"To Bring a Little Bit of the Land": Tanya Tagaq Performing at the Intersection of Decolonization and Ecocriticism
Bibliographic record
Abstract
Two needs that have grown increasingly critical in Canada throughout the twenty-first century are the reduction of global warming and the decolonization of lands, social institutions, and collectivities.Rather than operating independently, decolonization and environmentalism intersect as Indigenous actors contest Western assumptions about "nature" by asserting their own ecological frameworks.In this thesis, I explore Inuk vocalist Tanya Tagaq's artistic contributions to these efforts by analysing her musical commentaries on "nature" in light of Indigenous scholarship on "decolonization."I argue that Tanya Tagaq performs decolonized environmental Each instructor created welcoming learning environments in their classrooms and challenged me to explore new ways to engage music practices, and the lively discussions and comradery among my classmates greatly enriched my time at Carleton.I look forward to the future of each of their careers.Finally, I am particularly grateful for my friends and family.I truly appreciate the continual excitement, engagement, and emotional support that they provide, without which this task would have seemed all the more formidable.Their love and support are of the highest quality and value.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.020 | 0.010 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".