ITGS, Theory of Knowledge, and Wikipedia!

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Critics of Wikipedia often cite the online encyclopedia’s perceived lack of reliability, focusing on its open nature that allows anybody with Internet access to contribute to its articles. Key concerns are that incorrect or simply fictitious edits might be made, and might remain undetected for months or even years (there are several semi-famous cases that highlight this fact). A related issue arose in a recent TOK class during a discussion about bias in historical sources. One student quoted the old adage “history is written by the victor” and this somehow – in true TOK style, I’m still not sure how – led to us questioning the demographics of Wikipedia’s contributors. While “anybody” can edit Wikipedia, just what does a ‘typical’ contributor or editor look like? Even if the contributions they make are ‘correct’ (always a risky word to use in TOK!), could there be some form of systematic bias or leaning within the articles?As we know from ITGS, “unreliable data” is not necessary a synonym for “incorrect data”. Data may be unreliable if it is:

  • Out of date
  • Incomplete
  • Deliberately altered
  • Accidentally altered

In the context of Wikipedia, we could add ‘Written from a particular perspective’ to this list. But what if the skewed perspective was unconscious rather than deliberate? As it turns out, Wikipedia itself has several pages dedicated to its demographics and possible systematic bias. After some brief research we were able to find a variety of statistics that raise both ITGS social and ethical issues and helped us generate some interesting TOK Knowledge Questions.It is worth noting that there are two common roles played by Wikipedia’s users: Contributors – an open position that allows anybody to edit pages on the encyclopedia, and editors – users who are appointed to resolve issues such as despites and page vandalism. According to Wikipedia itself (which notes that this information is based on a 2010 survey):

contributors can be split into four approximately equal age-groups: those under 18, those between 18 and 22, those from 22 to 30 and the remainder between 30 and 85

In other words, approximately 75% of Wikipedia contributors are under 30. Other interesting statistics, again from Wikipedia, include:

  • 45% of contributors have secondary level education or less
  • 13-15% of contributors are women
  • The majority of contributors speak English as a first-language
  • Most contributors are from the Northern, Western hemisphere

Of course, there are other related issues too – such as the digital divide that we cover in ITGS. Clearly not everybody in the world has the access to computers, the Internet, or even electricity needed to contribute to Wikipedia. Among those that do, it still takes a person of a certain social class to have leisure time available to contribute to Wikipedia instead of doing other tasks such as earning money. Ironically another limitation mentioned by Wikipedia is the lack of sources available to poorer users. Since Wikipedia resources contributions to have verifiable sources, users without access to these potentially expensive items can find themselves unable to contribute to the world’s largest free encyclopedia.

Famous people in Wikipedia


There are so many potential impacts of these demographics that an entire TOK or ITGS lesson could be spent discussing them. Wikipedia cites an example of two articles to illustrate Western-bias: the first about Second Congo War – a five year war that resulted in up to 5 million deaths – is around 5000 words and has 38 sources. The second, the entry for the Falklands War – a much shorter war with a comparatively lower death toll – is around 11,000 words and has 146 cited sources. In another case a survey found that of the 25 most commonly mentioned people in the English version of Wikipedia, only 2 were women – and in the top 20, none were women.

Our the class came to a close we tried to generate some TOK-style knowledge questions relating to the issues we had discussed, and came up with the following:

  • How can we identify systematic bias?
  • Can we ever truly overcome systematic bias in sources?
  • If one source is true, does that automatically mean another source is ‘wrong’?
  • If ‘average’ is used in the mathematical sense, how representative would an ‘average’ contributor be? Is an ‘average’ of knowledge desirable?
  • Is there some information which cannot be simply classified as ‘correct’ or ‘incorrect’?
  • Is there a place for such information in an encyclopedia that aims to be “to be the sum of human knowledge” (which leads us back to a classic open-ended TOK question: “What is knowledge?”

My website has more resources for integrating TOK and ITGS.

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