From Wessex to India: Adapting Hardy's <i>Tess</i> in <i>Trishna</i>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Thomas Hardy's novels have been translated into Western film culture now for a century, and, most recently, a welcome filmic consideration of Tess of the d'Urbervilles (1891) is provided in Trishna (2010). Written and directed by Michael Winterbottom, the film is an adaptation of the tragic tale of Tess d'Urberville from Wessex into the equally difficult life of Trishna from Rajasthan, India. This article considers how Hardy's tale translates into a different, 21st century country, and how the portrait of Winterbottom's heroine and the contextual complexities found in the filmic narrative maintain – in spite of changes in place, space and character(s) – the integrity of Hardy's original novel.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it