Label-Free Distinctiveness: Building a Continuous Trademark Scale via Synthetic Anchors (2025)

Abstract: Trademark law protects distinctive marks that are able to identify and distinguish goods or services. The Abercrombie spectrum classifies marks from generic to fanciful based on distinctiveness. The Abercrombie spectrum employs hard buckets while the real world ofbranding rarely falls into neat bins: marks often hover at the blurry border between “descriptive” and “suggestive” for example. Byrequiring trademark examiners or researchers to pick one of the five buckets, one loses useful information where the lines get blurry. Sohard boundaries obscure valuable gradations of meaning. In this work, we explore creating a continuous ruler of distinctiveness asa complementary diagnostic tool to the original buckets. The result is a label-free ladder, where every mark, real or synthetic, gets a real-valued score. These continuous scores reveal subtle distinctions among marks and provide interpretable visualizations that help practitioners understand where a mark falls relative to established anchors. Testing with 95 expert-classified trademark examples achieves a Spearman’s ρ = 0.718 and Pearson’s r = 0.724 against human labels, while offering intuitive visualizations on the continuous spectrum. Ademo can be found at https://distinctiveness-ruler-demo.streamlit.app/.

## introduction a trademark is a word, symbol, or other identifier that distinguishes a company's goods or services from those of others @xcite . for example, "coca-cola" serves as a distinctive mark that identifies beverages produced by the coca-cola company, setting them apart from other competing products. as a form of intellectual property, the distinctive nature of an owner's trademark enables consumers to identify the source of goods or services and establishes economic values through brand recognition, customer loyalty, and market differentiation @xcite . assessing distinctiveness is a fundamental task in trademark law. the more distinctive a trademark is, the stronger its legal protection and the greater its potential for granting economic benefits. a trademark's distinctiveness, its ability to signal source and stand apart from other marks, needs to be assessed. in u.s. trademark law, the assessment is guided by the abercrombie spectrum, a framework introduced in abercrombie & fitch co. v. hunting world inc., 537 f.2d 4 (2nd cir. 1976), categorizing trademarks into varies degrees of protection: generic, descriptive, suggestive, arbitrary, and fanciful. generic terms employ the common name of the product and receive no protection. descriptive marks describe a product feature and require secondary meaning foot_0 to qualify. suggestive marks imply qualities and are inherently distinctive. arbitrary marks use common words in unrelated contexts and are strongly protected. fanciful marks are invented terms with the highest level of protection. while the abercrombie spectrum provides a conceptual framework for assessing a trademark's distinctiveness, it poses hard categorical boundaries on what is inherently a context-dependent, continuous property. in practice, some marks might fall into gray areas between categories, and human judgment can vary @xcite . this presents a challenge for assessing consistently, especially with respect to edge cases. this challenge motivates the need for a more continuous, interpretable scale of distinctiveness. instead of hard labels, we propose to leverage synthetic anchors to build a spectrum using a bradley-terry (bt) model. real marks can be place along the spectrum, potentially enabling a more consistent and data-driven assessment that amplifies the nuance nature of distinctiveness. our contributions are three-fold: 1. continuous distinctiveness scaler: we propose a method to model trademark distinctiveness as a continuous spectrum rather than in terms of discrete buckets. ## setup we conduct experiments to assess whether synthetic anchor comparisons can produce a meaningful distinctiveness spectrum for real trademarks. our evaluation focuses on (1) the correlation between model-derived scores and expected trademark distinctiveness, and (2) the robustness and monotonicity of the resulting spectrum derived from pairwise comparisons.