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The Political Economy of Andrew Carnegie's Library Philanthropy, with a Reflection on its Relevance to the Philanthropic Work of Bill Gates

2010· article· en· W2009280532 on OpenAlexaff
Siobhan Stevenson

Bibliographic record

VenueLibrary & Information History · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHegemonyPoliticsSociologyRelevance (law)IdeologyBattleMedia studiesCapital (architecture)Public administrationPolitical scienceLawHistory

Abstract

fetched live from OpenAlex

When it was announced in 1997, Bill Gates' library philanthropy programme attracted a tremendous amount of media attention. A central feature of that coverage was a renewed interest in Andrew Carnegie's library building programme. While identifying the historical similarities between Carnegie and Gates is an interesting exercise, failure to ground these comparisons in a critical policy analysis frame that attends to the political economy of largescale private philanthropy seriously limits, if not jeopardizes, the public library community's ability to respond to the broader cultural implications of Gates' library programme. Here, the radical philanthropic approach is used to frame a historical analysis of Andrew Carnegie's philanthropy as a response to the contemporary class warfare of the period, within which he was deeply implicated. Unpacking Carnegie's library philanthropy for its ideological importance in the struggle over the ownership and control of the means of industrial production provides a powerful analytic lens through which to view capital's updated hegemonic project, as reflected in Gates' philanthropy, which is designed to bring software and internet connectivity to America's public libraries.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
gptno category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
models splitAgreement compares identical category sets and study designs across arms.

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)0.003
metaresearch head score (Gemma)0.008
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 score0.111
Threshold uncertainty score0.220

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0300.029
Scholarly communication0.0190.008
Open science0.0010.005
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0080.001

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 head0.260
Teacher spread0.235 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Qualitative
Domainnot available
GenreOther

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

Citations9
Published2010
Admission routes1
Has abstractyes

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