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Record W2810674742 · doi:10.1093/llc/fqy079

Shelf life: Identifying the abandonment of online digital humanities projects

2018· article· en· W2810674742 on OpenAlexaff
Luís Meneses, Richard Furuta

Bibliographic record

VenueDigital Scholarship in the Humanities · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicDigital Humanities and Scholarship
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsDigital humanitiesAbandonment (legal)HumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Abstract A large portion of the research carried out in the digital humanities has an online digital object (usually referred as a project) as one of its components. In turn, these online digital objects can be catalogued as distributed resources, which implies that the administrative control of information related to a topic may be spread across online resources and/or collections maintained by multiple scholars in different institutions. This administrative decentralization can lead to changes in content that are often unexpected by a researcher, which can be caused by different factors or circumstances. This reasoning led us to formulate the following question: When can online digital humanities projects be considered abandoned? In this article, we carry out a study on the persistence and average life span of online projects in the digital humanities. More specifically, we will elaborate on their reliance on distributed resources and methods for measuring their shelf life: the average length of time that a digital project can endure without updates until it can ultimately be considered abandoned by its researcher.

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)0.015
metaresearch head score (Gemma)0.104
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.104
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.003
Science and technology studies0.0020.002
Scholarly communication0.0050.005
Open science0.0020.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.138
GPT teacher head0.278
Teacher spread0.140 · 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 designObservational
DomainEvaluation
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

Citations0
Published2018
Admission routes1
Has abstractyes

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