Does accepting knowledge claims always involve an element of trust?

“Good science doesn’t guarantee acceptance” (Kary et al). This statement underscores an issue in knowledge production: following proper methodology and guidelines doesn’t always entail acceptance. For expert and non-expert communities alike, full acceptance involves applying concepts to various scenarios, though degrees of acceptance can vary. To a lesser degree, acceptance can be tentative despite reservations, or tacitly accepting claims while waiting for confirmation. Since acceptance entails assuming some degree of truth, it involves trust. Trust includes faith in methodology, standards, nature following a uniform pattern, reliability of existing paradigms, senses of knowers and their individual evaluation or collective agreement, and conclusions drawn. The Scientific Revolution, leading to emergence of modern science in 17th century, emphasized importance of objectivity and systematic exploration in both natural sciences (NS) and human sciences (HS). Ever since, the use of scientific methodologies shows experts’ trust in the method’s applications. This essay will examine the necessity of trust in accepting knowledge claims in NS and HS.

In both areas of knowledge, paradigms play a fundamental role in knowledge production. According to Kuhn, paradigm shifts occur when obvious issues are discovered with dominant scientific models, leading to change in prevailing views and understanding of underlying principles (Rees). This may erode trust in existing theories, and rebuilding trust may require time. Yet, this often involves assuming the new paradigm is more accurate than the previous, suggesting some trust is always placed in the prevailing paradigm, in addition to other elements of trust, including faith in expertise, methodology, existing standards, and peer review. 

In NS, trust involves faith in evidence, methodology, and expertise, and empirical evidence is key to accepting knowledge claims. Examples demonstrating contrast between valid claims being accepted or rejected, on the basis of insufficient or questionable evidence, illustrate this. Since falsification constitutes scientific methods according to Popper (Mcleod), trust must be present for scientists to attempt falsifying claims or examine justifications, rather than dismiss it entirely. The rejection of Semmelweis’ handwashing theory in 1859 and acceptance of Cannizzaro’s 1860 atomic weight formula illustrates this (Rochelle and Julien) (Science History Institute). Despite the 8.87% decreased maternal mortality rates after implementing handwashing (Rochelle and Julien), Semmelweis’ theory linking handwashing with puerperal fever was rejected due to lack of trust in his expertise and statistical evidence. Lack of trust in Semmelweis’ case was based on the notion: correlation doesn’t equal causation–infections after doctors conducted maternal surgeries didn’t  prove ‘invisible-particles’ on doctors’ hands. Disagreement stemmed from lack of evidence of bacteria’s existence, resulting in uncertainty regarding Semmelweis’ hypothesis as statistics weren’t considered sufficiently empirical. Semmelweis was sent to an asylum (Wright-Mendoza). In contrast, Meyer and Mendeleev’s affirmation of Cannizzarro’s formula led fellow chemists to trust Cannizzaro’s expertise, despite Cannizzaro being relatively unknown (Science History Institute). This trust allowed scientists to attempt falsifying Cannizzaro’s formula, obtain objective evidence, conduct peer review, finally arriving at expert consensus based on evidence consistency and coherence with existing knowledge and allowing acceptance and official recognition of Cannizzaro’s formula, enhancing understanding of chemical nomenclature. The contrast between rejection of Semmelweis versus acceptance of Cannizzaro shows trust is necessary to facilitate scientific progress.

Yet, when absolute epistemic certainty is unattainable, this questions whether acceptance can occur without trust regarding claims scientists may not fully understand. Scientific community’s behaviour entails experts assessing research integrity and existing discoveries. Falsification encourages scientists to raise questions, resulting in a paradox of trust and falsification in research culture. Experts undertake replication, potentially furthering distrust when studies and results are unreplicable. For example, due to lack of empirical evidence in quantum physics, a 2015 poll showed over half didn’t understand certain aspects (Carroll). This suggests trust may not be present in acceptance of quantum physics but there could be trust in other evidence, like logic and mathematical proof. One example is Schroeedinger’s wave functions. Scientists doubt yet accept Schroedinger’s claims. Physicist Cavalcanti stated they’re facing “something of a reality crisis” (Cavalcanti). Though scientists like Christianto highlight “deep problems'' (Ritchie et al) with the theory, they accept to the extent of teaching it to students, showing acceptance despite lack of complete understanding or trust in certainty. When it comes to phenomena yet-to-be-observed or yet-to-be-proven, provisional acceptance can occur, regarding claims as usable until falsified, even without trust or full understanding.

