Bibliographic record
Abstract
The first time I met Marjorie Chan was a couple of years ago at a performance she was starring in at the Solar Stage. She and another actor, Peter van Gestel, were the sole actors in a couple of Tennessee Williams plays, Talk to Me Like the Rain and Let Me Listen and This Property Is Condemned. I was there at her invitation to check out her work for a short film I was trying to make on a shoestring budget and a dream, and finding an Asian actress for the part was not an easy task. It was my first real film and it would be the first time that I had ever worked with actors. I was dealing with a subject – sexual violation – that required some delicacy and sensitivity, both on my part and on the part of the actor. The film was meant to be a visual film poem, without dialogue, and the storytelling needed to be conveyed in slight nuances – very much dependent on the actor and what she brought to it. I had never seen Marjorie perform before, and as the lights dimmed and the play started, I was elated to find that Marjorie could act. I was excited, and when I met her after the performance we agreed that the film would be something we could do together.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.093 | 0.003 |
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; both teacher heads agree on what is shown here.
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".