Bibliographic record
Abstract
"Nights of Broken Glass" is an original screenplay inspired by my Grandfather's (Jan Schenk) testimony of his experiences in two different concentration camps during the Second World War. His experiences are fictionalized through my main character Treenka Hooksma, a seventy-seven year old woman living in Canada. When she moves to Birchville Manor, she associates the place with the concentration camp she was imprisoned in during her youth--' Sachsenhausen'--the second camp in which my Grandfather was incarcerated. She decides to leave the Manor and returns home where she finds seventeen-year-old Casie Simard in her old house. Although Casie has been hired to "clean out" Treenka's house, Treenka mistakenly identifies Casie as a ghost--one of five who have been haunting Treenka for over fifty years. The film investigates the relationship between these two women--their suspicion, trust, misunderstanding, forgiveness and love for one another.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 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; 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".