The Localization of Eugene O’Neill’s Play Desire under the Elms on China’s Stage
Bibliographic record
Abstract
This paper explores the acceptance of Eugene O’Neill’s play Desire under the Elms in China and studies the localization of this play on Chain’s stage. From the angle of acceptance, it examines when a culture accepts the influence of another culture, how one culture chooses and transforms another and gives birth to a third one: a variant resulting from the collision and merging of these two cultures. Key words : localization; Eugene O’Neill’s play Desire; culture Resume: Cet article etudie l'acceptation de Desir sous les ormes d'Eugene O'Neill en Chine et la localisation de cette piece sur la scene en Chine. Du point de vue de l'acceptation, il examine quand une culture accepte l'influence d'une autre culture, comment elle choisit et transforme une autre culture et en concoit une troisieme culture: une variante resultant de la collision et de la fusion de ces deux cultures. Mots-Cles : localisation; Desir sous les ormes; Eugene O'Neill; culture
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.015 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".