Yet, arguably, acceptance of claims always involves some element of trust in scientific enterprise or underlying paradigm. Despite paradigm shifts in scientific history, we continue to trust existing paradigms. Trust remains “deeply embedded” (Zak) with “biological basis” (Merolla et al), suggesting it’s an unconscious aspect in all acceptance. In NS, observation in collaborative scientific research implies trust in one's senses and in collective agreement of observations. Degrees of trust are thus shaped by different proofs and methods, leading to different degrees of trust in different areas of knowledge. Without complete understanding, there can possibly be trust in logic of the argument. In Schroedinger’s equation, scientists continue attempting to prove and provide solutions to potential issues since 1930 (Ritchie). The nature of attempting to find proofs implies trust in validity and existence of evidence. For example, experts and non-experts all accepted Soviet scientists’ false polywater discovery due to trust in credibility and professionalism, demonstrating how trust could be misplaced (Stromberg). Without peer review, results can be deceiving, yet these can be affected by errors in peer review, leading to mistaken beliefs. However, continued scientific inquiry into claims suggests elements of trust remain necessary for scientific claims. Acceptance in NS involves faith in experts to attain greater accuracy over time. For example, kilo’s redefinition based on Einstein’s quantum-theory (Letzter) suggests trust in applicability and reliability of theories, showing how scientists redefining concepts using new justifications and evidence requires trust in consensus prior to acceptance. Additionally, Reproducibility Project 2020, attempting to replicate experiments to address problematic studies (Baker) shows trust in current research practices despite problems occurring in past studies. This implies when new knowledge claims are made, trust in some factors, like process, method, credibility, applicability, reliability, or consensus and standards, remains necessary.

Arguably, knowledge acceptance in HS needs more trust than in NS, as ethical constraints present limitations in conducting and replicating studies. As HS involves patterns relating to individuals and societies, human participants play a key role. When unable to use rigorous methodology due to ethical reasons, thus lacking certainty, trust may be obtained through expert consensus and peer reviews. These either validate reliability of conclusions drawn, or acknowledge limitations but deem it sufficiently significant and applicable. In certain cases, it is difficult to control or consider all factors surrounding what is examined. For instance, the initial 1980s Marshmallow Experiment linked academic success to children’s ability to delay gratification by refrain from eating marshmallows immediately (Mischel et al). However, Mischel’s research failed to examine socio-economic factors influencing results. A 2018 modified replication suggested environmental factors and perceived stability of the world greatly influenced children’s wait-times, indicating self-control ability wasn’t the sole determinant of differences in results (Kidd et al). This illustrates how human behavioural studies are difficult to control and can be approached from different perspectives, thus causal relationships are difficult to establish. Yet, for an experiment to be replicated, some form of trust is needed in original conclusions, research aims, or value of research. Similar to NS, peer review plays an important role in assessing claims, evidence, research methodology, and justification provided by experts. Required performance of peer review demonstrates trust in expert communities to uphold standards, professionalism, and capabilities in identifying fraudulent research. When all this is missing, valid theories can be rejected despite evidence being provided. This happened to Nobel winner Ackerlof’s “Market for Lemons.” In 1970, Ackerlof discussed how imperfect knowledge could lead to lemons market under conditions of asymmetric knowledge (Akerlof). Ackerlof’s paper was rejected for five years due to lack of trust in his expertise, implying how trust is needed in acceptance of claims in HS.

However, what constitutes an element of trust in HS? In HS, elements of trust include trust in cognitive processes and tools, consistency of nature, and reliability of existing paradigms. These relate to degrees of acceptance, including provisional acceptance. Arguably, complete trust is necessarily essential in provisional acceptance, as claims are refined, reviewed and evaluated. The emergence of new fields of study like globalization indexes illustrates this. Two prominent indexes are KOF and Maastricht, yet other indexes have been proposed, like New Globalisation index (Huh and Park) (Samimi et al). While the indexes provide justifications for why they included certain measurement-indicators, it remains somewhat questionable what ‘trust’ would involve. Amidst expert discussions surrounding how globalisation should be measured, acceptance of an index can be considered tentative to some extent. For instance, though New Globalisation Index was developed in 2010, to date it remains less commonly examined compared to KOF and Maastricht. Ongoing discussions and revisions suggests how probabilistic truths are often produced in HS. Proposal of other indexes, like DHL Global Connectedness Index and UNIDO Connectedness Index, have contributed to the discussion of the most appropriate indicator of globalisation (Martens et al). When examining new proposed indexes some experts have accepted but others show ambivalence towards, it’s difficult to say for certain what element of trust is involved, and what degree of acceptance is present. This shows limitations in determining both degree of acceptance and elements of trust present in certain fields of study in HS. 

Overall, in both areas of knowledge, accepting knowledge claims always involves trust, though trust can appear in different forms and acceptance can vary in degrees. Discovering mistrust can lead to skepticism in considering new claims, yet falsification involves trust, and potentially leads to acceptance of new knowledge. Comparing NS and HS, whereas objectivity is required in NS, more uncertainty is created from limited achievable objectivity in HS, so trust may be more crucial in HS. Despite this, trust is essential in the pursuit and acceptance of knowledge in both fields, whether we are conscious of it or not.

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