Since May 1 of 2008, the Regulations on Open Government Information (the OGI Regulations, English translation here) have formally triggered the legal mandate for information disclosure for all government agencies across China. Over the last ten years, much attention has been paid to how much progress towards transparency can be and has been made in a political system long dogged by secrecy, with an enormous amount of ink spilled on this area of law. Yet one issue remains relatively untrodden, if not unknown, among scholars and observers interested in the Chinese transparency regime. That is transparency for public enterprises and institutions.
As part of the legacy from the planned economy of the pre-reform era, public enterprises and institutions, in Chinese 公共企事业单位, also known as state-owned enterprises and state-sponsored institutions, continue to perform a variety of public functions and/or to receive public funds. They still loom large in Chinese people’s lives today, spanning from health care to education, from transportation to electricity. Against this background, the level of transparency of these quasi or non-governmental organizations bears much significance and warrants more attention. In this paper I attempt to fill the gap in the existing literature.
It starts by explaining the legal framework of open public enterprises and institutions in China, paying particular attention to its difference from the same regarding administrative organs and empowered organizations under the OGI Regulations. The previously unnoted dualistic structure within China’s transparency law is pointed out and the 2019 amendment to the OGI Regulations to reinforce such a structure be introduced. I then explain the fourfold conventional wisdom that underpins such a legal change, as articulated by officials entrusted with the drafting task: First, it was believed that because public enterprises and institutions do not qualify as administrative subjects, they are usually unable to enter into administrative litigation. Even if they become defendants, it is difficult, if not impossible, for the courts to review the legality of their disclosure decisions. Second, it was suggested that the responsibility of ensuring public enterprises and institutions’ transparency, including settling grievances arising from lack thereof, is better entrusted to the oversight departments than to the judiciary. Third, the drafters thought that public enterprises and institutions should be considered regulatees whose transparency obligations are different from the freedom of information requirements that apply more generally to the government, and closer to compulsory disclosure requirements imposed on listed companies or charitable organizations. The fourth and last official rationale is that globally, the freedom of information laws primarily target government agencies rather than non-government organizations.
The rest of the article dissects the above reasoning and puts forward counterarguments. It first reports and assesses the transparency performance of the Chinese public enterprises and institutions since the implementation of the OGI Regulations in 2008, particularly in comparison to that of the administrative organs. It will be made clear that public enterprises and institutions had a rather poor transparency record over the last decade or so, due to a lack of hierarchical pressure from the government departments responsible for overseeing their operation. In other words, although it became a legal requirement back in 2008 that public enterprises and institutions should be more open, there has remained a huge gap between the law on paper and law in action. In contrast, as a silver lining, this paper demonstrates that the Chinese judiciary has actually been active yet prudent in scrutinizing public enterprises and institutions’ compliance with the OGI Regulations, in spite of the institutional barrier created by the dualistic structure. The paper then argues that to incorporate public enterprises and institutions into the OGI Regulations is in line with both the Chinese constitutional imperative for participatory democracy and the international mainstream of including non-governmental entities performing public functions and/or receiving public funds in the freedom of information legislation. This means that the underlying rationale for enhancing the dualistic structure by the 2019 amendment is wrongheaded. The concluding part summarizes and makes proposals for further legal reforms in this area.
Chun Peng’s paper is published with the University of Pennsylvania Asian Law Review and available here.
Chun Peng is presently an assistant professor and assistant dean at Peking University Law School. He received his doctorate and master’s degree in law from the University of Oxford and holds a double degree in law and economics from Peking University. He has published widely on Chinese constitutional law, administrative law and comparative law in English and Chinese. Besides scholarly work, he writes op-eds on China and the world at The Diplomat, China Daily and Caixin. His book Rural Land Takings Law in Modern China: Origin and Evolution is published with Cambridge University Press. More recently, he is interested in data governance and privacy law and has published on China’s social credit system and the newly enacted PRC Personal Information Protection Law.
