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. 2025 Jan 23;15:1421525. doi: 10.3389/fpsyg.2024.1421525

Table 2.

Most common quantitative-based research philosophies: assumptions and stances and the likelihood of embracing the quantitizing process.

Research philosophy Ontology Epistemology Axiology Methodology Likelihood of quantitizing Rationale
Platonism (Mathematical Realism; Balaguer, 1998; Tomšič, 2017) Abstract mathematical entities exist independently of human thought; timeless, non-physical objects. Knowledge is attained through intellectual intuition and logical reasoning. Values the discovery of absolute and universal truths. Deductive reasoning and discovery of eternal truths. High Quantitizing complements the search for universal mathematical truths.
Nominalism (Mathematical Constructivism; Kerkhove and Van Bendegem, 2012; Szabo, 2003) Denies the independent existence of mathematical entities; sees them as constructs or labels. Knowledge is a human construct, dependent on social practices and language. Values practical utility and coherence. Constructive mathematics and verification through consistency within mathematical systems. Low Prioritizes human-centric constructs over objective quantification.
Structuralism (Sturrock, 2008) Emphasizes the structures or relationships among mathematical entities, rather than the entities themselves. Knowledge arises from understanding these structures. Values insight into the structural aspects of mathematics. Analysis of relationships and patterns within mathematical systems. Moderate Useful for illuminating structural relationships.
Intuitionism (Dummett, 2000) Mathematics is a mental construct, not reflecting any external reality. Knowledge is subjective, accessed through mental processes and intuition. Values the certainty and constructiveness of mathematical proofs. Constructive proofs, emphasizing processes that can be intellectually grasped. Low Due to the focus on mental constructions rather than empirical data.
Formalism (Detlefsen, 2007) Mathematics is about manipulating symbols according to agreed rules; the symbols don't necessarily represent real objects. Knowledge is based on mastering these formal systems and operations. Values logical consistency and rigor in formal systems. Development and exploration of formal systems, independent of their interpretation. High Aligns well with the manipulation of formal systems and precise measurements.
Logicism (Demopoulos, 2013) Mathematics can be reduced to logical foundations. Mathematical truths are derived from logical truths. Values the clarity and undeniable truth provided by logic. Reducing mathematics to logic to prove mathematical truths. High Quantitizing supports the objective and universal nature of logical structures.
Empiricism (Meyers, 2006) Mathematical knowledge is derived from experience and is empirical. Knowledge is provisional and empirically tested. Values empirical verification and practical applications. Empirical observation and experimentation. High Crucial for linking mathematics to empirical observations.
Finitism (Ye, 2011) Only finite mathematical constructs exist; rejects the existence of actual infinity. Knowledge is about finite procedures and their results. Values computability and concrete results. Restricts mathematical practice to finite operations. Moderate If the focus remains on finite and tangible outcomes.
Realism (House, 1991) Mathematical entities exist independently of human knowledge or perception. Knowledge of these entities is discovered, not invented. Values the discovery of objective, independent truths. Objective investigation and logical analysis. High It aids in the objective analysis and understanding of mathematical entities.
Anti-Realism (Brock and Mares, 2006; Chalmers, 2009) Denies the objective existence of mathematical entities outside of human conceptual schemes. Mathematical truths are dependent on human practices or conceptual frameworks. Values the practical and explanatory power of mathematics. Focuses on the usefulness and practical application of mathematical concepts. Low to moderate Depending more on its practical utility than on seeking objective truths.
Fictionalism (Fine, 1993; Suárez, 2008) Mathematical entities are akin to fictional characters; they do not exist. Mathematical truths are “pretended” for their utility in explaining and predicting phenomena. Values the usefulness and explanatory power of mathematical constructs. Utilitarian use of mathematics as a tool for explanation and prediction. Moderate Appreciated for its practical benefits rather than its truth.
Psychologism (Crane, 2014) Mathematics is a product of human thought and psychological processes. Mathematical knowledge is derived from and limited by human cognitive capacities. Values the understanding of human cognitive processes in mathematics. Psychological investigation into how mathematical thoughts and processes develop. Low Focuses more on qualitative insights into human cognition.
Objectivism (Peikoff, 1993) Reality exists independently of consciousness; specific principles govern reality, including mathematical ones. Knowledge is based on objective observation and rational integration. Rational inquiry and empirical evidence. Rational inquiry and empirical evidence. High It aligns with the pursuit of objective knowledge through rational and empirical means.
Postpositivism (Phillips and Burbules, 2000; Popper, 2002) Acknowledges that scientific knowledge is imperfect and theory-laden. Knowledge is provisional and subject to revision; emphasizes critical testing of theories. Values rigorous testing, critical thinking, and acknowledges the fallibility of scientific inquiry. Scientific methods with a recognition of their limitations; uses qualitative and quantitative research. High But with a critical stance, recognizing the limits and potential biases of quantitative methods.

Adapted from “Philosophical assumptions and stances of the most common mixed methods research-based research philosophies,” by Onwuegbuzie, 2024. Dialectical Publishing, p. 13. Copyright 2024 by Dialectical Publishing.