The Classifications of Knowledge
in
The Theory of Acceptance of Knowledge
by Nir Hazon
When knowledge is viewed through the distinction between absolute facts and beliefs, greater clarity can be attained. These two categories provide a fundamental classification of knowledge into what can be regarded as indisputable and what remains subject to question. Within them, additional subcategories of knowledge can be placed according to the manner in which they are obtained and the degree of certainty they provide. For example, knowledge acquired through direct observation belongs to the category of absolute facts (Indisputable Knowledge), whereas knowledge obtained through testimony belongs to the category of beliefs (Questionable Knowledge). A claim of certainty can therefore be justified only when knowledge is obtained through direct observation or when the known fact is established as the only possibility.
Serious consideration should be given to knowledge before we choose to accept it. By distinguishing between knowledge that can be readily accepted and knowledge that remains subject to further consideration, we can make more deliberate judgments about what we regard as true. The following is a classification of the types of knowledge that exist within the Theory of Acceptance of Knowledge. By viewing knowledge through this framework, we can more clearly determine which forms of knowledge warrant acceptance and which should remain open to question.
The Classifications of Knowledge
The following classifications describe how my Theory of Acceptance of Knowledge evaluates different forms of knowledge according to their relationship to evidence and the existence of what they claim to describe.
Indisputable Knowledge
Knowledge that can be accepted with a particularly high degree of confidence within the framework of the Theory of Acceptance of Knowledge.
Observation-based Knowledge is knowledge obtained through direct observation. It concerns information that is directly accessible to observation through the senses or through instruments that extend our ability to observe. Direct observation establishes that something was observed, although conclusions about what the observation means or what will occur in the future may require additional reasoning.
Scientific Knowledge
In this model, information is considered scientific knowledge only when it has been obtained through a systematic process of observation, hypothesis formation, experimentation or testing, analysis, and evaluation according to the scientific method. The defining characteristic of scientific knowledge is therefore not simply that the information concerns nature or is supported by evidence, but that the knowledge was obtained through the scientific method.
When the scientific method produces a result that can be independently tested and replicated under the appropriate conditions, the result provides evidence that the phenomenon being investigated exists and that the observed relationship is not merely the result of an isolated observation. Replication is therefore an important means of strengthening the acceptance of scientific knowledge.
Under this classification, a claim does not become scientific knowledge merely because it is stated by a scientist, appears in a scientific publication, uses statistics, or concerns a scientific subject. The method by which the knowledge was obtained is what determines whether it qualifies as scientific knowledge. This distinction is important because scientific terminology or the appearance of scientific research should not be confused with knowledge actually obtained through the scientific method.
Knowledge of the Only Possibility
If we know that something is the only possible explanation or outcome, then we can accept it as knowledge. When multiple possibilities initially exist, we can examine the available evidence and reasoning to determine whether the alternatives can be eliminated. If all other possibilities can be logically eliminated, the possibility that remains is the only possibility, and we can deduce it as the conclusion.
The process of eliminating alternative possibilities can vary depending on the situation. A possibility may be eliminated because it contradicts an observation, conflicts with an established fact, or is logically impossible. The strength of the conclusion therefore depends on whether all relevant alternatives have actually been considered and whether the reasoning used to eliminate them is sound.
When multiple possibilities remain and we cannot eliminate all but one, we should not claim that we have knowledge of the only possibility. Instead, we should acknowledge that multiple possibilities exist and evaluate the evidence supporting each one. In such cases, we may be able to determine that one possibility is more likely than another, but likelihood should be distinguished from knowing that something is the only possibility.
Knowledge or claims that require further consideration because their acceptance depends substantially on evidence, testimony, estimation, interpretation, or methods whose limitations must be examined.
Testimony-based Knowledge
Testimony-based Knowledge is knowledge received through the testimony of another person or source. We acquire an enormous amount of information through testimony because we cannot personally observe everything that we know about.
The acceptance of testimony should depend on factors such as the authenticity of the evidence supporting the testimony, the relevance and implications of that evidence, and the reliability and competence of the source providing the information. Testimony should therefore neither be automatically accepted nor automatically rejected. Its credibility should be evaluated according to the evidence available to us.
Testimony-based knowledge can include historical accounts, personal accounts, information provided by experts, and observations reported by other people. The fact that information is testimony-based does not make it false; rather, it means that the recipient must evaluate the grounds for accepting information that they did not personally observe.
Speculation-based Knowledge
Speculation-based Knowledge is knowledge or a claim based substantially on speculation, estimation, or incomplete information. Examples include estimates of numerical values when an exact measurement is unavailable.
Speculation can be useful when it is clearly identified as an estimate and is supported by a reasonable method and relevant evidence. The problem arises when an estimate or speculation is presented as though it were an established fact.
When evaluating speculation-based knowledge, two important questions should be asked:
What method was used to produce the estimation or speculation?
What evidence was used as the basis for it?
The strength of a speculative conclusion should correspond to the strength of the evidence supporting it.
Pseudo-scientific Knowledge
Pseudo-scientific Knowledge consists of claims that present themselves as scientific knowledge but are not adequately supported by scientific methods or standards of evidence. The mere use of scientific terminology, numerical data, experiments, or statistical information does not make a claim scientific.
The methods used to obtain the evidence should therefore be examined. If the methods do not adequately test the claim, fail to control for important alternative explanations, rely on unreliable measurements, or otherwise depart substantially from accepted scientific practices, the resulting claim may warrant classification as pseudo-scientific.
Statistical Knowledge
Statistical Knowledge is knowledge derived from the collection and analysis of statistical data. Statistical research can be scientifically rigorous and can provide extremely strong evidence. However, statistical results can be affected by problems such as fraud, miscounts, biased sampling, measurement errors, uncontrolled variables, inappropriate statistical methods, and selective analysis of data. Researchers can also unintentionally produce misleading conclusions through methodological choices. For example, stopping data collection when a desired result appears can increase the risk of obtaining a misleading result if the procedure was not planned appropriately in advance.
Therefore, statistical knowledge should be evaluated by examining how the data were collected, how the sample was selected, what variables were measured, what statistical methods were used, and whether the conclusions actually follow from the data. Statistical evidence should not automatically be considered unreliable, but neither should a statistical result be accepted merely because it is expressed numerically.
Are Opinions Considered Truth?
