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Record W2578942293 · doi:10.3138/jsp.48.2.76

Laying Tracks as the Train Approaches: Innovative Open Access Book Publishing at Heidelberg University from the Editors' Point of View

2017· article· en· W2578942293 on OpenAlexvenueno aff
Andrea Hacker, Elizabeth Corrao

Bibliographic record

VenueJournal of Scholarly Publishing · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistic Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsPublishingWorkflowReading (process)Point (geometry)Face (sociological concept)Product (mathematics)Process (computing)Computer scienceInstitutionWorld Wide WebLibrary scienceManagementSociologyPolitical scienceDatabaseLawSocial science

Abstract

fetched live from OpenAlex

In April 2016, Heidelberg University's newly founded open access publisher heiUP launched the first volume of the new book series Heidelberg Studies in Transculturality. This article reports on the challenges, accomplishments, and setbacks that informed the entire editorial production process, not only of the first volume but also of the series and the publishing enterprise overall. The authors offer insights on crucial issues that any new open access publishing endeavour at an institution might face, namely acquiring manuscripts, designing and building workflows, and collaborating with partners to build an outlet for hosting the finished product. This article also illustrates how the goal of providing a new digital reading experience through an innovative HTML format, in addition to print-on-demand and PDF versions of each manuscript, affected the progress of the entire project. Finally, we report on what it took to deliver results.

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)0.006
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.999
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0050.006
Scholarly communication0.0260.012
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0120.003

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 head0.280
GPT teacher head0.359
Teacher spread0.078 · 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 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

Citations5
Published2017
Admission routes1
Has abstractyes

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