 --> 00:50:37.380

can reach out to the organizers and uh look ask 

for the slides and thank you for your attention

00:50:39.720 --> 00:50:48.360

thank you so much Professor Jima for this 

very um empirically driven data-driven and  

00:50:48.360 --> 00:50:59.280

also theoretically grounded uh work and um and I I 

look forward to reading your articles more closely

00:51:02.040 --> 00:51:11.040

on that um so we have a few minutes right now 

we have eight minutes I think we could extend  

00:51:11.040 --> 00:51:19.320

our event for another five or ten minutes or 

so because I have a few questions and then  

00:51:19.320 --> 00:51:27.420

the audience also have questions let me um let 

me ask my questions actually at the conclusion  

00:51:27.420 --> 00:51:36.120

of your talk because you've shared a light on um 

the possibility of future research in developing  

00:51:36.120 --> 00:51:43.920

the view of Chinese philanthropy which is very 

important one is I share with you about your  

00:51:43.920 --> 00:51:54.300

dilemma of um you know doing research in China at 

the current time so could I assume that what you  

00:51:54.300 --> 00:52:03.060

have done so far is really based on the Golden 

Era of Chinese non-profit sector development you  

00:52:03.060 --> 00:52:14.580

know around the 2010s right so that was really the 

golden time between 2004 to 2000 probably 2011 or  

00:52:14.580 --> 00:52:25.380

12. um uh so so I I I you know when I'm not doing 

the kind of what you're doing I also run into the  

00:52:25.380 --> 00:52:34.800

dilemma I I do migration and development and 

there are stuff um also when you run into um uh  

00:52:34.800 --> 00:52:42.480

you know the local context that you feel that you 

know a lot but now you are losing knowledge and  

00:52:42.480 --> 00:52:49.980

um could you um you know I have two questions 

on that so one is what are you your research has  

00:52:49.980 --> 00:52:56.280

been done you what you have been presented 

is during the Chinese golden age and now  

00:52:57.240 --> 00:53:04.560

um you know any challenges when you are doing 

similar type of research and then the other  

00:53:04.560 --> 00:53:13.260

the other question is with the methods so you you 

use a very novel message now you also point out to  

00:53:13.260 --> 00:53:19.320

the appropriateness of the methods so could 

you shed more lights on the appropriateness  

00:53:19.920 --> 00:53:27.900

and then the third one is data so you like this 

is kind of a golden lining you said that there  

00:53:27.900 --> 00:53:34.500

are a lot of data available but it depends on your 

local knowledge and how to you know access to this  

00:53:34.500 --> 00:53:45.900

data so do you have a better way to try to access 

and also to any lessons for the local researchers  

00:53:45.900 --> 00:53:54.720

to access to local data rather than us overseas 

Scholars yeah uh sure um thanks for some of those  

00:53:54.720 --> 00:53:59.700

questions um the first one I would respond to 

is a kind of a one very specific research topic  

00:53:59.700 --> 00:54:04.380

in the future I actually have a very I have 

an interest to work on it but I don't have  

00:54:04.380 --> 00:54:11.100

um since sometimes you you as as a pre-tener I 

need to kind of diversify my investment right so I  

00:54:11.100 --> 00:54:16.980

actually I I probably have three kind of research 

streams one fade a little bit I I have work on the  

00:54:16.980 --> 00:54:22.140

other two research streams and there's one reason 

to speak a research topic on this on on This  

00:54:22.140 --> 00:54:30.060

research stream is about the party Branch so since 

she since she's time they uh the the the the party  

00:54:30.840 --> 00:54:36.540

um stress and the power of the party branch 

in all kinds of units in China especially in  

00:54:36.540 --> 00:54:44.940

non-profit Nations as well right so um I would 

really uh fascinated by how these party branches  

00:54:44.940 --> 00:54:52.680

functions as a kind of a connecting points so in 

that place part in the political Elites example  

00:54:52.680 --> 00:54:57.720

the last paper I studied the Duro Elites right 

they are people they are not institutionalized  

00:54:57.720 --> 00:55:06.660

