Modern Wendat Lexicography: Using XML to Reflect the Grammar and Lexicon of an Iroquoian Language
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: Building dictionaries with tools and methods emerging from Eurocentric traditions has proved problematic for Indigenous languages. We are building a dictionary for Wendat, an Iroquoian language formerly known as Huron that is being reawakened in Wendake, Québec. There are twelve manuscript dictionaries and lexicons for Wendat, created by missionaries during the seventeenth and eighteenth centuries. We are encoding the manuscripts using a standard Text Encoding Initiative (TEI) schema. However, when we came to create and encode a modern reconstructed Wendat dictionary, we were overly constrained by Eurocentric structures and assumptions inherent to TEI. Building our own custom XML schema allows us to better reflect Wendat grammar, responding to community needs and our evolving understandings of the language. This article describes the development of this schema, based on analysis of the archival documentation and related languages. Through this discussion, we will exemplify the schema we built and address the points of friction between TEI and Wendat grammatical structures. Our custom schema enables us to elegantly and economically represent exactly what our analysis of the language reveals, capturing elements of the language such as event-verb consequentiality, conjugation class, and stems, while avoiding incompatible elements and assumptions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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