Definitions by Abzugal Nammugal Enkigal
Dynamic-Complex Science Theory
A meta‑scientific framework that integrates insights from dynamic systems theory (process, time, flux) and complexity science (emergence, non‑linearity, networks) to understand science itself as a dynamic, complex system. It studies how scientific knowledge evolves through feedback loops, tipping points, and path dependence. It rejects static, equilibrium models of science (e.g., Popperian falsification as a simple logical step). Instead, it models scientific change as a complex adaptive process, with paradigm shifts as phase transitions. It also applies to the methodology of science: research should embrace dynamic, adaptive approaches rather than rigid protocols.
Dynamic-Complex Science Theory Example: “Dynamic‑complex science theory models the replication crisis not as a failure of individual scientists but as a complex system pathology: publication bias created positive feedback loops, amplifying false positives until a tipping point (the crisis) was reached. Reform requires changing the system’s dynamics.”
Dynamic-Complex Science Theory by Abzugal Nammugal Enkigal June 1, 2026
Paraconsistent Science Theory
A meta‑scientific framework that allows scientific theories to contain genuine contradictions without invalidating the entire enterprise. It draws on paraconsistent logic, which tolerates contradictions by rejecting the principle of explosion (from a contradiction, anything follows). Paraconsistent Science Theory is useful for domains where contradictions are empirically unavoidable: quantum mechanics (wave‑particle duality), dialectical materialism (contradiction as driver of change), and certain ecological or social systems. It argues that demanding total consistency can be a scientific handicap; sometimes we must learn to manage contradictions, not eliminate them.
Paraconsistent Science Theory Example: “Paraconsistent science theory explains why quantum mechanics can treat the electron as both wave and particle—a contradiction in classical logic—without the theory collapsing. Physicists have learned to work with a paraconsistent ontology.”
Paraconsistent Science Theory by Abzugal Nammugal Enkigal June 1, 2026
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 Science Theory by Abzugal Nammugal Enkigal June 1, 2026
Epistemology of Complexity
A branch of epistemology that studies how we can know, understand, and justify claims about complex systems—systems with many interacting parts, non‑linear dynamics, emergence, and path dependence (ecosystems, economies, brains, climate). It challenges traditional epistemology, which often assumes simplicity, linearity, and reproducibility. It asks: what counts as evidence in a complex system? How can we predict when small changes cause large effects? How do we handle irreducible uncertainty? It draws on complexity science, systems thinking, and post‑normal science. It advocates for new epistemic virtues: humility, pluralism, and adaptive management.
Epistemology of Complexity Example: “The epistemology of complexity explains why climate models produce probabilistic projections, not certain forecasts: complex systems are sensitive to initial conditions, and long‑term predictions are inherently uncertain. Knowing that uncertainty is itself a form of knowledge.”
Epistemology of Complexity by Abzugal Nammugal Enkigal June 1, 2026
Ethnography of Scientific Evidence
A qualitative research method that immerses the ethnographer in a scientific setting to observe how evidence is literally produced, handled, and mobilized. Ethnographers watch lab technicians run experiments, note how data are cleaned, how outliers are discarded, and how uncertainty is communicated. They interview scientists about their “gut feelings” regarding evidence. This approach reveals that evidence is not a static object but a dynamic process—something scientists do, not just something they have. It captures the tacit, embodied, and social dimensions that formal accounts miss.
Ethnography of Scientific Evidence Example: “The ethnography of a clinical trial lab showed that ‘clean’ data were often the result of a postdoc’s judgment calls about which subjects to exclude. Those judgments became invisible in the final paper, but they shaped the evidence.”
Ethnography of Scientific Evidence by Abzugal Nammugal Enkigal June 1, 2026
Philosophy of Scientific Evidence
A branch of epistemology that investigates the nature, justification, and limits of evidence in science. It asks: what is the relationship between evidence and hypothesis? What makes something evidence? Can evidence be theory‑laden, and if so, does that undermine objectivity? It explores concepts like confirmation, induction, Bayesian updating, and the problem of underdetermination. It also examines the ethics of evidence (e.g., what evidence must researchers disclose?). Unlike sociology (descriptive), philosophy of scientific evidence is normative: it evaluates what good evidence should be and how it should be used.
Philosophy of Scientific Evidence Example: “The philosophy of scientific evidence debates whether a single randomized controlled trial counts as ‘evidence’ for a policy, or whether we need a systematic review. The answer affects whether we trust new drugs—or wait decades.”
Philosophy of Scientific Evidence by Abzugal Nammugal Enkigal June 1, 2026
Sociology of Scientific Evidence
A subfield of science studies that examines how evidence is produced, selected, interpreted, and validated within scientific communities—not as abstract logical entities, but as social achievements. It asks: what counts as evidence for a given community? How do instruments, trust, and reputation shape what is accepted? Why do some studies become “landmark evidence” while others with similar findings are ignored? It studies the social construction of evidence, showing that facts are not simply “out there” but are made through negotiation, inscription, and credibility. Unlike philosophy (which asks what evidence should be), sociology of scientific evidence investigates what evidence actually does in practice.
Sociology of Scientific Evidence Example: “The sociology of scientific evidence revealed that fMRI images became persuasive not because they were more accurate, but because they looked like photographs—visual rhetoric shaped what counted as ‘proof’ of brain activity.”
Sociology of Scientific Evidence by Abzugal Nammugal Enkigal June 1, 2026