Truth vs. Justification: Why a Well-Justified Interpretation Isn't Necessarily True?

In scientific, theological, and social debates, it is often assumed that a well-justified claim is automatically true. From a methodological point of view, however, these are two different concepts. Truth refers to the relation between a claim and reality, whereas justification refers to the relation between a claim and the available evidence. Confusing these two levels leads to many interpretative errors and to excessive certainty in formulated conclusions.

The classical definition of truth, derived from Aristotle, assumes that a claim is true when it corresponds to the actual state of affairs. Truth does not depend on the number of supporters of a given position, the strength of a researcher’s conviction, or the length of time an interpretation has been accepted.

Truth is not decided by authority, but by reality.

In research practice, however, a difficulty arises: the reality under analysis is very often not directly accessible to observation.

This is especially visible in historical and textual studies. The researcher does not observe the events described in the sources or the processes that led to the formation of a text. The researcher has access only to traces preserved in the form of documents, manuscripts, linguistic data, historical testimonies, or reception materials. This means that knowledge is indirect. The object of analysis becomes a reality reconstructed on the basis of available data, not reality itself observed directly.

In such a situation, it is possible to assess the degree of justification of a given claim, but not to verify it directly. The researcher may analyse the quality of data, compare competing hypotheses, and evaluate the strength of arguments. However, one cannot automatically move from the statement “I have evidence” to the statement “I know the truth.” Between truth and justification there is an epistemological gap that cannot be completely removed.

This phenomenon is well illustrated by the problem of translating biblical texts. A translation does not provide direct access to the original act of communication, but is a reconstruction based on available linguistic, textual, and historical data. This reconstruction may be highly faithful, careful, and methodologically justified, yet it remains a reconstruction. The translator does not reproduce the communicative reality of the author itself, but builds the most credible possible model of it on the basis of preserved evidence. Every translation is therefore an attempt to approach the meaning of the text, not its direct and entirely interpretation-free reproduction.

This means that a claim may be well justified and still turn out to be false. The history of science provides many examples of theories that for a long time were regarded as the best justified explanation of the available data, but were later corrected or rejected. This does not mean the failure of science. Rather, it reveals the limits of human cognition. Justification always refers to currently available evidence, not to complete knowledge of reality.

The reverse situation is also possible. A claim may correspond to reality but remain weakly justified because of insufficient data. In historical research, some hypotheses gained strong support only after the discovery of new sources, manuscripts, or artefacts. Their later accuracy does not mean, however, that they were previously well justified. Truth and justification are therefore not equivalent concepts.

Christ in front of Pilate, Mihály Munkácsy | Wikimedia Commons

One of the most common cognitive errors is to identify conviction with justification. Conviction is a psychological state of the researcher or participant in a debate. It may result from personal experience, tradition, authority, or an adopted worldview. Conviction itself, however, is not evidence. Likewise, a high level of subjective certainty does not automatically increase the epistemic value of a claim. Methodology is primarily interested in the quality of justification, not in the strength of declared belief in a given view.

Evidence-based approaches do not replace truth with the category of justification. Their purpose is not to redefine truth, but to improve the quality of the process by which conclusions are reached. Truth remains the aim of knowledge, while evidence is a tool for assessing whether a given interpretation is better justified than the available alternatives. As we read in the Bible: “but test all things. Hold on to what is good.” (1 Thessalonians 5:21 CSB). From a methodological point of view, this is a call for critical evaluation of claims, not for their automatic acceptance. The higher the quality of data, the greater the transparency of the research process, and the more rigorous the analysis of competing hypotheses, the greater the probability that the accepted conclusion corresponds to reality.

It should be emphasised that evidence-based methodology does not create its own definition of truth. Nor does it replace truth with a research procedure. Its task is to increase the quality of justification through the systematic collection of data, the assessment of their credibility, and the control of the interpretative process. Truth remains the regulative aim of the entire cognitive process. Justification is therefore not an alternative to truth, but the most reliable way of approaching it under conditions of limited knowledge.

From a methodological point of view, research maturity does not consist in declaring certainty, but in consciously managing uncertainty. The researcher should not ask only whether they are right. They should primarily ask to what extent their position is justified in light of the available data and what circumstances could lead them to revise their conclusions. This is why, in an evidence-based approach, well-documented uncertainty is more valuable than unjustified certainty.

Truth remains the point of reference for the entire research process. Justification remains the measure of the quality of the path leading to that aim. The better the data, the more transparent the argumentation, and the more critical the analysis of competing hypotheses, the greater the chance that the accepted conclusion truly corresponds to the state of affairs under investigation.