Developing Indigenous Language Materials for Schools and Land-Based Documentation: Gwa'sala-'Nak'waxda'xw Nation and Kwakwala (ISO: kwk)
Bibliographic record
Abstract
This study examines school-based and land-based language materials for Kwakwala (ISO, kwk) developed during a three-year investigation (2016)(2017)(2018)(2019).The materials focussed on three requirements: first, supporting teachers and researchers who are learning the language, second, ensuring that documentation is accurate and conforms to curriculum and guidelines from Elders, and third, integrating Indigenous language and knowledge throughout school activities and revitalization of traditional homelands.I address the above requirements using a Transdisciplinary model to approach the complex multi-disciplinary needs of the school and land-based activities.These require Indigenous knowledge and expertise from numerous disciplines.In this study, similar to Mark and Turk (2021), various disciplines (Indigenous and Western-based) are unified through an overarching theory.Situated Learning is the unifying theory to ensure language, social, cultural, and locational contexts are authentic and situated in Indigenous settings.Evidence-based analysis is the over-arching method used to examine the materials.Together, these frame Situated Documentation, a method used in this study to situate community-based documentation in authentic locations.Participatory Action Research integrates the expertise of school staff, researchers, experts, Chiefs and Elders with the researcher.iii Transdisciplinary highlights include Word Paradigm corpus-based concordance analysis to compare Kwakwala inflections in materials with curriculum expectations, multimodal ethnographic coding of print and multimedia materials to examine the situational accuracy and consistency of language and social conventions, and comparative analysis to determine the communicative competence in narratives.In addition, analyses include comparison with earlier materials, attention to ethnophysiography, and examination of the study-developed computer-based parser to correct difficulties with written documentation.In conclusion, the materials developed during the study assist the community and the school to achieve their goals to revitalize their homelands and language.The materials meet curriculum expectations, represent language and Indigenous themes, conform to Indigenous social values and dialect variation, and demonstrate authentic and accurate land-based documentation.Results from computer-based parsing demonstrate improved documentation of written language.Recommendations indicate that non-fluent teachers benefit from grammaticalfunctional materials and links between curriculum expectations and language structures, while both teachers and land-based researchers benefit from situating documentation activities in authentic locations.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".