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Record W2548996622

Theme of Adore and Nationalism in Tagore’s Gitanjali: A Study

2016· article· en· W2548996622 on OpenAlexvenueno aff
G. R. Maruthi Sankar, M. Sriprabha, Suchitra S Kumar, Rakesh Kumar

Bibliographic record

VenueHigher education of social science · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicIndian History and Philosophy
Canadian institutionsnot available
Fundersnot available
KeywordsTheme (computing)HumanityPoetryLiteratureDivinityPhilosophyArtTheology
DOInot available

Abstract

fetched live from OpenAlex

Rabindranath Tagore (1861-1941) was a significant contributor to the emerging history of Indian Literature in English. His famous work Gitanjali gave him worldwide recognition. It won him Nobel Prize for Literature in 1913. It was appreciated for its creativity by W. B. Yeats, Ezra Pound and many other European critics. The songs in Gitanjali are the Poet’s meditation on God, Man and Nature. This work Gitanjali expresses his keen sense of observation, his lively curiosity, his humour, and humanity, his Philosophies of love, life and God. Tagore’s Gitanjali has been celebrated as a great poem on the divinity of love. Love lights the inner world of human feelings and sensibilities, and one of the oldest as well as Universal emotions and it is also the most complex and versatile of all emotions. The spirit of love is advocated by religions and celebrated in Literature. Apart from man - woman relationship, love between father and daughter, mother and son, man and God, has been a recurrent subject for Literature. The treatment of love in Indian Literature dates back to Classical Literature. Here, an attempt is made to analyse the theme of love in Tagore’s Gitanjali. “Gitanjali,” or Song Offerings, is a collection of poems translated by the author, Rabindranath Tagore, from the original Bengali. This collection won the Nobel Prize for Tagore in 1913. This volume includes the original introduction by William Butler Yeats that accompanied the 1911 English language version. Gitanjali is a collection of over 100 inspirational poems by India’s greatest poet.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.287
Teacher spread0.246 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations2
Published2016
Admission routes1
Has abstractyes

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