A critical analysis of implications for Indigenous nationalism in Nunavut and the role of education and language instruction.
Bibliographic record
Abstract
The following will draw from Marxist and critical theories, along with Indigenous and decolonial concepts, which are being applied to consider an intersection between language and education policy, and its role in nationalist discourses in Nunavut. Of particular concern is the way that educational justifications are being used in order to encourage the standardization of Inuktitut. With reference to the limited body of research in this area, the unintended consequences of this project will be considered from the perspective of a teacher who spent a year teaching in a minority language community. The unintended, or oftentimes acknowledged consequence of standardization being the erosion of minority dialects has counterhegemonic consequences whereby teachers are likely to resist and resent a centralized imposition of a standard dialect if it means sacrificing their regional, or sometimes community specific dialect of Inuktitut. This exploration will situate the ongoing language standardization within a history of nationalist movements which have privileged a standard dialect in the name of national unity really emerging during the period of national unification from around 1870-1910s in Europe. It will be argued that Inuit language authorities are replicating this process with similar justifications made over the past century.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.033 | 0.041 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".