Taking tonal proof to the world stage: developing a framework of creative and strategic choices to enhance an aspiring Australian feature film director's vision
Bibliographic record
Abstract
This thesis is informed by my own transition from short filmmaking to the writing and directing of my first feature film, The Butterfly Tree (2017). It investigates the crucial role of domestic distributors within the context of an Australian feature film ‘mainstream’ funding model and focuses on how domestic distributors evaluate an Australian feature film pitch and project. It also explores the power of tonal proof (for the purposes of this thesis, defined as a short-form project tonally reflective of the long-form project in terms of genre, tone and style). Its central line of inquiry investigates how aspiring Australian feature film directors can efficiently transition from short filmmaking to feature film directing by strengthening their creative vision while simultaneously meeting funding body and funding system requirements. This process has synthesised primary and secondary research with reflective creative practice and praxis, and involved the creation of two short films and an awardwinning feature film. The feature competed at the Toronto International Film Festival, one of the most prestigious ‘A list’ film festivals in the world and was also released theatrically in Australia.
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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 | 0.039 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.058 |
| Scholarly communication | 0.034 | 0.023 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".