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Record W2885223282 · doi:10.16995/dm.78

On Not Writing a Review about Mirador: Mirador, IIIF, and the Epistemological Gains of Distributed Digital Scholarly Resources

2018· review· en· W2885223282 on OpenAlexvenueno aff
Joris van Zundert

Bibliographic record

VenueDigital Medievalist · 2018
Typereview
Languageen
FieldArts and Humanities
TopicDigital Humanities and Scholarship
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipContext (archaeology)Simple (philosophy)Computer scienceRealmEpistemologyPhilosophyHistoryPolitical science

Abstract

fetched live from OpenAlex

This piece mushroomed from a simple enough looking suggestion to write a review about Mirador, a viewer component for web based image resources. While playing around and testing Mirador however, a lot of questions started to emerge–questions that in a scholarly sense were more significant than just the functional requirements of textual scholars and researchers of medieval sources for an image viewer. These questions are forced upon us because of the way Mirador is built, and by the assumptions it thereby makes–or that its developers make–about its role and about the larger infrastructure for scholarly resources that it is supposed to be a part of. This again led to a number of epistemological issues in the realm of digital textual scholarship. And so, what was intended as a simple review resulted in a long read about Mirador, about its technological context, and about digital scholarly editions as distributed resources. The first part of my story gives a straightforward review-like overview of Mirador. I then delve into the reasons that I think exist for the architectural nature of the majority of current digital scholarly editions, which are still mostly monolithic data silos. This in turn leads to some epistemological questions about digital scholarly editions. Subsequently I return to Mirador to investigate whether its architectural assumptions provide an answer to these epistemological issues. To estimate whether the epistemological “promise” that Mirador’s architecture holds may be easily attained, I gauge what (technical) effort is associated with building a digital edition that actually utilizes Mirador. Integrating Mirador also implies adopting the emerging standard IIIF (international image interoperability framework); a discussion of this “standard-to-be” is therefore in order. Finally the article considers the prospects of aligning the IIIF and TEI “standards” to further the creation of distributed digital scholarly editions.

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)0.026
metaresearch head score (Gemma)0.159
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: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.159
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.007
Science and technology studies0.0020.004
Scholarly communication0.0090.012
Open science0.0020.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.004

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 head0.117
GPT teacher head0.313
Teacher spread0.196 · 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
GenreReview

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

Citations19
Published2018
Admission routes1
Has abstractyes

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