A multi-dimensional approach to classification of Iran’s languages
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The enterprise of classification is central to the construction of a language atlas, particularly in the Iranian context. While existing two-dimensional models of language classification are useful as a starting point, they are ultimately incapable of handling some of the important complexities found in Iran’s language situation. To address these issues, we propose a multi-dimensional “language relation web”, based on a force-directed multigraph visualization, as an alternative model for expressing connections between language varieties. This architecture allows for differentiation and representation of multiple types of linkages, each of which constitutes a dimension of classification, in a single visualization: shared genealogical inheritance, structural similarity through contact, and association through ethnic identification. The resulting model provides new insights into the classification of Iran’s languages and raises questions and prospects for the broader classification process.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.009 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it