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Record W4213008652 · doi:10.1007/s10502-021-09384-x

Digital critical archives, copyright, and feminist praxis

2022· article· en· W4213008652 on OpenAlexaff
Nicola Wilson, Claire Battershill, Helena Clarkson, Matthew Hannah, Illya Nokhrin, Elizabeth Willson Gordon

Bibliographic record

VenueArchival Science · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicDigital and Traditional Archives Management
Canadian institutionsThe King's UniversityUniversity of Toronto
FundersArts and Humanities Research CouncilUniversity of Reading
KeywordsEthosMetadataSociologyPraxisPublishingPoliticsCultural heritageCitizen journalismCritical theoryCustodiansWorld Wide WebPolitical scienceComputer scienceHistoryLaw

Abstract

fetched live from OpenAlex

Abstract With the continued proliferation of digitized materials, critical attention to the ideologies informing the creation of digital archives remains crucial. How are digital archives made and what are their goals? How do different participants in the process work together in collaborative teams towards shared ideals? This paper outlines the methodological and political considerations that underlie the creation of a critical digital archive of historical and born-digital materials relating to 20th-century publishing history,The Modernist Archives Publishing Project(MAPP). Here we outline the archival practices and critical ethos that have informed the collaborative creation ofMAPPby an international team of scholars, archivists, cultural institutions, students, and copyright estate holders. We address issues of selection that arise in creating a critical digital archive; feminist critical metadata practices; and our approaches to workflow and copyright; and conclude with an example of an archival document type in which the issues of feminist critical curation and copyright collide.

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)0.023
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.004
Science and technology studies0.0160.084
Scholarly communication0.0220.019
Open science0.0020.010
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0070.000

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 head0.020
GPT teacher head0.225
Teacher spread0.205 · 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 designTheoretical or conceptual
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
Published2022
Admission routes1
Has abstractyes

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