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Record W2029262987 · doi:10.1353/scp.2011.0036

Journal des Savants: From the Republic of Letters to the Cloud Library

2011· article· en· W2029262987 on OpenAlexvenueno aff
Claude Potts

Bibliographic record

VenueJournal of Scholarly Publishing · 2011
Typearticle
Languageen
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsDigitizationRealmNewspaperCloud computingWorld Wide WebScarcityCollection developmentService (business)Library scienceDigital libraryComputer scienceMedia studiesPolitical scienceSociologyLawArtTelecommunicationsBusinessLiterature

Abstract

fetched live from OpenAlex

As more books, journals, and newspapers make the inevitable transition to the electronic format, academics get the sense that the only scholarly materials one really needs can be found in the digital realm. Through the imagined voice of the Journal des Savants —the world's oldest scholarly journal still active today—this article brings to the surface valid concerns about print scarcity, familiar terrain for not only Europeanists but for anyone who works in area studies. It objects to conventional metrics for determining scholarly value and reconfirms known perils of relying solely on the mass-digitization efforts of Google Books. Most importantly, the article questions an over-reliance on digital preservation repositories such as LOCKSS, CLOCKSS, Portico, and HathiTrust—key players in the so-called Cloud Library, or external network of trusted digital library collection and service providers. The push toward cloud-sourced collections comes at a time when research libraries are hastily embarking on ambitious cooperative regional initiatives to systematically de-duplicate their costly, problematic, redundant, and very much terrestrial print collections.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.979
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0180.007
Scholarly communication0.0210.009
Open science0.0010.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0280.006

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 head0.205
GPT teacher head0.256
Teacher spread0.051 · 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.

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

Citations2
Published2011
Admission routes1
Has abstractyes

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