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Record W2054300561 · doi:10.1111/1469-8219.00085

The poetry of nationalism<sup>*</sup>

2003· article· en· W2054300561 on OpenAlexaff
David Aberbach

Bibliographic record

VenueNations and Nationalism · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsMcGill University
Fundersnot available
KeywordsNationalismPoetryMilitarismLustMythologyNazismLiteraturePatriotismSociologyLawPolitical scienceArtPolitics

Abstract

fetched live from OpenAlex

Abstract. The poetry of nationalism has roots in ancient literature, particularly the Hebrew Bible, but is mostly a product of nationalism since the French Revolution. Many national poets are politically active and serve in government. Asserting artistic individuality, they express national individuality, though nationalism can also suppress creativity. Calling for moral regeneration, poets inspire their people with memories of heroism, real or imagined, and with myths unique to the nation. Their poetry often springs from defeat but anticipates national liberation and independence. Yet there is also a dark side to some national poets, particularly in their glorification of violence and lust for revenge against oppressors. National poetry changed after the failed revolutions of 1848–9. National poets were less inclined to believe in liberal ideals and progress toward universal goals and there was greater disillusionment and ambiguity toward the national role. World War I severely limited the militarist tendency in national poetry.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.005
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.017
GPT teacher head0.330
Teacher spread0.313 · 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 designQualitative
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

Citations17
Published2003
Admission routes1
Has abstractyes

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