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Fuzzy Science Theory

A meta‑scientific framework that applies fuzzy logic to the evaluation and practice of science itself. It rejects sharp dichotomies (scientific/unscientific, proven/unproven, objective/subjective) in favor of degrees: a theory can be “highly scientific” or “somewhat supported” rather than simply true or false. Fuzzy science theory accounts for the gradations of evidence, the vagueness of scientific concepts, and the continuous spectrum between rigorous science and pseudoscience. It is used in science communication, research evaluation, and philosophy of science to move beyond binary thinking.
Example: “Fuzzy science theory allowed her to rate the homeopathy claim as ‘0.2 scientific’—not fully pseudoscience, not fully valid, but somewhere in the gray zone.”
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Fuzzy Science Theory

Application of fuzzy logic (truth degrees between 0 and 1) to the philosophy and practice of science. It proposes that scientific statements are not true or false in a binary way, but belong to blurred categories. Hypotheses have degrees of confirmation, theories have degrees of acceptance, and demarcation itself is fuzzy. It offers an alternative to the excessive rigor of neopositivism and the rigidity of Popper's criterion.
Fuzzy Science Theory Example: "In Fuzzy Science Theory, saying 'general relativity is true' means a truth degree close to 0.99 – yet there are small observational anomalies preventing absolute 1."

Paraconsistent Science Theory

feminine noun An approach that allows dealing with contradictions in science without logical collapse (the principle of explosion). In scientific practice, contradictory theories often coexist for long periods (e.g., relativity and quantum mechanics). Paraconsistent logic formalizes this tolerance. Paraconsistent Science Theory holds that contradictions can be productive and do not necessarily mean falsehood.

Example: "In Paraconsistent Science Theory, wave-particle duality is not a logical error – it is a well-behaved contradiction that lives within quantum mechanics without exploding the theoretical edifice."

Fuzzy Science Theory

A meta‑scientific framework that applies fuzzy logic (degrees of truth, continuous membership) to the practice of science itself. It argues that many scientific concepts—species, health, risk, significance—are not binary but graded. Therefore, science should abandon crisp “true/false,” “significant/not significant,” “science/pseudoscience” dichotomies in favor of fuzzy categories. Fuzzy Science Theory replaces null‑hypothesis significance testing (NHST) with fuzzy measures of evidence; it replaces sharp demarcation with degrees of scientificity. It is controversial in mainstream statistics but influential in risk assessment, environmental science, and AI. It offers a more nuanced image of scientific reasoning.
Fuzzy Science Theory Example: “Fuzzy science theory rates the evidence for homeopathy as 0.2 (not zero, because some RCTs show small effects), the evidence for acupuncture as 0.6, and the evidence for paracetamol as 0.95. Demarcation becomes a spectrum, not a binary line.”

Fuzzy Demarcation Theory of Science

A model of demarcation—distinguishing science from non‑science—that rejects binary boundaries (science/pseudoscience) in favor of graded membership. Instead of sharp dividing lines, fuzzy demarcation treats “scientificness” as a matter of degree, based on multiple criteria (testability, empirical support, coherence, etc.). A field can be more or less scientific depending on context, and boundaries are gradual. This avoids the problem of essentialism, where a single feature (like falsifiability) excludes legitimate but messy disciplines such as historical geology or early epidemiology. Fuzzy demarcation acknowledges that science is a cluster concept, not a checklist.
Example: “The fuzzy demarcation theory of science allowed her to place astrology low on the spectrum—not absolutely ‘non‑science,’ but very far from physics, while recognizing that some ‘fringe’ areas might inch closer with better methodology.”
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