Locating Criticality in the Lexicography of Historically Marginalized Languages
Bibliographic record
Abstract
In this contribution, we address a practice in which many field linguists working with endangered, Indigenous, and underresourced languages participate: the creation of a dictionary. In such lexicographical projects, there is an urgent need for language workers to become more aware of their own ideological and intellectual baggage and to explore how such projects can contribute to challenging harmful colonial research practices. Informed by long-standing traditions in lexicographical theory, this emerging self-awareness encourages researchers to reflect on the ways their dictionary work aligns with, or diverges from, established practices. We propose that by introducing a degree of criticality and self-reflexivity into lexicography, dictionary work with historically marginalized and underresourced languages can undergo an ethically productive and theoretical reorientation. We situate our contribution in the wider context of critical theory, decolonial studies, and critical Indigenous studies and in the growing literature on language reclamation and Indigenous methodologies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.015 | 0.103 |
| Scholarly communication | 0.015 | 0.016 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".