Bibliographic record
Abstract
Translation has variously been described as “transfer of meaning,” “substitution of meaning,” “carry-over of meaning,” “regulated transformation,” etc. If in the West it is attributed to the second fall of man, meaning loss of common language of mankind, in India, it is taken as “new writing.” It involves both the processes of reading and writing and is a bilingual activity. The safe and sound definition of translation could be “new creation” in the target language. The best examples could be the different versions of the Ramayana and the Mahabharata in different regional languages of India based on Valmiki’s The Ramayana and Vyasa’s The Mahabharata respectively. The major theories of translation are Polysystem theory of translation propounded by Itamar Even-Zohar and Gideon Toury; Canadian feminist theory of translation by Susan Bassnett, Barbara Godard, and others; Deconstructive theory of translation by Jacques Derrida; and Cannibalistic theories by Haroldo de Campos and Augusto de Campos. The praxis of translation helps the cause of nation-building and moves toward the creation of World Literature, transcending the boundaries of a nation.
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 | 0.016 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.010 | 0.089 |
| Scholarly communication | 0.019 | 0.024 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".