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Record W3154589712 · doi:10.1080/07075332.2021.1907438

Travels in Diplomacy: V.S. Srinivasa Sastri and G.S. Bajpai in 1921–1922

2021· article· en· W3154589712 on OpenAlexaboutno aff
Vineet Thakur

Bibliographic record

VenueThe International History Review · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicColonial History and Postcolonial Studies
Canadian institutionsnot available
FundersNetherlands Institute for Advanced Study in the Humanities and Social Sciences
KeywordsDiplomacyPolitical scienceArtLawPolitics

Abstract

fetched live from OpenAlex

In April 1921, V.S. Srinivasa Sastri was appointed as India’s representative to the Imperial Conference in London. His secretary was a young Indian Civil Service officer, G.S. Bajpai. Over the course of the next two years, the two Indians travelled together as India’s diplomatic representatives to London, Geneva, Washington, Australia, New Zealand and Canada. The young Bajpai and his ‘chief’ developed a loving bond that was to remain strong for the rest of their lives. These travels, as I will show, were very crucial to the making of India’s pre-eminent diplomat in the interwar years, Sastri, and the country’s foremost foreign policy bureaucrat at independence, Bajpai. But the afterlives of these journeys were also to manifest beyond their personal/political lives. These two years were formative to the making of Indian diplomacy in general and to India’s response on the questions of race and the commonwealth in particular. This essay will follow Sastri and Bajpai as they travel together as ‘diplomats’ and map the ways in which they came to ‘learn’ the conduct, expectations and execution of diplomacy.

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)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0040.005
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.048
GPT teacher head0.328
Teacher spread0.280 · 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
GenreEmpirical

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

Citations1
Published2021
Admission routes1
Has abstractyes

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