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Record W2154019950 · doi:10.22230/src.2014v5n4a189

Meeting Scholars Where They Are: The Advanced Research Consortium (ARC) and a Social Humanities Infrastructure

2014· article· en· W2154019950 on OpenAlexvenueno aff
Elizabeth Grumbach, Laura Mandell

Bibliographic record

VenueScholarly and Research Communication · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicDigital Humanities and Scholarship
Canadian institutionsnot available
Fundersnot available
KeywordsOutreachScholarshipDigital humanitiesWorld Wide WebLibrary scienceScholarly communicationConstruct (python library)SociologyComputer sciencePolitical sciencePublishing

Abstract

fetched live from OpenAlex

The Advanced Research Consortium (ARC) is the central organizing force for several virtual research environments (VREs). ARC is the hub for these period-specific nodes, which offer digital project peer review, aggregation and search technologies, and forms of community engagement. The mission of both ARC and the nodes is to construct and support a “social system” for the humanities in which the digital and the traditional can come together to develop a working social humanities infrastructure. This article discusses how the ARC infrastructure evolved from the framework of scholarly engagement developed by NINES (Networked Infrastructure for Nineteenth-Century Electronic Scholarship) and explains how the consortium assists the scholarly community: through digital project peer review, aggregation and search, and outreach services.

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)0.019
metaresearch head score (Gemma)0.026
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0170.015
Scholarly communication0.0200.020
Open science0.0020.033
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0170.003

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 head0.125
GPT teacher head0.346
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.

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
Published2014
Admission routes1
Has abstractyes

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