but she's time he institutionalized this this 

these units right so they are institutions that  

00:55:06.660 --> 00:55:13.620

is more powerful than these these as these people 

the people here right so you know one One Thing  

00:55:13.620 --> 00:55:19.140

Once you institutionalize it is more powerful 

and it's more efficient to do something so  

00:55:19.740 --> 00:55:27.600

how these kind of party branches is working and uh 

what's an influence how how how it is manipulating  

00:55:27.600 --> 00:55:33.060

the two sides and probably manipulating is not the 

correct word but how to connect the two two spaces  

00:55:33.060 --> 00:55:37.260

is really fascinating and there are some data 

here because all these number of nations they  

00:55:37.260 --> 00:55:43.800

need to report their party their activities of 

their party branches so and they need to report  

00:55:43.800 --> 00:55:50.700

that in the in the public report um yeah this is 

a fascinating area I I would love to take a look  

00:55:51.420 --> 00:55:56.640

um this is not new but this is translated from the 

she's time the second response to the tooth data  

00:55:56.640 --> 00:56:03.780

is um I think the for the data first you need 

to know China you need to know how they work  

00:56:04.920 --> 00:56:13.020

um and you you need to know how people 

manipulating those numbers right um so um that's  

00:56:13.020 --> 00:56:18.600

kind of a context that nuances and sensitivity 

is really important which I'm uh gradually losing

00:56:21.240 --> 00:56:26.040

um but on the odd side uh everybody's 

very important is do some dirty work so  

00:56:26.040 --> 00:56:30.360

for this paper there's a data set for the 

database I clean a lot of data by myself  

00:56:31.320 --> 00:56:36.840

um just to go over each of the record and do those 

kind of a dirty work by myself it's very time  

00:56:36.840 --> 00:56:44.460

consuming but it's extremely helpful because since 

I have been working with this data directly I'm  

00:56:44.460 --> 00:56:51.540

very sensitive to the research topics to uh what 

kind of research questions this data can answer  

00:56:51.540 --> 00:56:56.640

what are those caveats what are those missing 

data what are the why those data I'm missing  

00:56:56.640 --> 00:57:05.220

so those caveats I know um I know better if I I I 

if I don't do those dirty work I will do nothing  

00:57:05.220 --> 00:57:10.140

about it so I think those dirty works is really 

really those Hands-On work is very important for  

00:57:10.140 --> 00:57:16.800

me uh which I can do even right now but uh still 

yeah I'm losing on the other hand right the the  

00:57:16.800 --> 00:57:24.420

the the the context the sensitivity about the 

Chinese context uh yeah that's um some of my  

00:57:24.420 --> 00:57:33.780

thoughts yeah that's good and I think how you um 

uh deal with data and then you know do your do  

00:57:33.780 --> 00:57:39.720

the Dirty Work do the Hands-On work by yourself 

that's very important because through doing it  

00:57:39.720 --> 00:57:47.820

even though it's tedious and yeah and also very 

time consuming work but it you know it helps you  

00:57:47.820 --> 00:57:57.360

understand the situation and also to make data um 

analyzable uh so that's that's uh that's great I I

00:57:59.040 --> 00:58:09.960

how to define appropriate right right right and my 

feeling is the formal kind of hypothesis testing  

00:58:09.960 --> 00:58:17.220

is really not a good way to do the research or 

sometimes even it is descriptive that's okay uh  

00:58:17.220 --> 00:58:21.300

because you know sometimes you in our field 

publishing General article is very important  

00:58:21.300 --> 00:58:26.520

right so a lot of Scholars get some data Maybe 

I'm not a lot of Scholars but some Scholars  

00:58:26.520 --> 00:58:31.620

there are some Scholars who are doing this get 

some data and get some hypothesis and test those  

00:58:31.620 --> 00:58:36.900

hypothesis and then get the result this is very 

positive this is kind of very positive Paradigm  

00:58:36.900 --> 00:58:45.120

on doing these in previous studies positivist 

you mean yeah positive I'll lose a lot of those  

00:58:45.120 --> 00:58:51.960

nuances about this about the details there right 

