Bibliographic record
Abstract
Travel literature is considered a major source of knowledge of customs, traditions and culture in a society. A traveller writes to inform others about his experiences. Chaudhuri went to England to share his experiences with the viewers of BBC. The memoir written by Nirad C. Chaudhuri is essentially subjective and is called A Passage to England. While some of his ideas based on his readings were close to reality, some others had to be recreated in the light of the reality. The first hand experience added to the knowledge gained through reading. For Chaudhuri as for many others “one half of his perception of England was the perception of something not India”. The differences in the two cultures as expressed by Chaudhuri strike the reader just as they must have been felt by Chaudhuri when he saw and experienced them. Comparisons have been made between Chaudhuri's A Passage to England and E.M. Forster's A Passage to India. Although the two belong to different genres both focus on the interactions between a majority group and an individual or a small group of individuals of an altogether different group.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".