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Record W2549315197 · doi:10.1057/978-1-137-46163-6_3

The Ideologies of English Intellectualism and of American Philanthropy

2016· book-chapter· en· W2549315197 on OpenAlexaboutno aff
Anna Rosser Upchurch

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2016
Typebook-chapter
Languageen
FieldArts and Humanities
TopicScottish History and National Identity
Canadian institutionsnot available
Fundersnot available
KeywordsIdeologyIntellectualismThe artsPolitical scienceSociologySocial scienceLawPolitics

Abstract

fetched live from OpenAlex

This chapter first explores the ideology of English intellectualism that influenced the identities of Keynes and Massey: a notion of the ‘clerisy’ first articulated in the nineteenth century in England by the poet Coleridge. The chapter argues that the clerisy tradition, with its insistence on social responsibility for the man who had the benefit of an education at Oxford or Cambridge, influenced intellectuals and wealthy aesthetes to involve themselves in arts policy in Great Britain and Canada. The ideology of philanthropy, as articulated by Andrew Carnegie in the early twentieth century, shaped the identities and motivations of Massey and Elmhirst to use their wealth to fund cultural projects and get involved in arts policy recommendations. The chapter concludes that intellectuals and philanthropists shared common beliefs about their social roles, and they collaborated to establish cultural institutions, including arts councils. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.021
Scholarly communication0.0070.004
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.025
GPT teacher head0.224
Teacher spread0.199 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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