Destruction and Disjuncture: Ironies of Apology, Exhibition, and Ethnography along British Columbia’s Dammed Peace River
Bibliographic record
Abstract
Abstract In June 2016, BC Hydro (British Columbia’s provincially-owned electric utility) opened a new exhibit at the W. A. C. Bennett Dam Visitor Centre. The Our Story, Our Voice gallery brought the hardships endured by the region’s First Nations citizens as a result of the fifty-year-old dam to light. A carefully crafted apology from BC Hydro’s Deputy CEO figured prominently in the gallery’s opening ceremony. But with a controversial new dam threatening the province’s last stretch of free-flowing Peace River, both the exhibit and the apology were deeply ironic. This article draws on my complex and contradictory experience at the exhibit’s opening ceremony to ground an exploration of irony’s analytical value: I examine the irony inherent in apologizing for past transgressions while perpetuating very similar new ones, investigate the exhibit itself as a paradoxical presentation, and acknowledge that my presence in British Columbia was possible because of a foundation established by a man—Axel Wenner-Gren—who was both an early proponent of damming the Peace River and an ethnographic enthusiast. Embracing reflexive attention to momentary, power-laden, and occasionally uncomfortable encounters with people, places, and evidence, I demonstrate how contemplating irony can serve as a compelling way to convert experience into understanding.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.028 | 0.025 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".