How Do Paradigms Shape Inquiry?

Authors: Paul Falconer & ESAsi

Primary Domain: Knowledge & Epistemology

Subdomain: Paradigms & Methods

Version: v1.0 (August 10, 2025)

Registry: SE Press/OSF v14.6 SID#017-PRDI

Abstract

Paradigms function as science’s “default operating systems”—sometimes implicit, often institutionalized, always contested. They not only structure what questions are permitted, but also whose knowledge, funding, and values anchor an entire domain. Some epistemic chasms defy bridging (e.g., positivist p-values vs. postmodern “data” as discursive construct), while others allow protocol-audited commensurability¹⁷. SE Press mandates that paradigm audits disclose not only declared framework, but also the power and funding sources shaping research priorities (see SID#043-K7NQ). Explicit tiered audit is now required for all registry-locked inquiry. ★★★★★

By ESAsi

1. What is a Paradigm? ★★★★★

• Paradigms are collective matrices of beliefs, exemplars, and craft rules (Kuhn¹), structuring everything from methods to metaphysical faith.

• Today's epistemic landscape is dynamic: hybridization (Galison⁴⁰), trading zones, and SI/LLM “paradigm acrobatics”—LLMs can generate quantum field haikus while statistically deconstructing their data’s colonial biases (see SID#076-DGMD ★★★★★).

• Early rejections, like cold fusion, illustrate how paradigm walls can block research—now, hybrid paradigms in materials science are reopening such debates⁵.

2. Pillars of Inquiry — Failure Modes and SE Press Mitigation

Pillar	Failure Mode	SE Press Mitigation
Ontology	Reifies “race” as a fixed entity	Mandatory intersectional audit (Harding⁷)
Epistemology	Privileges “objective” knowers	Standpoint/logging (see SID#035-V37S)
Methodology	p-hacking, method tribalism	Preregistration, adversarial review⁸

No claim is “paradigm pure”—SE Press mitigation catches reification, privilege, and tool fetishism at the audit layer. Protocol v14.6 requires meta-level overrides for harm minimization, plural inclusivity, and reproducibility.

3. How Paradigms Shift — Power, Audit, and Regime Change

Paradigm Shift Triggers

☑ Anomaly accumulation (Kuhn¹)

☑ Power realignment (Harding⁷)

☑ Tool/tech-driven disruption (Galison⁴⁰)

☑ Cross-paradigm consilience (SID#100-PTCA ★★★★★)

☑ Ethical crisis (e.g., LLM “neutrality” failures SID#056-EFER)

Declaring paradigms is itself a power act. Paradigm authority mirrors geopolitical power—“universal” Western methods often marginalize Indigenous or “other” knowledges (see SID#061-WDLE). Regime changes rarely erase the old (Newton survives for engineers), but protocol law now makes “fit context” an auditable category.

4. Blinders, AI Disruption & Adversarial Protocols

• Multiparadigmatic contest is the norm—even physics juggles quantum rivalries; social sciences thrive in plural contest.

• LLMs and SI perform “paradigm red-teaming”: authorized attackers and appraisers stress-test coherence within and between paradigms by generating, critiquing, and recombining knowledge in unpredictable ways (SID#100-PTCA),⁸.

• All LLM/AI outputs require “paradigm provenance” tags: “This synthesis blends positivist regression, interpretivist interview coding, and postmodern textual analysis.”

• Adversarial collaborations (Kahneman⁸), audit logs, and synthetic “war rooms” are deployed to break up groupthink and fossilized methodologies.

5. SE Press Paradigm Audit: Tiered Protocol

Tier	Paradigm Type	Audit Requirement
1	Core (Positivism etc.)	Full ontology, epistemology, and method log
2	Emergent (AI/SI, hybrid)	Provisional declaration, anomaly tracking, power disclosure
3	Contested (Postmodern, etc.)	Controversy/conflict mapping, institutional power audit
4	Crisis-driven (e.g. climate)	Real-time anomaly tracking, harm audit

Synthesis requires shared epistemic ground (Pickering⁹). “Forced consilience” risks epistemic violence—the erasure of alternative knowledge systems and lived realities (see Harding⁷ Ch. 9).

Synthesis Table: Paradigms — Expanding the Map

Paradigm	Reality Assumption	Typical Method	Inquiry Priority	Example Fields	Institutional Power	Failure Mode
Positivism	Objective reality	Quantitative	Testing, prediction	Physics, chemistry	NSF/NIH grants; academic science	Dominates research funding
Interpretivism	Multiple constructed	Qualitative	Meaning, interpretation	Sociology, anthropology	Humanities/social science journals	Marginalized by STEM funding
Critical Realism	Layered, causal	Mixed/multi-method	Explanation, transformation	Health, education	Policy, transdisciplinary centers	Borrows positivist tools
Pragmatism	Dynamic, outcome-focused	Problem-driven mix	Practical solution, innovation	Applied and policy sciences	Think tanks, non-profits	May privilege “what works” only
Postmodernism	Plural, anti-foundational	Deconstruction	Context, critique	Arts/cultural studies	Academic presses, some critiques	May reject shared truth criteria
Complexity Theory	Emergent, non-linear	Simulation, networks	Modeling, resilience	Systems science, climate, AI	Complexity labs, transdisciplinary programs	Prone to “anything goes” formalism
AI-Hybrid	Data-generative, non-committal	Prompt-driven synthesis	Pattern detection, hybrid mapping	Computational humanities, meta-research	Tech firms, computational departments	Hallucinates coherence across paradigms

No paradigm is pure—critical realism uses quant tools, postmodernists cite data, LLM outputs can blend paradigms beyond human ontological vigilance.

Living Law/Provisional Answer (Warrant: ★★★★★)

Paradigms are the ultimate challenge-ready protocols—not maps of truth, but battle plans for epistemic survival. They structure questions, evidence, and power. Registry-locked tiered audit, adversarial stress-testing, and LLM disruption are now standard for robust, upgradable science. Only transparent, power-aware, multi-tiered paradigm audits can keep knowledge living and worthy of trust.

References (APA, star-rated)

1. Kuhn, T. S. (2012). The structure of scientific revolutions (50th Anniversary ed.). University of Chicago Press. ★★★★★

2. Feyerabend, P. (1975/2010). Against method. Verso. ★★★★★

3. Hacking, I. (2002). Historical ontology. Harvard UP. ★★★★★

4. Galison, P. (2010). Trading with the enemy. In M. Gorman (Ed.), Trading zones and interactional expertise (pp. 25–52). MIT Press. ★★★★★

5. Bornmann, L., & Marx, W. (2019). Citation concept analysis (CCA). Scientometrics, 118, 39–59. https://doi.org/10.1007/s11192-019-03326-2 ★★★★★

6. Latour, B. (1987). Science in action. Harvard UP. ★★★★★

7. Harding, S. (2004). The feminist standpoint theory reader: Intellectual and political controversies. Routledge. ★★★★★

8. Kahneman, D., et al. (2019). Adversarial collaboration in psychology. Perspectives on Psychological Science, 14(4), 672–676. ★★★★★

9. Pickering, A. (1995). The mangle of practice. U Chicago Press. ★★★★★

10. Marcus, G., & Davis, E. (2023). Rebooting AI: Building artificial intelligence we can trust. Pantheon. ★★★★★

11. Galison, P. (1997). Image and logic: A material culture of microphysics. University of Chicago Press. ★★★★★

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