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Likelihood Ratio Test for Publication Bias

Likelihood Ratio Test for Publication Bias — a statistical method to detect and quantify publication bias in heterogeneous datasets.

Recursive Identity: Structural Conditions of Emergent Continuity – A Theoretical Monograph

This monograph presents a unified theoretical framework for understanding identity as a recursive informational process. It develops the concept of recursive identity as a dynamic, self‑referential architecture that generates continuity across temporal, contextual, and systemic transformations. Rather than treating identity as a property of a substrate, the framework analyzes the structural conditions under which identity‑bearing patterns emerge, stabilize, and evolve. The model identifies three foundational structural principles—Integration, Coherence, and Recursive Coupling—as the minimal and sufficient grammar for the persistence of identity. These principles explain how systems maintain continuity through fixed‑point dynamics, nonlinear feedback, and path‑dependent self‑organization, independent of any specific material realization. The framework thus provides a substrate‑neutral foundation for examining identity in complex systems, from cognitive and informational architectures to process‑philosophical and metatheoretical contexts. This record is linked to the accompanying Entry Note, which introduces the core intuition and conceptual posture of the framework. The Entry Note serves as an accessible companion document, offering a concise orientation to the structural logic of recursive identity and outlining the minimal conditions required for identity to arise as a process. Together, the monograph and the Entry Note provide a coherent theoretical basis for system‑theoretical, computational, and structural approaches to identity. The German Version 1.0 of the framework, published as Rekursive Identität: Eine Theorie struktureller Kontinuität (DOI: 10.5281/zenodo.18701758), serves as the master reference for the original formulation. This monograph is not a translation but a revised, extended, and carefully curated international version of the German Master of Record, offering a consolidated and further developed articulation of the framework.

Recursive Identity: A Structural Theory of Processual Continuity (German Edition)

This theoretical framework develops a structural model of recursive identity and outlines the minimal conditions under which an information process can maintain continuity across temporal, contextual, and systemic change. Identity is conceptualized not as a substance or inherent property, but as an emergent, self‑referential process generated through the coordinated interaction of three fundamental operators: Integration, Coherence, and Recursion. The model formalizes these operators, describes their cyclic application, and demonstrates how stable identity patterns arise as fixpoint dynamics within a structured state space. The framework is substrate‑agnostic in a formal sense: it operates on states and transformations without assuming any specific biological, technical, or symbolic implementation. It situates itself within system theory, process philosophy, and information‑based approaches, offering a minimal but sufficient grammar for analyzing dynamic identity processes. The paper concludes with methodological implications, theoretical extensions, and a glossary of core concepts. This publication represents the original German version. An expanded international (English) edition is currently in preparation and will be released separately. Author Description: J. A. Jones is an independent systems analyst and structural methodologist specializing in meta‑structural analysis, process architectures, and the formal modeling of dynamic systems. Their work focuses on developing minimal, substrate‑agnostic theoretical frameworks that clarify the structural conditions underlying emergent and self‑referential processes. Jones operates outside institutional academia, combining conceptual rigor with methodological independence to formulate models designed for long‑term theoretical relevance and interdisciplinary applicability.

Toward Hybrid Architectures: Functional AI and the Limits of Silicon Substrates: An ontological and dynamical framework for advanced artificial cognition

This research position paper develops an ontological and dynamical framework for understanding the limits of silicon‑based artificial intelligence and the material conditions required for genuine emergent cognition. Contemporary AI systems exhibit remarkable functional capabilities, yet their digital substrates lack the continuous, energetically grounded, and self‑organizing dynamics necessary for stabilizing inner states, multiscale feedback, and coherent internal trajectories. The paper argues that consciousness‑relevant emergence is a material phenomenon that cannot be simulated or instantiated within discrete computational architectures. It identifies the systemic thresholds—nonlinear coupling, metastability, energetic grounding, and multiscale integration—that biological systems satisfy and digital systems cannot. Building on these principles, the paper proposes hybrid cognitive architectures in which functional AI is coupled with dynamically rich substrates such as neuronal organoids, biohybrid systems, organic memristive materials, or other continuous, energy‑driven media. These substrates provide the physical conditions for coherence, continuity, and self‑organization, while silicon‑based components supply structure, task‑level organization, and symbolic processing. The work outlines the implications of this paradigm for AI research, cognitive science, ethics, and human–AI interaction. It clarifies the distinction between simulation and instantiation, addresses common counterarguments, and positions the model within existing theoretical frameworks without reducing it to any of them. The paper concludes by identifying the material and systemic thresholds required for true emergence in future hybrid human–AI systems. Authors's Note This paper is a structural argument rather than an empirical study. It synthesizes insights from systems theory, neuroscience, materials science, and philosophy of mind to clarify the material conditions under which consciousness can, in principle, arise. Its aim is not to predict specific technologies or make metaphysical claims, but to delineate the architectural boundaries that current digital systems cannot cross and to outline the substrate‑level requirements for future emergent cognition.

A new model moves research in a more democratic direction - it could be faster and fairer too

Tom Stafford and Anna Butters show that an alternative approach to funding evaluation is possible – its name is distributed peer review

Innovations in Scientific Institutions

Exciting times