Indigenous Ecocinema: Decolonizing Media Environments
Bibliographic record
Abstract
Introducing the concepts of d-ecocinema and d-ecocinema criticism, Monani expands the purview of ecocinema studies and not only brings attention to a thriving Indigenous cinema archive but also argues for a methodological approach that ushers Indigenous intellectual voices front and center in how we theorize this archive. Its case-study focus on Canada, particularly the work emanating from the imagineNATIVE Film + Media Arts Festival in Toronto--a nationally and internationally recognized hub in Indigenous cinema networks--provides insights into pan-Indigenous and Nation-specific contexts of Indigenous ecocinema. This absorbing text is the first book-length exploration foregrounding the environmental dimensions of cinema made by Indigenous peoples, including a particlarly fascinating discussion on how Indigenous cinema’s ecological entanglements are a crucial and complementary aspect of its agenda of decolonialism. Additionally, see West Virginia University Press Booktimist's Q&A with author Salma Monani: https://booktimist.com/2024/12/12/the-author-of-indigenous-ecocinema-describes-new-ways-to-approach-indigenous-responses-to-climate-issues/
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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; both teacher heads agree on what is shown here.
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".