Military Legacies and Indigenous Heritage in Canada's Newest National Park Reserve
Bibliographic record
Abstract
In 2015, the Canadian government created Akami-Uapishk u -KakKasuaak-Mealy Mountain National Park Reserve. Located on the central coast of Labrador, it was designed to protect 11,000 square kilometres of natural landscape and safeguard a 7000-year history of Indigenous cultural heritage through co-management with local Innu and Inuit populations. However, the cultural and ecological history central to the park&s;s creation narrative is at odds with the region&s;s lesser-known, more toxic colonial history. Throughout the 20 th century, colonial decision-making led to the depopulation of Indigenous settlements on the Porcupine Strand, a 40-kilometre expanse of scenic rolling sand dunes and beach along the eastern edge of the Park. This ultimately enabled Cold War military deployment and associated hazardous contamination to occur. Between 2001 and 2004 archaeological surveys recorded more than 100 Indigenous sites along the Porcupine Strand, while also recording evidence of naval Operation NORAMEX, a joint Canadian-American cold war era landing exercise that impacted the Indigenous archaeology on the Strand and continues to pose physical risks for both Indigenous users and visitors. We draw on archaeology, memory and history to situate the toxic legacy within the park into a long-term context and interpret the entanglement of militarism, park creation and colonialism, as well as the impacts of contemporary Indigenous communities.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.009 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".