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Record W2016814977 · doi:10.1080/00467600802054562

A long shadow: Frederick P. Keppel, the Carnegie Corporation and the Dominions and Colonies Fund Area Experts 1923–1943

2008· article· en· W2016814977 on OpenAlexaboutno aff
Richard Glotzer

Bibliographic record

VenueHistory of Education · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Education Studies Worldwide
Canadian institutionsnot available
Fundersnot available
KeywordsShadow (psychology)CorporationSociologyManagementPolitical sciencePublic administrationPsychologyEconomicsLaw

Abstract

fetched live from OpenAlex

The Carnegie Corporation found its first great manager in Frederick Paul Keppel (1875–1943). Keppel's career is important to historians of education because interwar Carnegie initiatives, articulated through the Corporation's Dominions and Colonies Fund and Teachers College, Columbia University, internationalised American educational theories and practices throughout the English‐speaking world. Keppel's concept of key men, prominent authorities influencing events in their home countries, was central to these endeavours. Both products and advocates of modernism, key men put their confidence in the natural and social sciences, in turn melded into the grand themes of their times; the British Imperial Mission, American Expansionism, and shared Anglo‐Saxon racial identity. The preparatory nature of Keppel's life and work experiences are first explored. The article then surveys how the complex, yet remarkably informal, network of overseas key men were established. An examination of the Carnegie legacy offers some conclusions.

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 score0.240
Threshold uncertainty score0.476

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0080.004
Scholarly communication0.0040.002
Open science0.0000.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0180.001

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 head0.086
GPT teacher head0.308
Teacher spread0.222 · 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

Citations10
Published2008
Admission routes1
Has abstractyes

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