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Record W6981250474

Dr. Balachandra Rajan: From India to Canada, Fragments in Search of a Narrative - In Memoriam

2009· article· en· W6981250474 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2009
Typearticle
Languageen
FieldComputer Science
TopicLaw, AI, and Intellectual Property
Canadian institutionsnot available
Fundersnot available
KeywordsTributeNarrativeScholarshipSuspectDilemmaPoetryPoliticsFeelingWonder
DOInot available

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.276
Threshold uncertainty score0.555

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0230.004
Scholarly communication0.0080.003
Open science0.0020.004
Research integrity0.0020.011
Insufficient payload (model declined to judge)0.0290.007

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.

Opus teacher head0.066
GPT teacher head0.291
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

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