right although my study is like that as well but  

00:58:51.960 --> 00:58:57.840

I know that's my disadvantage right I tried I 

try to avoid that although sometimes most of the  

00:58:57.840 --> 00:59:03.600

time I cannot avoid them but I'm conscious 

about my my limitation here uh so I think  

00:59:03.600 --> 00:59:09.960

um I think the journal uh and other Scholars 

need to be more generous and be more patient  

00:59:10.500 --> 00:59:16.620

uh by generous I mean even in this 

distributed study if it is case study if  

00:59:16.620 --> 00:59:21.480

if it is evidence I think evidence is also 

important if you have evidence to support  

00:59:22.620 --> 00:59:29.220

um and just to to to to to uh disclose 

those kind of nuances those contexts  

00:59:29.220 --> 00:59:36.360

is more important than run those hypothesis 

testing and get all those Stars significance  

00:59:37.320 --> 00:59:43.620

that that that's that's too too simplified so I 

think um if the the general agency needs to be  

00:59:43.620 --> 00:59:48.120

more kind of more generous on this point and also 

you need to be cautious as well because sometimes  

00:59:48.120 --> 00:59:54.000

if we don't have evidence everyone everyone 

can talk about it right like I see uh I see  

00:59:54.000 --> 01:00:00.780

I read a I read a paper I read an article uh a 

conceptual article uh I say oh this is characters  

01:00:00.780 --> 01:00:06.300

are very convincing then I see some comments under 

underneath everyone can talk about it because you  

01:00:06.300 --> 01:00:12.900

don't have data but if I have a data look this is 

what data say right so your alternative hypothesis  

01:00:12.900 --> 01:00:18.000

your alternative assumption does not understand 

or even 80 stand is just a marginal it's a kind  

01:00:18.000 --> 01:00:22.200

of a marginal position so I think this is data 

if you don't have data I don't have an empirical  

01:00:22.200 --> 01:00:28.920

kind of a data uh everyone can talk about it and 

you cannot distinguish distinguine which one is  

01:00:28.920 --> 01:00:38.820

than the others yeah right right so so what you 

are saying is um is using mix assets is kind of  

01:00:38.820 --> 01:00:46.860

the way to go more appropriate you know one is 

you do hypotheses testing and the other one I  

01:00:46.860 --> 01:00:54.780

I like the way you build your typology and then 

use case studies to illustrate the typology rather  

01:00:54.780 --> 01:01:05.220

than just use simply use data to do certain type 

of hypotheses testing so that's good um um let  

01:01:05.220 --> 01:01:15.120

me um run some questions from the practitioner's 

side so here is a question from Marina candonas in  

01:01:15.120 --> 01:01:24.060

China donate to projects and programs outside 

of China for example give non-profits outside  

01:01:24.060 --> 01:01:31.800

of China as a way to collaborate in global 

projects and programs to solve World challenges  

01:01:33.780 --> 01:01:41.280

the answer is yes and there is a kind of a 

movement uh try to try to do that but it is not a  

01:01:42.540 --> 01:01:46.500

I know a lot of Foundations are trying 

to go to the go to Africa right they're  

01:01:46.500 --> 01:01:50.820

trying to support them and also 

the you know the uh project hope  

01:01:51.900 --> 01:01:57.060

they try to develop an African version of 

project Hope by the Chinese Youth Foundation the  

01:01:57.060 --> 01:02:05.220

xionguchan however that doesn't go so goes very 

far from uh from planning and only I think there's  

01:02:05.220 --> 01:02:12.060

only minor uh non-prominations of doing that I'm 

not saying there's no donation to it there are  

01:02:12.060 --> 01:02:20.520

some of the Nations doing that but very minor 

and uh the uh trans kind of a translation money  

01:02:20.520 --> 01:02:28.620

flow is controlled Financial flow is also control 

like in China it's uh we we you cannot transfer  

01:02:28.620 --> 01:02:36.960

money from maybe to US Dollars uh freely right so 

every people individuals have five I think it's  

01:02:36.960 --> 01:02:45.600

uh uh 50 South 50 000 US Dollars equivalent 

uh per year so you can for each individual  

01:02:45.600 --> 01:02:49.620

person you can only transfer that for the for 