‘The trustworthy shall roam everywhere under heaven, while those who breach trust shall not be able to move a single step’ is the underlying maxim of China’s Social Credit System (SCS) project. Taking a step closer to understand what is behind this rhetoric quickly reveals that the SCS is better to be spoken of in plural, and the initiatives proliferating under it include projects as various as commercial loyalty programs, market regulation measures, and judicial enforcement mechanisms. But what does the central government envision in terms of a comprehensive system? We may find answers by looking at how the central government organs in charge of SCS building regularly assess the progress of the pioneers, cities. This is done through quantified criteria, so called SCS Construction Assessment Indicators. They offer a rare comprehensive depiction of how the perfect municipal SCS looks like in the eyes of the central planners. Based on these criteria, Marianne von Blomberg lays out what it takes to build a municipal SCS.
The National Development and Reform Commission and the People’s Bank of China, two major players in SCS creation, annually issue assessment indicators to evaluate the progress cities make on that front. Those performing best are designated “SCS construction model cities” (社会信用体系建设示范城市). Each of the twelve indicators in every set deals with what may be understood as one construction site within the larger SCS project. This is how they work: For progress on each site, cities get points. Further, a set of “hard indicators” includes ten concrete goals “which all must be completed without exception”. They may be regarded as centrally designed manuals for municipal SCS building which are handed to local leaders.
Filling a gap between the broadly termed conceptual central documents and the orders, legislation and specifications scattered across localities and realms which each relate to one of the SCS’s many parts, they are a rare official depiction of the whole SCS which is, moreover, translated into concrete criteria.
Step 1: Build your infrastructure for credit information production & sharing
The code: Under the unified social credit code, the gathered credit information is allotted to the then credit subjects. Issuing this code to legal persons and other organizations is a first fundamental element in SCS construction that reappears in all sets of indicators with the bar to earn points being raised throughout the years.
The records: Credit information is stored in credit records (信用记录, sometimes: sincerity files 诚信档案) that are to be set up by departments in charge of more than 21 realms as various as tax collection, construction, transport, e-commerce, birth control, education and research, environmental protection, law firms and lawyers, notaries, and for civil servants. In addition, the judiciary and providers of public utilities such as water, electricity and telecommunication are to gather and share information. What amounts to credit information differs across localities and administrations, it is commonly stipulated in credit information catalogues (find an example of such a catalogue here). As of 2019, Hangzhou has collected 140 million pieces of credit information, Suzhou has collected 350 million pieces, and Nanjing 1,4 billion (Zhu Lili 祝丽丽 2019).
The platform: Such credit information, once gathered, is directly to be forwarded to the credit information sharing platform (信用信息共享平台). The indicators of 2016 were the last to ask for the creation of such a platform, it was in the following years treated as given prerequisite. Its vital role in the system is illustrated by the fact that approximately one fourth of all points can only be attained if the platform is constructed. One indicator reads: “0.5 points are deducted for every city-level unit that is not connected to the credit sharing platform and sharing their information”. However, the experience of SCS construction model city Zhengzhou shows that linking up the platform with the sources of information such as administrative departments and providers of public utilities is a significant challenge.
Step 2: Make trustworthiness records the basis for decision-making in public administration
Joint reward and punishment: Joint reward and punishment (联合奖惩) refers to the realization of punishments and rewards in one realm to those entities who have been enlisted for trust-breaking or exemplary trustworthy behaviour in another realm. The ban to book high-speed trains for those who have defaulted on court judgments is an example. Joint reward and punishment was, upon the announcement of the first batch of model cities described as the “ring in the bull’s nose” of SCS construction, that, if being taken care of, will “cause all smaller things to follow.” Correspondingly, it has steadily gained importance in the indicators: 11% of all points in 2017 are to be achieved by implementing joint reward and punishment, jumping to 21% in 2018, and to 22% in 2019. Cities can gain points for example for each case where joint punishment was meted out against a trust-breaking entity or where benefits materialized for the red-listed, as well as for institutionalization of joint reward and punishment, meaning its integration in information systems and work procedures. Hard indicator 11 requires that “the number of realms where the city implements joint reward and punishment is not less than the respective number of realms at national level”.
