Canadian Documentary in the Global Context
Bibliographic record
Abstract
The last thirty years have seen an enormous expansion of documentary practice and the proliferation of documentary across a wide variety of platforms on a global scale. This expansion comes at a time of increasing global integration and the growing need to address problems on a planetary scale, such as climate change, refugees and mass migration and continuing armed conflicts around the world. Canada is a founding nation of documentary practice and continues to be a world leader, advancing the use of visual and audio documentary to address global economic, environmental and cultural challenges and recording the human experience. Incorporating clips from relevant films, this talk will address Canadian documentary practice in the global context and examine the traditional role of documentary to record and reveal human stories and to ‘speak truth to power’ in an increasingly integrated world. About the Lecturer: Tim Schwab is Professor in the Department of Communication Studies at Concordia University in Montréal where he teaches video and sound production and documentary studies. He has produced and directed numerous documentaries including THE BURNING BARREL, winner of the Distinguished Achievement in Documentary award from the International Documentary Association, and the acclaimed Canadian Broadcasting Corporation documentary BEING OSAMA, broadcast on television networks worldwide. His feature documentary CINEMA PALESTINE was released 2014 and has played in over twenty film festivals in North America, the UK and the Middle East.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.030 | 0.012 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.036 | 0.002 |
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".