A visible expression of this reflexivity is the so-called limitation section in scientific publications. In this section, the boundaries of a study are explicitly addressed: for example, potential sample bias, measurement uncertainty, or constraints on the generalisability of results. Within the scientific community, this practice is standard and widely regarded as an integral component of sound research.
However, for readers outside a given discipline, this structure often remains difficult to access. While the findings of a study are frequently communicated in highly condensed form, the context of its limitations is often omitted in public reception. As a result, scientific knowledge can appear more complete and definitive than it actually is in its methodological grounding.
This leads directly to the central question:
Does the established practice of scientific limitations suffice to adequately reflect the ontological scope of empirical knowledge?
This question points to a level that remains largely peripheral in many empirical studies: the ontological scope of scientific knowledge. This does not refer to whether a method has been correctly applied, but rather to which aspects of reality are made visible by a given methodological framework in the first place.
An example helps to clarify the distinction. When a study on life satisfaction uses a standardised questionnaire, the usual limitations are typically acknowledged. The sample may be biased. The questions may be interpreted ambiguously. The results may not easily generalise to other populations. All of these are important methodological constraints.
However, a more fundamental question is asked less frequently: does a questionnaire on life satisfaction actually capture the phenomenon in its entirety, or does it only access certain operationalisable aspects of it?
At this point, a different form of limitation becomes visible. It is not that the method is flawed. Rather, every method provides a specific access route to reality while necessarily excluding others. Every empirical investigation is based on selection, operationalisation, and reduction. Complex phenomena are translated into variables, relations are transformed into measurable values, and experiences are converted into data points.
This reduction is not a weakness of science. It is a precondition of scientific inquiry. Without it, comparability, reproducibility, and analysis would hardly be possible. It becomes problematic only when the limits of this reduction fade from view.
For this purpose, I propose the concept of ontological partiality. It refers to the fact that scientific knowledge always captures only a particular segment of its object of inquiry. This claim does not refer to methodological error or insufficient scientific quality. Rather, it describes a fundamental feature of empirical knowledge itself.
Most limitation sections in scientific papers primarily reflect the quality of the chosen method within its analytical framework. They ask how reliably something was measured. Far less frequently do they address which aspects of the investigated phenomenon remain, in principle, outside that framework.
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| Picture: Dimitar Donovski on Unsplash |
This may indicate a largely overlooked gap. Contemporary science possesses an extensive toolkit for reflecting methodological uncertainty. However, comparatively few established routines exist for reflecting ontological constraints.
This becomes particularly visible in the communication of scientific results. Diagrams, metrics, and statistical models often create the impression of a direct representation of reality. Yet these are always methodologically constructed representations of selected aspects of that reality. The presentation appears complete, although it is necessarily selective.
This does not imply that empirical research loses its legitimacy. On the contrary, the strength of scientific knowledge lies precisely in its methodological discipline. Nevertheless, a more reflective approach to research may require not only discussing measurement error, sampling issues, or validity, but also the ontological scope of one’s claims.
The question of scientific limitations may therefore need to be extended by an additional dimension. Beyond assessing how reliable a result is within a given framework, it should also be considered which aspects of reality that framework is capable of capturing in the first place.
The challenge is not to replace empirical science with philosophy. Rather, it is to assess the reach of empirical knowledge more realistically. Scientific results remain indispensable. However, they are not direct representations of reality, but methodologically structured access routes to it.
The question of why ontological boundaries receive less attention in research, teaching, and science communication than methodological ones will be addressed in a subsequent contribution. For now, it is sufficient to note that the established practice of scientific limitations may not fully reflect the scope of its own constraints.i
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