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Record W4396978236 · doi:10.32920/25560546.v1

Digital Humanities as Memory Work: Memory Eternal as a Virtual Site of Mourning

2024· preprint· en· W4396978236 on OpenAlexaboutno aff
Jolene Armstrong, Angela Joosse, Siobhan O'Flynn, Monique Tschofen

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicDigital Humanities and Scholarship
Canadian institutionsnot available
Fundersnot available
KeywordsDigital humanitiesWork (physics)Memory workHumanitiesArtComputer scienceArt historyCognitive sciencePsychologyPhilosophyEpistemologyEngineering

Abstract

fetched live from OpenAlex

Named for the Ukrainian Orthodox prayer for the dead, the Canadian feminist Decameron Collective's Memory Eternal | Вічная Пам'ять explores trauma and remembrance. Designed for the Oculus Quest 2, this feminist digital sandbox storytelling project by a group of nine women scholars from Canada reflects on grief at the personal and collective scales, elaborating on the losses of the pandemic and war. In a 7 minute video, our project showcase will explore the work’s forms and themes, providing an overview of the seventeen works which populate the digital space, and will contextualize it within overlapping frames of Digital Humanities and research creation, e-literature, and interactive documentary.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.019
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0140.025
Scholarly communication0.0190.010
Open science0.0010.013
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0180.001

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 head0.051
GPT teacher head0.245
Teacher spread0.194 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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