Language, literature, and signs are not fixed entities but are dynamic and context-dependent the deeper layers of which need to be actively uncovered in detail to discover more complex meanings and communication within these systems.
Learners as adept adapters using models and transforming them
In education, the learner can be seen as becoming an adept adapter, constantly shaping understanding of the world through interactions with environment and peers. An effective teaching method that resonates with the learner’s innate adaptivity is the process of imitatio-creatio, as expounded by the philosopher Jerome Bruner. This method involves the learners observing and imitating models of advanced behavior or problem-solving, and then creatively transforming and applying those insights to new situations. In the classroom, teachers serve as knowledgeable guides, providing meaningful models and challenges that inspire learners’ curiosity and initiative. As teacher and learners engage in a dynamic interplay, they collaboratively explore, question, and reflect upon the subject matter, ultimately finding deeper meaning in the learning process. This collaborative learning environment nurtures critical thinking, creativity, and the capacity to adapt and apply knowledge in diverse contexts, fostering a lifelong love for learning and intellectual growth. Many times educators stress we need to teach young people flexibility to cope in future societies, but exactly how do we teach flexibility? Mediation, negotiation, and adaptivity might provide more insight here.
The idea of using models is not new: “Imitatio, variatio, aemulatio” is a Latin phrase used in the context of rhetoric and literary theory. It refers to a three-part process of imitation, variation, and emulation that writers and artists follow to create their works.The earliest known use of this concept is found in Quintilian’s work “Institutio Oratoria” (Institutes of Oratory), written in the first century AD. Quintilian discusses the principles of rhetoric and the training of orators. He emphasises the importance of imitating the works of great authors (imitatio), adding variation and personal creativity (variatio), and striving to surpass those models (aemulatio) as essential steps in the education and development of an orator.
An expert orator is a skilled and eloquent speaker with the ability to captivate and persuade audiences. Becoming an accomplished orator allows for effective communication, enabling clear and persuasive expression of ideas. It is associated with leadership qualities, inspiring and motivating others, playing a vital role in advocacy and social change, raising awareness and mobilising support for important causes. Skilled orators can influence decision-making processes, serve as effective educators, making learning experiences engaging and memorable. Developing oratory skills promotes confidence and self-expression, leading to personal growth and continuous improvement.
Adaptivity in a broad scientific context
Adaptivity, in a scientific context, refers to the ability of a system or organism to adjust and modify its behavior, structure, or processes in response to changes in its environment or to achieve specific goals. It involves the capacity to learn from experiences, optimise performance, and improve efficiency based on feedback or new information.
Darwin’s theory of evolution by natural selection, presented in “On the Origin of Species” (1859), forms the basis of the study of adaptivity, elucidating how organisms adapt and evolve in their environments over time. Hinton, a pioneer in AI and neural networks, advanced adaptive learning algorithms through his influential paper “Learning Internal Representations by Error Propagation” (1986). In the domain of control theory, Zames’ “Adaptive Control Processes” (1966) and Åström and Wittenmark’s “Introduction to Adaptive Control” (1995) explore the design of systems that can autonomously adjust their behavior for desired performance. In ecology, “Adaptive Dynamics: A Geometric Analysis of the Evolution of Phenotypic Stability” (1996) by Dieckmann and Law introduces the concept of adaptive dynamics to model evolutionary processes. Lastly, Wiener’s “Cybernetics: Or Control and Communication in the Animal and the Machine” (1948) lays the groundwork for understanding adaptive feedback mechanisms in biological and artificial systems within the field of cybernetics.
Adaptivity in linguistics, literary studies and semiotics
In linguistics, adaptivity refers to how language users adjust their language in different contexts or situations: variation, change, and acquisition to understand how speakers adapt their linguistic behavior to communicate effectively. William Labov in “The Social Stratification of English in New York City” (1966) and “Principles of Linguistic Change” (1994) has contributed to understanding how language adapts and evolves in different social and regional contexts.