Regulation by credit classification (信用分级分类监管) refers to adjusting the intensity of market regulation measures, such as random inspections, to the credit status of the relevant subject. Regulation by credit classification is on the ascendant, with a rise in proportional value within the respective sets of indicators of 9%, to 17%, to 22% from 2017-2019. This “novel type of regulation” is not only overhauling traditional market regulation but increasingly a tool for administrative agencies concerned with other realms. Since 2017 it has been woven into other indicator groups such as commercial sincerity, social sincerity and judicial credibility construction.
Step 3: Foster a market for credit products for individuals that make use of public credit information
A score: A municipal social credit score is to be set up for the respective city’s residents using their social credit information (this is what in Hangzhou is called the Qian River Score, in Fuzhou the Jasmin Score, in Suzhou the Osmanthus Score, etc). Through the “credit+ programs” enumerated below, public credit information translated into the score indeed follows a subject into numerous areas in daily life- in a rewarding manner.
Credit+ programs: Integrating market forces has helped to develop credit products that are to be used by local administrations in their daily work so that social credit information directly impacts how convenient a citizen’s everyday life is. In the 2017 indicators still vaguely termed “sincerity conveniences in public service”, the concept has matured into fully-fledged programs such as “credit easing procedure” (信易批) in the course of which administrative agencies tolerate the lack of secondary documents when proceeding requests of high-scorers. Likewise, “internet+credit+medical treatment”, “internet+credit+elderly care”, “credit easing transport” and “credit easing loans”, to name just a few of those programs enumerated in the latest set of indicators, allow high-scoring subjects certain privileges such as fast track handling of paperwork at hospitals.
Step 4: Equip your SCS with remedial paths- or don’t
From a legal point of view it appears striking that the objection procedures laid out at some length in province-level social credit regulations and recently reemphasized by the latest central level SCS guideline are not mentioned throughout the indicators. A careful deduction we can draw from that and the fact that the author could not yet find legal cases involving relevant provisions is that the focus of municipal SCS building lies on pushing forward the system’s coverage first.
Credit Repair: Not strictly speaking a remedial measure, credit repair (信用修复) refers to a procedure with the help of which credit subjects can have unfavourable credit information deleted and relevant punishment halted. They are required to eliminate all damages caused by their “untrustworthy” behaviour, or where that is not applicable, undergo “credit repair trainings”. The indicators award points to cities for cases of successfully completed trainings (possible in online formats and without final exam, making them easily circumventable) and the de-blacklisting of entities as a result of such.
Step 5: Make sure your city has a sound financial environment
Interestingly, the indicator on constructing a trustworthy financial eco-system seems to be standing on its own- other than the other indicators, it makes no mention of the credit sharing platform, blacklists, credit records, regulation by credit classification or other central SCS tools. Instead, points are given to cities on the bases of whether normatively, the level of trustworthiness is high. For instance, where no significant regional financial risk has occurred, the 2019 Indicators award two points. While most of the indicators seek to have a system of dealing with specific trust-related problems set up, the indicator on the financial eco-system is less concerned with SCS infrastructure building, but with the greater goal to achieve a more trustworthy financial environment. Further, this indicator alone is to be evaluated not by the assessment groups that handle the other indicators but by the PBoC alone.
Political ideology: It is less helpful for municipal SCS designers aiming for the title of SCS model city to put much effort on living up to political rhetoric. While the indicators do mention the ubiquitous Xi Jinping Thought, implementing the CPCCC’s and the State Council’s directives on the SCS (all eleven of them which are enlisted, translations here), and Socialist Core Values- The relevance of these elements in relation to the other indicators shrank from 11% in 2017 to 8% in 2018 and 2019, the 2016 indicators and the hard Indicators do not mention them at all.
