Multi-level modeling provides established mechanisms for describing how fields characterize elements across multiple abstraction steps. Potency-based approaches are especially useful when the intended depth of characterization is known and can be expressed directly in the modeling language. This paper presents a different solution, referred to as Modeled Field Semantics (MFS). Instead of defining field behavior only as a built-in language mechanism, MFS represents certain aspects of field behavior explicitly in the model. The motivation for MFS comes from cases where field behavior is not limited to assigning a value at a predetermined abstraction depth. A value may be interpreted differently by classifier-objects and instance-objects, and the differences may also become part of the field structure itself, for example when a general field later continues as several distinct fields representing different roles. In MFS, such decisions are not treated only as consequences of predefined field semantics, but can be expressed in the model through explicit field relationships, assignment rules, and value access operations. MFS treats selected aspects of field behavior as part of the modeled semantics. Field lineage, value-assignment rules, getter and setter behavior, and their configuration can be represented explicitly instead of being fully pre-encoded as one fixed language semantics. The result is a way to describe field semantics in which structural behavior and value interpretation remain explicit, adjustable, and subject to validation within the model.