Livelihoods and Lifecycles: Dialogs of Sustainability in Film and Video of the Canadian Forest Products Industry
Bibliographic record
Abstract
Sustainability and reforestation have been ongoing concerns of public discourse around the forest products industry in British Columbia, Canada, since the late 1970s, when media images of clearcutting and its perceived threat to wildlife habitats catalyzed activist responses to forestry practices. By the late 1980s, the forest products industry was attempting to regain control of the story of forest management through informational films and videos that promised sustainable harvest and reforestation. As the conflict in BC's old-growth forests known in the Canadian media as the War in the Woods raged into the 1990s, videos provided tree planters, harvesters, and foresters with narratives of sustainability to explain their work in the face of intense media scrutiny. Yet, this body of ecocentric videos that repositioned the forest worker firmly within a lifecycle of destruction and regrowth had limited circulation. This paper examines industrial films from several British Columbia-based forest products companies, as well as internal and trade publications from this period to demonstrate how the forest products industry employed informational and training videos to engage in dialogs of sustainability and to counter criticism of their commitment to forest longevity in the period of the War in the Woods.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 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".