“The Quality of Knowledge is Best Measured by How Many People Accept it.”

The first predicament in answering this knowledge question is how we interpret the “quality of knowledge”. One framework is akin to the correspondence theory of truth, with the quality of knowledge reflecting the extent to which it objectively reflects reality. This framework is used in many AoKs and can be applied to evaluate the quality of knowledge. We begin by considering some examples in the AoKs of history and natural science, for which the claim holds true within the framework presented above: The principle of normative science, outlined by Thomas Kuhn, claims that scientific knowledge is objective when it fits into a contemporary, generally accepted paradigm .

We define a paradigm as a group of prevailing concepts, assumptions, values and methodologies within a community .

Normative science somewhat aligns with the central knowledge claim, since scientific knowledge can be considered objective without significant falsification, as long as it aligns with a prevailing paradigm. Andrew Wakefield’s study of a correlation between MMR vaccines and autism led to widespread questioning of the usage of vaccines within disease prevention .

However, the resulting anti-vaccination paradigm, in the form of anti-vaccine sentiment in many countries, is not accepted by a majority of the general public. Importantly, most experts within the medical field contest the rival paradigm, regarding it as inaccurate. The claim holds true in this example for a majority of the general public and experts within the fields of science and vaccinology.

The case evokes a new dimension to the central knowledge claim: Instead of measuring general acceptance, should the quality of knowledge be measured through its acceptance by experts within a discipline? This approach seems especially sensical in niche fields like vaccinology, whose understanding in the general public is limited.

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General consensus may be a bad measure for the objectivity of knowledge, since it requires basic understanding of the knowledge production process. Furthermore, many disciplines rely on peer-review when measuring the quality of arguments presented, laying the responsibility of fact-checking on a small group of experts, rather than the general public.

The process of peer review is widely applied within historiography when discussing contested historical interpretations. Whilst researching my Extended Essay, I read Susan Bordo’s “The Creation of Anne Boleyn”, and G.W. Bernard’s “Power and Politics in Tudor England”. Bernard argues that Anne Boleyn was guilty of the charges leading to her execution in 1536. His opinion is not shared by Bordo and other experts in the field, who call Bernard’s arguments “sensationalistic, poorly argued and flimsy” . Bernard struggles against one of the strongest prevailing paradigms within his field, and there is little chance of a paradigm shift in his favour . The fact that Bernard’s arguments are widely read and criticised by other historians illustrates a major difference between history and science as AoKs.

Whilst both of them rely on empirical knowledge within knowledge production, history relies on imagination and memory as ways of knowing more heavily than science. This leads to a partial impossibility of disproving historical theories; whilst Bernard’s theory is unlikely, it is difficult to disprove. It consequently receives a degree of legitimacy impossible to a scientific theory that could easily be falsified. This characteristic of history is linked to the central claim: Since historical knowledge is difficult to objectively disprove, the general acceptance of a theory, especially amongst experts, becomes a more reliable constituent in certifying its quality. Thus, several historical paradigms can exist at once, and marginal theories are difficult to dismiss entirely.

Contrastingly, scientific paradigms do not tend to co-exist in significant conflict. Within a scientific field there is usually one set of generally accepted paradigms, instead of several contradictory ones. Scientific paradigm shifts can thus be considered more extreme than historical ones, since Kuhn’s normative science entails the necessity of a scientific revolution accommodating new theories in the case of significant contradiction to the prevailing paradigm. In this scenario, much of the knowledge accepted before is re-evaluated according to the emerging paradigm. An example is the revolution of sexology starting in the 1950s, championed by scientists such as Alfred Kinsey and Masters & Johnson. The revolution necessitated a paradigm shift within the field of human sexuality, previously dominated by false medical assumptions based in taboo and restrictive cultural norms. Although scientific knowledge is considered relatively unbiased, due to the possibility of re-creating experiments and testing theories, this is a clear example of cultural bias affecting scientific knowledge.

