Mapping the Documentary Field: Independent Filmmaking and Television in Australia
Bibliographic record
Abstract
Television has become the prime medium for distributing documentaries in many countries during the past quarter of a century. In some countries, including Australia, independent filmmakers have increasingly come to interact with broadcasting institutions, public film assistance organisations and market networks of program distribution. These developments have created controversy among scholars and filmmakers over the influence that television exerts on documentary forms. This paper presents a tripartite method for investigating the changing field of documentary: analysis of film support bodies and film policy; attention to the practical experience of independent filmmaking related to television; and exploration of the correlations between documentary forms and their contexts. In doing so, it draws on data, examples and ideas developed in a collaborative research project that focuses on recent Australian documentary. The researchers in this larger project have conducted interviews with filmmakers and cultural administrators, and have investigated the relations between independent production and the structures of film assistance and national and international television distribution. While identifying the problems in the search for documentary form and meaning, the paper highlights the capacity of independent filmmakers to respond imaginatively to changing industrial and technological circumstances.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".