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| title: DiscourseGeometry | |
| emoji: 🧭 | |
| colorFrom: green | |
| colorTo: blue | |
| sdk: gradio | |
| sdk_version: 5.49.1 | |
| app_file: app.py | |
| pinned: false | |
| license: apache-2.0 | |
| short_description: Compare text collections on semantic axes | |
| # DiscourseGeometry | |
| Reference implementation of the spatial-geometric framework for discourse comparison | |
| (Vallego, 2026, [SSRN](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6387958)). Part of the | |
| [H4rmony Project](https://theh4rmonyproject.org). | |
| Two collections of texts are placed in the semantic space of a sentence encoder and compared on a **primary axis** | |
| and up to five **secondary axes**. Each axis is defined by two sets of exemplar texts (pole A, pole B); secondary | |
| axes are orthogonalised with Gram-Schmidt in the order given. The default preset reproduces the paper's study | |
| (TinyLlama-1.1B-Chat vs its H4rmony fine-tuned version on 60 prompts, four ecosophical axes). An extended preset | |
| adds two secondary axes proposed in the paper's §9.2, Non-human Agency and Intergenerational Responsibility | |
| (exemplars in `extra_axes.py`), appended after the paper's three so their results are unchanged. | |
| **3D view.** Two modes. *Semantic map* (default, as in SpatialSemanticAnalysis): x = position on a chosen axis | |
| (0–100%), y and z = the two main directions in which all texts differ once that axis is removed; the pole exemplars | |
| are shown with the collections. *Chosen axes*: any three axes (primary or secondary), as raw projections or | |
| orthogonalised in the chosen order, with each collection's centroid and first principal component. | |
| **Documentation.** `DiscourseGeometry_Documentation.docx` explains every input, measure and output. | |
| ## The six layers | |
| | Layer | Question | Reported | | |
| |---|---|---| | |
| | Axis validation | Are the axes well defined? | pole separation, separation ÷ mean SD, d′, leave-one-out check, angles between axes, primary–secondary overlap | | |
| | 1 · Primary axis | Where does each collection sit, and did it move? | mean score and position, shift, t-test, Cohen's d, permutation p, optional neutral baseline | | |
| | 2 · Secondary axes | Which dimensions moved? | Gram-Schmidt-projected shifts with Bonferroni correction | | |
| | 3 · Order check | Do the results depend on the Gram-Schmidt order? | GS vs raw shifts and their ratio | | |
| | 4 · Secondary Frobenius | How is the shift spread across the named dimensions? | column norms and shares | | |
| | 5 · Full-space Frobenius | How large is the total difference, and how much do the named axes capture? | ‖ΔE‖_F, per-unit shift and consistency, coverage of the primary, secondary and combined subspaces vs random directions, residual | | |
| | 6 · Eigenanalysis | Did the shape and orientation change? | eigenvalues, isotropy, effective dimensionality, PC1 loadings, PC1 angle to the primary axis, principal-axis rotation with permutation test and bootstrap intervals; also in the full space | | |
| **Designs.** *Paired*: two sets of responses to the same prompts in the same order (paired t-test, Cohen's d_z, | |
| sign-flip permutation, per-unit Frobenius as in the paper). *Independent*: two corpora (Welch t-test, Cohen's d, | |
| label permutation, Frobenius as centroid separation with its share along the axes, plus shape difference). | |
| **Robustness.** The encoder can be switched (all-mpnet-base-v2, bge-base-en-v1.5, e5-base-v2, a multilingual mpnet) | |
| to check that findings do not depend on one model. | |
| **Scales.** Score = dot product with the axis (positive = toward pole A), as in the paper. | |
| Position = 0% at the pole B centre, 100% at the pole A centre. Eigenvector signs are arbitrary, so only angles | |
| between directions (0–90°) are interpreted. | |
| **Generation (optional).** The two collections can be generated in the app from a list of prompts with any two | |
| Hugging Face causal language models (greedy decoding). | |
| ## Cite | |
| Vallego, J. (2026). *A spatial-geometric framework for discourse comparison: Centroid projection, Frobenius norm, | |
| and eigenanalysis in a constructed semantic measurement space*. SSRN. | |
| https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6387958 | |
| Vallego, J. (2026). *DiscourseGeometry* [Software]. Hugging Face Spaces. | |
| https://huggingface.co/spaces/neovalle/DiscourseGeometry | |