the company of a number of nations there must  

01:02:49.620 --> 01:02:54.360

be some kind of restrictions as well but it's not 

very popular you can do but it's not very popular  

01:02:55.980 --> 01:03:03.180

yeah talking about transferring of funds like 

out of China how about private donors donating to  

01:03:03.180 --> 01:03:12.360

organizations I mean to non-profits within China 

um so your talk kind of shed lights on um the  

01:03:12.360 --> 01:03:23.640

the book interlocking relations in the non-profit 

sector now would the private donor donate money to  

01:03:23.640 --> 01:03:30.960

their own like slash money to Their Own Foundation 

or to larger foundations or to smaller non-profits  

01:03:31.860 --> 01:03:41.040

how how to how does like say for example if 

there is a donor who wants to to donate like  

01:03:41.040 --> 01:03:49.800

what would be the uh mechanisms for them to 

donate to a range of different non-profits  

01:03:50.460 --> 01:03:56.580

yeah are you talking about an overseas non-profits 

or no no within China within China yeah yeah  

01:03:58.200 --> 01:04:03.780

um I'm at first I'm not I'm not a wealthy uh I'm 

not a rich person here so I don't have that kind  

01:04:03.780 --> 01:04:11.160

of first-hand experience um uh but secondly uh 

from the information I know about is they have  

01:04:11.160 --> 01:04:16.200

their own channels giving out and they have some 

of them they have their own foundations as well  

01:04:16.200 --> 01:04:22.800

and sometimes when they say do when they say 

we said about a donation it's really uh matter  

01:04:22.800 --> 01:04:28.380

what what they are donating right so when we talk 

about donation we probably are donating out our  

01:04:28.380 --> 01:04:34.320

kind of personal wealth that's our personal money 

right some of them are donating their stock stocks  

01:04:35.400 --> 01:04:39.120

um all kinds of assets they are donating 

their assets instead of their personal  

01:04:39.120 --> 01:04:47.580

wealth or wealth so it's a really uh it's a 

really uh complicated but uh I was it's more  

01:04:47.580 --> 01:04:52.500

like a wealth management project instead 

of just like our average citizen to giving  

01:04:52.500 --> 01:05:00.660

out yeah well well thank you I I think 

I have a lot of questions chance to but

01:05:00.660 --> 01:05:11.520

In the interest of time, we are going to close 

and so thank you so much again for participating  

01:05:11.520 --> 01:05:19.920

in today's event and the event is organized 

by UCLA Asia Pacific Center and I was sent to  

01:05:19.920 --> 01:05:26.520

organize a range of public events workshops and 

international conferences and we will have our  

01:05:26.520 --> 01:05:33.000

training workshop on June 8th and the training 

Workshop is in the afternoon and we would have a  

01:05:33.000 --> 01:05:42.180

panel discussion in the first one hour and a half 

and then a closed session for the students in the  

01:05:42.180 --> 01:05:50.880

workshop. So I hope that you would also zoom in 

on our panel discussion our panel discussion would  

01:05:50.880 --> 01:05:58.620

include first-generation and second-generation 

philanthropists, as well as non-profit practice  

01:05:58.620 --> 01:06:09.720

listeners, talking about you know the importance 

of giving and also the importance of philanthropic  

01:06:09.720 --> 01:06:16.920

work in the community at the community level. So 

please visit our website for specifics and also  

01:06:16.920 --> 01:06:24.300

watch out for our email announcement please join 

me to thank Professor Ma again for his insightful  

01:06:24.300 --> 01:06:30.720

and informative lecture. I also want to thank 

the Cyrus Tang Foundation for their support  

01:06:31.440 --> 01:06:40.680

as well as thanking our Center's Deputy Director 

Aaron Miller, Program Coordinator Jeannie Chen,  

01:06:40.680 --> 01:06:49.020

Graduate Student Fellow Lina Wang, and 

Undergraduate Student Assistant Lillian Shen  

01:06:49.020 --> 01:06:56.400

for their hard work and support behind us. And 

thank you so much and good evening, good morning  

01:06:56.400 --> 01:07:07.020

thank you very much. Do you want to stay on a 

bit, I think Marina wants to say hello right yeah.