We can ask ourselves the question: Can biased generally accepted knowledge be of good quality? If we assume that the quality of knowledge is measured by how accurately it describes reality, the answer for our AoKs must be no. Bias naturally eliminates objectivity and should be avoided (whenever possible) in most AoKs. However, bias and propaganda are effective tools for control of the public narrative and assertion of political, social and religious power, which might in itself be one objective of knowledge application. In this case, biased knowledge can be of good quality, since its objective of control is fulfilled. In the example of sexology, biased knowledge was used as a tool to control the population, their reproduction and adherence to marital and social institutions. The revolution alleviated stigma surrounding discussion of human sexuality. We understand that the old paradigm of sexology was a product of its time, and the new paradigm following the scientific revolution reflects its own time.

This brings us to a key problem with the central knowledge claim: If generally accepted paradigms change as time progresses, how can we justify the objective measuring of knowledge according to how many people accept it? In discussing this, we return to the historical example of different characterizations of Anne Boleyn after her death. During the reign of Mary Tudor, imagery of Boleyn as a great whore, witch, and heretic was common. This was based in Mary’s personal, ideological and religious bias against Boleyn, who instigated the downfall of her mother. Contrastingly, during the reign of Elizabeth I, Anne was portrayed as a protestant martyr, a characterization, which, according to modern experts, is equally inaccurate as previous accusations of witchery. After the Tudor vernacular, Boleyn’s characterization fluctuated between these extremes, until the 20th century saw her re-imagination as a radical feminist femme fatale , a popularized and flawed interpretation. This example allows us to consider the role of bias within historical knowledge. If our views are biased by our individual circumstance, can there be any unbiased knowledge, and can we rank knowledge according to its bias?

Revisionism is one school of historiography that comes to mind when considering this question. It assumes that in order to maximize objectivity within historical knowledge production, prevailing historical paradigms should be routinely revised and questioned. This clearly links to our central knowledge claim, since revisionists insist on the questioning of generally accepted paradigms to ensure the health of history as a discipline. Whilst most revisionists would not see their version of history as utterly unbiased, they would probably argue that it is more objective than other historical knowledge. Thus, not only can varying levels of historical bias be recorded, but historical knowledge can and should be evaluated accordingly. Now, how about a case of two equally biased, contradictory interpretations, for example the different views about Anne Boleyn? Can contradictory views or paradigms be considered equally objective reflections of reality?

When it comes to scientific paradigms the answer to this knowledge question must be no. Although previous paradigms are important in giving rise to current standards of scientific knowledge, they are not accepted to objectively reflect scientific reality to the same extent as current paradigms. Considering historical knowledge, the case may be slightly different. Historical theories can be difficult to disprove, due to the nature of historical knowledge production. Some philosophers link this ambiguity to the nature of history itself: The actor-centred philosophy of history defines history as a “flow of human action, constrained and propelled by a shifting set of environmental conditions.” Thus, no historical study can ever accurately portray historical reality, since it necessitates focus on a certain period or region, and cannot take into account the various causes and contexts of each human life, crucial to accurately understand historical realities.

Thus, all historical knowledge is a grave simplification of reality. We mustn’t understand this as a unique quality of history or humanities as AoKs, since many scientific paradigms are simplified when taught, in order to facilitate understanding of complex phenomena . Although historical paradigms, in contrast to scientific ones, are rarely altogether dismissed, the discipline does differentiate between the quality of different paradigms and weighs current and past paradigms differently. The weakness of the central knowledge claim, within the framework of the quality of knowledge measured by its objectivity, is its failure to consider the shifts in generally accepted paradigms throughout time and place.

In order to follow the logic of the claim, the knower must commit a logical fallacy by accepting two mutually exclusive theories to be equal. Although the claim may be useful in comparing the quality of two rival paradigms, it fails to take into account the misinformation and bias characteristic to knowledge accepted by the general population, which would surely weaken the quality of knowledge within both AoKs. We conclude that the claim is not the best measure of the quality of knowledge in our chosen AoKs. Whilst it may be accurate in certain limited examples, standard methods used in both fields are more successful in evaluating the quality of knowledge.