Uprooting national narratives: representations of the forest industry in Port Alberni, British Columbia
Bibliographic record
Abstract
This work is an analysis of three representations of the forest industry in Port Alberni, British Columbia. I contend that these different representations—a radio broadcast, a museum and a site of heritage tourism—rely upon a dominant national narrative of Canada as a white settler space, a narrative that is racialized and gendered, but which often passes as the ‘truth’ about the nation. Through a discursive analysis of the three sites, I aim to reveal how this process occurs. The white settler narrative, I argue, is problematic from an environmental, anti-racist and anti-oppressive perspective, because of its embedded celebration of colonialism and forest devastation, its racism and its sexism. The project of unpacking the white settler narrative and revealing its oppressive nature helps to disrupt the notion that it is a ‘true’ story about Canada, and creates space for alternative narratives to emerge.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.028 | 0.014 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".