<p>The Ethical Matrix offers a structured framework for ethical deliberation by mapping stakeholders against <i>prima facie</i> ethical principles. This approach is compatible with quantitative analysis, where the matrix is converted into two numerically scored matrices. However, when numerous stakeholders are involved, numerical representations can obscure stakeholder–principle intersections and may encourage misleading aggregation of incommensurable ethical values. Herein, we introduce a post-processing framework (Ethicalc) that preserves the granularity of the scores within the data but complements Ethical Matrix deliberation by improving its visualization. The approach scales impact by importance using the Hadamard product and applies a hyperbolic tangent transformation governed by a deliberation tuning parameter, <i>c</i>, which progressively surfaces additional ethical tensions as its value increases. This enables a gradual increase in the depth of ethical deliberation and yields a characteristic visual heatmap of the ethical dilemma. We first employed the framework on the classical rbST dairy-farming case using illustrative scores are used, and then to a contemporary case study on introducing genetically modified mosquitoes into the wild, for which importance and impact scores were empirically elicited from 20 bioethics-trained participants. This framework is accompanied by a standalone application (Ethicalc) that presents all analytical layers, including qualitative interest statements, raw scores, and color-coded matrices, within a single interface.</p>