Week13 -- My Wikipedia Editing Experience This Week --WU WENHAO

Wu wenhao 2021080464

This week, my Wikipedia editing experience prompted deeper reflection on the nature of "reliable data"—particularly when it comes to citing statistics from Chinese government sources.

While updating the Real estate in China article, I added a paragraph summarizing industry data from the National Bureau of Statistics of China (NBS). The figures tracked the number of real estate enterprises between 2012 and 2023, showing both domestic and foreign investment trends. I ensured the data were up-to-date and taken directly from NBS official yearbooks. However, I soon discovered that this citation might not be acceptable under Wikipedia’s sourcing policies.

According to the Wikipedia:Reliable sources/Perennial sources guideline, official Chinese government websites—such as the NBS—are not consistently considered reliable, particularly on topics that might be politically sensitive or economically controversial. This raised an important question for me: If I cannot use the official statistics bureau of the country in question, then where am I supposed to obtain valid and acceptable data?

This dilemma is even more striking when I consider that Western sources such as the BBC, The Economist, or the World Bank are generally regarded as trustworthy, even when reporting on countries they are geographically and politically removed from. Does this reflect a broader editorial bias that privileges English-speaking institutions and casts doubt on local governmental sources—especially those from non-Western countries?

It is understandable that Wikipedia aims to guard against propaganda or manipulated narratives. Yet, not all statistics released by a government agency are inherently unreliable. Many datasets—like those tracking company numbers, GDP growth, or urbanization rates—are used by international organizations, financial analysts, and academic institutions. In fact, some of the same data I cited from NBS are also featured in World Bank reports, suggesting a level of acceptance and reuse in global contexts.

This led me to explore alternatives. If NBS is not ideal for citation, could I use data from global financial institutions like the International Monetary Fund (IMF), the World Bank, or consulting firms such as McKinsey or PwC that publish market intelligence reports on China? Perhaps academic journal articles that rely on NBS data themselves would provide a more acceptable intermediary. But then again, I’m essentially going in circles—seeking validation from Western institutions for numbers originally published by Chinese authorities.

In the end, this experience has taught me that the issue is not simply about accuracy or transparency; it’s also about trust, credibility, and perceived neutrality. Wikipedia, as a collaborative platform, must constantly negotiate between openness and vigilance. As contributors, we must learn not only how to write factually, but also how to navigate these unspoken politics of information legitimacy.

Moving forward, I plan to strengthen my citation strategies by seeking third-party publications that interpret or analyze Chinese government data, especially from peer-reviewed journals or multinational economic bodies. I also hope to raise awareness within the editing community about the nuances of sourcing in global topics—where a one-size-fits-all standard may inadvertently exclude valid local knowledge.