Innovations and making use of local specialities: Notably, not even this indicator that explicitly encourages experimentation and lists examples mentions the application of AI and other technology that is frequently associated with the SCS. Indeed, the most high-tech element the indicators lay down is the building of the information sharing platform and credit websites. Most technological innovation for municipal SCSs appears to happen within the private sector: Cities gain points for fostering a market of credit products. How such products may eventually be “incorporated” into the larger, centrally driven project was demonstrated in early 2018: The PRC’s first credit scoring services that were given licenses to experiment with their products did not get the license in the end but were made minority shareholders of one PBoC-lead Credit Scoring entity called Baihang Zhengxin (百行征信, the whole story).
Marianne von Blomberg is a PhD Candidate at Zhejiang University’s Law School and Cologne University’s Chair for Chinese Legal Culture and working as a Research Associate with the latter. She is particularly interested in the intersections of the law and social credit and recently focuses on reputational sanctions within the Social Credit System. Get in touch with her on LinkedIn or follow her on Twitter.
Open public data, as a philosophy and a set of policies for increasing the access and use of the dataset of public bodies, has been advocated and implemented across the globe for its promise of increased public accountability among other benefits. Nonetheless, it is often neglected that public accountability is a desired, but not a guaranteed outcome.
Since the first attempt in Shanghai to broaden public data access in 2011, open public data initiatives have witnessed rapid development but also pushbacks from local municipalities and departments, among which lack of willingness in participation and low data quality are the two primary challenges to realize the benefits of local open public data initiatives. As a countermeasure, the local regulators of open public data initiatives in Shanghai have experimented with a novel approach, building on the assumption that the perceived risk of liability in disclosing data is a key barrier for the local municipalities and departments to engage actively with open public data.
In our paper “Decoupling Accountability and Liability”, published recently in Naveiñ Reet: Nordic Journal of Law and Social Research (PDF here), we explore this novel regulatory approach by looking into the recently announced Interim Measures for the Opening of Public Data in Shanghai and the context of their emergence. By unfolding the local regulators’ accounts of the development of the interim measures, we explore: how can interim regulatory measures reduce the perceived risk of liability among public bodies and contribute to accountability of open public data initiatives?
Our findings show that the adopted interim measures have managed to provide both clarity and flexibility to open public data entities, when it comes to opening their data. In particular, the measures institutionalized the roles and responsibilities of these entities by specifying the different categories in which they can be categorized and outlining clearly their specific duties and the circumstances under which they can incur liability. At the same time, due to their interim nature, the measures allowed for certain level of flexibility as they can be easily amended in case they are not optimal. This experimental approach towards regulating open data, which relies on interim, yet specific measures, reduces the legal uncertainty, which open public data encounter when opening their data sets. Thus, they potentially contribute to increased accountability.
In our paper, we also discuss the appropriate level to regulate open data initiatives, an issue which has implications for the ability of the legislators to achieve both, clarity and flexibility of the measures. While the majority of the measures on supra-national (e.g. European Union) or national level remain somehow general and lasting for the foreseeable future, we argue that they cannot substantially reduce the legal uncertainty experienced by public entities, which remain unwilling to participate fully in open data initiatives. In our research, we emphasize the importance of local legislative initiatives to achieve the necessary specificity of the measures, while also ensuring that they remain flexible enough.
Cancan Wang is an Assistant Professor at the Department of Business IT, IT University of Copenhagen, Denmark. She was trained in sociology, ethnology and information systems. Her current research interest lies in the sociomaterial development (e.g., governance, regulation, and organizational arrangements, etc.) of public digitalization (e.g., open data, artificial intelligence, social media, etc.). Feel free to contact her at firstname.lastname@example.org or over LinkedIn.
Kalina Staykova is an Assistant Professor at the Department of Digitalization, Copenhagen Business School, Denmark. She was trained in information systems, inter-national law and management. Her research investigates broad range of issues related to digital platforms (e.g., design, adoption, monetization, regulation, etc.) in various contexts (e.g., digital payments, e-commerce, open data, etc.). Contact her at email@example.com or find her on LinkedIn.