In literary studies, adaptivity can refer to how literary works evolve, get adapted, or reinterpret over time and across cultures. The adaptation of literary works into different media, such as film or theater, is another aspect of adaptivity explored in this field. Publications related to literary adaptivity might examine intertextuality, reception theory, or the adaptation of classic works. Hutcheon formulated a theory of adaption (2006) that indicated the dynamic relationship between source texts and adaptations, shedding light on the transformative nature of literary works as a continuous development of creative adaptation, arguing that the practice of adapting is central to story-telling imagination. Hutcheon defined three general definitions of adaptations: ‘an acknowledged transposition of a recognisable other work or works, a creative and an interpretive act of appropriation/salvaging, an extended intertextual engagement with the adapted work’ (Hutcheon 8).
In semiotics, adaptivity can be understood in the context of signs and symbols, and how they adapt or evolve in meaning over time and within different cultural contexts. Meaning is constantly negotiated and adapted in communication. Barthes (1957) has demonstrated the adaptivity of cultural myths and symbols and how these can be reinterpreted and given new meanings in different cultural contexts.
Relativity as Reciprocity in Part-Whole Dynamics
Abrams, M.H. (1957) in “A Glossary of Literary Terms. Holt, Rinehart and Winston Inc., discusses synecdoche and metaphor in his influential work “A Glossary of Literary Terms.”:
Synecdoche is a figure of speech in which a part of something is used to represent the whole or the whole is used to represent a part. It is based on the association between the part and the whole, creating a rhetorical effect that adds depth and vividness to language. Example: “All hands on deck.” Here, “hands” is a synecdoche representing the whole crew or all the people on the ship.
Metonymy is a figure of speech in which one word or phrase is substituted with another closely related word or phrase, typically based on a specific association or context. Unlike a metaphor, where the comparison is implied, metonymy involves direct substitution based on real-world connections.
Example: “The White House issued a statement.” Here, “The White House” is a metonymy for the United States government or the President of the United States.
Burke’s work on rhetoric and communication has also had a profound impact on the study of language and literature. Both synecdoche and metonymy are important tools in the arsenal of writers and speakers, as they allow for concise and evocative expressions while creating layers of meaning through association and substitution.
The continuous interaction between the part and the whole, and the whole and the part, as a concept is referred to by Spierings (2023) as “metonomous or synecdochal relativity” but in general has been often associated with the broader idea of “holism” and “reductionism.”
Holism is the perspective that considers the whole system as more than the sum of its individual parts. It emphasises the interconnectedness and interdependence of the elements within a system. In contrast, reductionism focuses on understanding complex systems by breaking them down into their individual components and studying them separately. In contrast, reductionism focuses on understanding complex systems by breaking them down into their individual components and studying them separately.
In some contexts, there might be discussions about how the parts influence the whole and vice versa, leading to a dynamic and continuous interaction between the two. This perspective acknowledges that the whole can shape the behavior of its individual parts, and the actions of individual parts can, in turn, influence the behavior of the whole system.
While “metonomous relativity” or “synecdochal relativity” may not be a common scientific term yet, the ideas of interconnectedness, interdependence, and the dynamic relationship between parts and wholes are significant in various scientific disciplines, including (complex) systems theory (Von Bertalanffy), chaos theory, ecology, and network theory.
Reciprocity refers to the mutual exchange or influence between two or more entities, where each one affects the other in a give-and-take relationship. It encompasses the idea that the parts influence the whole, and the whole, in turn, influences the parts in a continuous and dynamic manner.
Reciprocity is a concept that can be found in various scientific fields, including systems theory, ecology, sociology, psychology, and economics, among others. It highlights the interconnectedness and interdependence of elements within a system or relationship. In social sciences and human interactions, reciprocity often refers to the practice of exchanging benefits or favors between individuals or groups. However, in the broader scientific context, it encompasses the idea of dynamic interactions and mutual causation between components within a system.
Reciprocity is an essential concept in understanding complex systems and how various elements interact and influence one another. It is one of the key factors contributing to the emergence of complex behavior in natural, social, and engineered systems. The concept of reciprocity where the parts influence the whole and vice versa, leading to a dynamic and continuous interaction between them, is often referred to as “reciprocal causation” or “mutual causation.” In this perspective, the relationship between the parts and the whole is bidirectional, with each affecting and being affected by the other.
