Bibliographic record
Abstract
Abstract The term ‘recut’ designates a trailer that a fan has created by editing footage from a film or trailer to new sound (voice-over, sound effects and underscore). The resulting re-imagined audio-visual text typically presents a genre-shifted narrative that intertextually relates to the source material. The ‘re-tuning’ by fan-editors involves imposing a new soundtrack (usually music and/or narration) over reordered and edited images, like the adapted family-friendly ‘Shining’ (2005) from the horror film The Shining (Kubrick, 1980) or the horror trailer refashioning of ‘Mrs. Doubtfire – Recut’ (2009). The literature about ‘vidding’ and recutting provides a foundation for considering how fans provoke new meanings when they add or re-order voice-overs, sound effects and music in recut trailers. The fan-editor must creatively engage with genre-based cinematic trailer practices and traditions of musical signification in re-imagining the source text. Thus sound effects and electronically distorted music predominate in re-tuned horror trailers, like ‘Mrs. Doubtfire – Recut’ or ‘Scary Mary Poppins’ (2006), while light-hearted melodies and instrumentation prevail when adapting source material to create a recut comedy trailer (‘The Wicker Man’ 2006). Thus the recut and re-tuned trailer represents a transformative nexus of sight and sound within fandom.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".