Environment and society in Átl’ḵa7tsem/Howe Sound Biosphere: towards an integrated media ecology
Bibliographic record
Abstract
In 1895, the Lumière brothers’ Workers Leaving the Factory marked the birth of cinema and the mass dissemination of visual communication. The power of screen-based images allowed ordinary people to see their world and their place in it in a new way, with the light of a new unifying force, spoken in silence. Art, entertainment and propaganda, these images and the way they were created in many ways foretold the impacts they would have on their environment, such as in the first documentary, Nanook of the North, shot in the Canadian Arctic about an Inuit man named Allakariallak (1922). The Lumière workers’ factory also marked the industrialisation of cultural storytelling, contributing to the symbolic annihilation of marginalised communities, including Indigenous people and nature, relegated to the backdrop in film studies, rather than character. Moreover, the deregulation of communications industries would lead to a global climate crisis in our media ecology. More than a century since the silent spring of cinema, nature is being granted legal status and has become the central character in determining the outcome of our human story. The Bachelor Degrees of Environment and Society at Capilano University, Canada, endeavour to remediate these education ‘hotspots’ by integrating Indigenous land- and water-based knowledge with environmental studies, science and slow cinema praxis in a sensitive, multi-jurisdictional biosphere region, Átl’ka7tsem/Howe Sound Biosphere, Canada, under the unifying concepts of consilience, decolonisation and sustainability. These educational models attempt to offset the impacts of colonialism and corporatism, creating a balance between humans, industry and the environment, modelling reconciliation as a way forward.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.017 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 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".