The Unified Theory of Emotions (UNITE): A Universal, Non-circular, Quantitative, and Predictive Framework for All Human Emotions

This record contains the foundational research paper introducing The Unified Theory of Emotions (UNITE), a universal, non-circular, quantitative, and predictive framework intended to explain, classify, and mathematically model all human emotions within a single coherent system.UNITE addresses a longstanding limitation in affective science, psychology, philosophy of emotion, and computational emotion research: most existing theories either explain only a subset of emotions, rely on circular labeling, remain descriptive rather than predictive, or fail to provide a mathematically operational structure that can be applied consistently across domains. In contrast, UNITE proposes that emotions are not primitive or irreducible states, but measurable relational outputs generated from three underlying non-emotional variables: Effort (E), Gratitude or Blame (G/B), and Proximity (P).The core mathematical formulation of the framework is:ES = E × (G/B) × Pwhere the resultant Emotional Score (ES) predicts both the direction and the intensity of Subject 1’s emotion toward Subject 2. In this framework:Effort (E) captures the extent of real, expected, committed, threatened, feared, or otherwise consequential investment associated with Subject 2.Gratitude or Blame (G/B) captures whether Subject 1 credits Subject 2 positively or negatively in relation to the perpetuation-relevant outcome.Proximity (P) refers strictly to physical closeness or distance, including physically desired, feared, threatened, committed, or mentally experienced physical closeness in cases where Subject 2 is experienced as non-localized, symbolic, spiritual, or otherwise not directly tangible.UNITE argues that all emotions, whether commonly labeled as love, hate, grief, pride, jealousy, devotion, resentment, awe, loyalty, disgust, admiration, or ambivalence, can be understood as lawful expressions of the same deeper relational structure. Rather than treating emotions as disconnected categories, the framework places them on a continuous and computable emotional spectrum generated by measurable combinations of E, G/B, and P. This allows UNITE to explain not only emotional labels, but also why emotional intensity varies, why apparently contradictory emotions coexist, why mislabeling is common, and why the same outward behavior may correspond to different underlying emotional states depending on the hidden structure of effort, blame or gratitude, and proximity.The paper develops the theory conceptually, mathematically, and cross-domain. It demonstrates that the same formulaic structure applies not only to person-to-person relationships, but also to human responses toward animals, objects, institutions, brands, nations, ideologies, deities, memories, imagined entities, and artificial intelligence systems. This cross-domain applicability is one of the central claims of the paper and one of the reasons the framework is positioned as universal rather than domain-specific.A key contribution of UNITE is that it is non-circular. It does not define an emotion by naming the emotion. Instead, it derives emotional outcome from prior non-emotional variables. This makes the framework potentially falsifiable, externally testable, and suitable for computational implementation. The paper also emphasizes that common human emotional labels are often imprecise or misleading, and that the mathematical structure can reveal when ordinary language has mislabeled the actual relational state.The paper includes and/or directly references multiple validation layers associated with the disclosed framework:a cross-domain independently verifiable appendix applying the framework to 70 behaviorally decomposed archetypal cases, where the scoring process is made inspectable and the predicted emotional direction and intensity are shown against observed or historically recognizable emotional patterns;a separately deposited 300-case external validation workbook built from bespoke human-readable scenarios, designed so that an independent evaluator can assign emotional labels first and only then compare them against the pre-filled UNITE formula-derived outputs;a separately deposited fully reproducible 1,000,000-case computational validation dataset and simulation, with complete code and verification materials, in which the UNITE formula correctly predicted both the emotional direction and the quantitative emotional intensity in 100% of cases within the disclosed computational setup.Together, these resources are intended to show that UNITE is not merely a philosophical proposal, but a mathematically operational framework with immediate relevance for:affective sciencerelationship psychologybehavioral predictionpsychiatry and mental health interpretationconflict and negotiation analysisorganizational and consumer behaviorsocial and political behavior modelingreligion and devotion studieshuman-AI interactionemotionally conscious artificial intelligenceThis record contains the core UNITE paper itself. Supporting validation deposits are linked separately for transparency, reproducibility, and independent inspection.