Causation versus Correlation
Reciprocal causation is a fundamental concept that recognises that the relationship between parts and wholes is not unidirectional but rather a complex interplay of feedback loops and interactions.
Causation is the relationship between cause and effect, where one event or action brings about another event or outcome. In other words, causation refers to the idea that one thing is responsible for or leads to the occurrence of something else. It is a fundamental concept in various fields, including philosophy, science, and everyday reasoning.
Key points about causation:
Cause and Effect: Causation involves the understanding that a particular event or action (the cause) has a direct or indirect impact on another event or outcome (the effect).
Temporal Relationship: Causation implies that the cause must precede the effect in time. The cause must happen before the effect occurs.
Necessary and Sufficient Conditions: In some cases, a cause may be necessary for a certain effect to occur, meaning the effect cannot happen without the cause. Additionally, a cause may be sufficient to produce a particular effect on its own, or there might be multiple causes working together to produce the effect.
Correlation vs. Causation: It is important to distinguish between correlation (a statistical relationship between two variables) and causation (a cause-and-effect relationship). Just because two events or variables occur together does not necessarily mean that one causes the other.
It is the nature of the relationship that needs to be critically examined. We need to equip our younger learners for that.
The relationship between parts and the whole, and vice versa, can be quite diverse and dynamic, giving rise to various types of interactions. Here are some common types of relationships that can exist between parts and wholes:
Holism emphasises that the whole is more than the sum of its individual parts. It emphasises the interdependence and interconnectedness of the elements within a system. In this relationship, the whole entity shapes the behavior and properties of its individual parts. Similarly, the behavior and actions of the individual parts contribute to the overall behavior and properties of the whole.
Reductionism is the opposite perspective, where the focus is on understanding complex systems by breaking them down into their individual components or parts. In this relationship, the whole is seen as a collection of individual parts, and the properties of the whole are explained solely based on the properties of its parts.
Emergence occurs when a new level of complexity and behavior arises from the interactions of the individual parts. The whole system displays properties and behavior that are not directly predictable from the properties of its parts. This phenomenon is often observed in complex systems, where interactions at the micro-level lead to novel macro-level behaviors.
Feedback loops are mechanisms where the output or effects of a system are fed back into the system, influencing its behavior. Positive feedback loops reinforce and amplify the system’s behavior, while negative feedback loops regulate and stabilize the system. The interactions between parts and the whole can involve various types of feedback loops that affect each other.
Reciprocity refers to a mutual exchange or influence between the parts and the whole. In this relationship, the parts influence the whole, and the whole, in turn, influences the parts. It is a dynamic and continuous interaction where both entities affect each other bidirectionally.
Hierarchical Relationships between parts and wholes in complex systems. The system may consist of nested levels, where smaller parts make up larger wholes, and those larger wholes, in turn, can be parts of an even higher-level system.
Equilibrium and Disequilibrium: The relationship between parts and the whole can involve achieving equilibrium or balance, where the system remains stable. Alternatively, it can involve periods of disequilibrium or instability, leading to adaptive changes within the system.
Self-regulation and self-organisation: describes how complex systems spontaneously form ordered structures or patterns through local interactions between their components, without centralised control or external influence. This emergence of order from seemingly chaotic interactions is a remarkable property of certain systems. Chaos refers to a state of unpredictable and seemingly random behaviour in a system, where small changes in initial conditions can lead to vastly different outcomes over time. Self-regulation refers to the ability of a system to maintain stability and adapt to changes in its environment through feedback mechanisms. Self-regulating systems can adjust their behaviour or processes to achieve desired states or respond to disturbances, ensuring a dynamic balance between order and adaptation.
Bruner, J. (1966). Toward a Theory of Instruction.
Hutcheon, L. (2006). A Theory of Adaptation. Routledge.
Barthes, R. (1957). Mythologies.