Bibliographic record
Abstract
Ketaki Datta is an Associate Professor of English at Bidhannagar College, Kolkata; a novelist, a critic and a translator. She wrote her PhD thesis on Tennessee Williams, which she published in 2011 under the title The Black and Nonblack Shades of Tennessee Williams (Bookworld, Kolkata). Among her accomplishments as an editor, the following volumes deserve mention: Indo-Anglian Literature: Past to Present (Booksway, Kolkata, 2008), New Literatures in English (Bookworld, Kolkata, 2011), and Sahitya Akademi Award-winning English Collections: Critical Overviews and Insights (Authorspress, New Delhi, 2014). Her translation from Bengali of Paadi (The Voyage) by Jarasandha (the pen name of Charu Chandra Chakraverty) was published in 2008 (Booksway, Kolkata), while her translation of Shesh Namaskar by Santosh Kumar Ghosh (Shesh Namaskar = The Last Salute) was released in 2013 (Sahitya Akademi, New Delhi). Her articles and translations have been published in various international journals, and her poems are featured in Brian Wrixon’s anthology (Canada). Her debut novel, A Bird Alone (Sarup Books, New Delhi, 2009) has been highly commended by the reviewer of Dorrance Publishing Co. (USA), besides being positively reviewed by Indian Literature (Sahitya Akademi), the Telegraph, and the Sunday Statesman (India).
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.029 | 0.007 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.017 |
| Insufficient payload (model declined to judge) | 0.021 | 0.006 |
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".