Bibliographic record
Abstract
Kristian Lever’s ambitious short film I Need You to See Me (2024) centres on the relationship between troubled ballet student Hilton (Rory Toms) and substitute teacher Ethan (Sam Salter). In this interview, Lever and I discuss how his company Klever Creatives has expanded from telling stories via dance and dance theatre to film, and we examine this project, which brings it all together. Lever goes over the casting process before delving into the world of the ballet school and how it so often fails to provide young people such as Hilton with adequate support. In the film, Hilton faces homophobia at home, and behind the scenes, he has kicked a boy in the face. However, he weaponizes his vulnerability; and he abuses Ethan’s trust when he blackmails his teacher sexually. Lever and I go over his reading of the film, what Hilton’s actions mean for him and what they mean for Ethan, and the prospects of Lever’s returning to these characters. This interview advances scholarship by introducing Lever’s creative programme, by examining the film’s depiction of the ballet classroom, and by exploring how it might do more.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.030 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".