Vol. 1, No. 1 (2026) — R.U.B.B.I.S.H. Journal Inaugural Editorial and Featured Papers
Issue overview
This issue marks the inaugural publication of R.U.B.B.I.S.H. Journal, featuring four interdisciplinary research articles spanning cognitive science, artificial intelligence, legal theory, and philosophy of technology. Drawing on everyday experiences, internet culture, and real-world institutions, the authors investigate seemingly trivial yet widely shared social and behavioral phenomena through probabilistic models, machine learning techniques, and legal analytical frameworks. Together, these studies reveal a common theme: within complex social systems, individual behavior, technological tools, and institutional rules continuously interact, producing a reality that is simultaneously rational and absurd. From dream probability and animal behavior modeling to secondhand smoke liability and Transformer insurance systems, the articles uncover the hidden structural logic embedded in everyday life.
Editorial note
Within traditional academic systems, many research topics are often considered “too mundane” or lacking in seriousness, making them difficult to publish through conventional channels. Yet it is precisely these seemingly trivial phenomena—such as the probability of appearing in dreams, defensive behavior in animals, disputes over secondhand smoke in shared spaces, or even the insurance classification of fictional mechanical lifeforms—that constitute an important part of our social experience.
R.U.B.B.I.S.H. Journal seeks to provide an open space for discussing topics that lie between rigorous scholarship and the humor of real life. We encourage authors to observe reality through interdisciplinary methods and to systematically explore complex everyday phenomena using theoretical models, data analysis, legal reasoning, or thought experiments.
The journal does not aim to challenge traditional academic standards themselves, but rather to expand the boundaries of research questions. If all social phenomena are worthy of understanding, then those that appear absurd, marginal, or overlooked are equally worthy of study.
This inaugural issue includes four articles that examine patterns of behavior and institutional logic embedded in everyday experience from the perspectives of cognitive science, artificial intelligence, legal theory, and philosophy of technology. They represent both serious intellectual inquiry and an experiment in the forms of academic expression.
Inaugural Editorial
The name R.U.B.B.I.S.H. Journal derives from a slightly humorous acronym:
Research – Universe – Biology – Business – Information – Society – Humanities
The name is both playful and reflective. It serves as a reminder that within systems of knowledge, there are no truly “trivial” questions. Phenomena that appear insignificant often conceal complex social structures and cognitive mechanisms.
The journal is founded upon a simple idea:
If a research subject originates from the real world, then no matter how ordinary or absurd it may appear, it can become an entry point for understanding society and human behavior.
For this reason, the journal welcomes research that includes:
- Systematic observation of everyday phenomena
- Experimental applications of interdisciplinary approaches
- Studies combining data, theory, and thought experiments
- Unconventional perspectives on social, technological, and cultural issues
We believe that scholarship is not only about rigorous analysis, but also about exploration. In this sense, humor, imagination, and critical thinking are equally important components of knowledge production.
R.U.B.B.I.S.H. Journal hopes to become an open experimental platform where researchers from diverse backgrounds can share their observations and reflections on the world.
Featured papers
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The Probability of Appearing in Someone’s Dream: A Bayesian Perspective on Dream Generation and Emotional Mechanisms
This study applies a Bayesian inference framework to explain the probabilistic structure underlying the appearance of individuals in dreams. Dreams are conceptualized as a probability-generating system continuously updated by memory weights and emotional intensity. The authors argue that dreams are not merely random noise, but may instead represent a byproduct of the cognitive system’s implicit inference about social relationships and emotional states. The study provides a mathematically structured pathway for understanding the relationship between dreams and emotional cognition.
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Modeling and Analysis of Hakimi Hiss Behavior Based on Machine Learning
Combining ethology with machine learning methods, this study develops a systematic model for the characteristic defensive behavior of felines known as hissing. Using the Hakimi Hiss Dataset (HHD), acoustic features are extracted and classified through models including Support Vector Machines and neural networks. The research demonstrates the potential of artificial intelligence in recognizing animal behavior and offers a data-driven perspective for understanding defensive responses in animals.
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'I’m Not Smoking — I’m Exercising Your Rights': Legal Interpretation Challenges of Secondhand Smoke Intrusion in Property Law and the Operational Path of Injunctions in Tort Law
When secondhand smoke crosses the boundary of private space, should it be legally classified as an intrusion of 'property' or as an impact caused by 'behavior'? From the intersecting perspectives of property law and tort liability law, this paper analyzes the structural difficulties in interpreting secondhand smoke intrusion within existing legal frameworks. It proposes a more operational governance pathway through the tort law mechanism of injunctions to cease harm. The study highlights the boundary problems traditional legal concepts face when addressing everyday conflicts.
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Should Optimus Prime Be Covered by Vehicle Damage Insurance or Personal Accident Insurance?
If a vehicle simultaneously possesses mechanical structure and autonomous consciousness, how should traditional insurance systems define its legal identity? Using the fictional Transformer character Optimus Prime as a hypothetical case, this article examines the attribution of insurance liability when the subject transitions between vehicle form and mechanical lifeform. By comparing the institutional logic of vehicle damage insurance and personal accident insurance, the paper reveals fundamental assumptions within modern insurance systems regarding subject classification and risk categorization.