Dr. Balachandra Rajan: From India to Canada, Fragments in Search of a Narrative - In Memoriam
Bibliographic record
Abstract
A heartfelt memorial piece for Dr. Balachandra Rajan, an Indian diplomat and poetic scholar, written by Teresa Hubel.\nIntroduction:\nWhile preparing to write this tribute to Dr. Balachandra Rajan, I found myself wondering what in his eminent life I should be recalling for your benefit. Which events or personal preferences, habits, gestures, or even political commitments and publications can be tallied up to create some kind of coherent narrative that conveys the gist of him? The dilemma is that, when it comes to Dr. Rajan (who in my memory can never be remembered as anyone other than Dr. Rajan, not Balachandra or Dal, as he was known by his friends here), the details I could cobble together to create the gist that he was to me arc, I expect, different from what others might gather, others who have also known him, respected him, and loved him, as I did, and who, like me, found their lives changed by him. I suspect that his colleagues in Milton scholarship and in his department at the University of Western Ontario are better able to describe his public side: his many professional achievements, for instance, and all his theoretically diverse and numerous publications. It seems to me that, because I spent so much time apparently idly talking with Dr. Rajan in the last twenty years or so, mostly about his life and the people whose lives mattered to him and about India, a country that partially defined him and also often annoyed him and the fascination for which brought us together initially and then many, many times afterward it would make sense for me to linger awhile over the decisions he made that brought him, finally, to London, Ontario, Canada. The man who impressed me was somewhere in those decisions.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.004 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.011 |
| Insufficient payload (model declined to judge) | 0.029 | 0.007 |
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".