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Record W4408888496 · doi:10.16995/dscn.11108

Remediation and Spectral Bibliography: Ghost Hunting in Early Modern Books

2025· article· en· W4408888496 on OpenAlexvenueno aff

Bibliographic record

VenueDigital Studies / Le champ numérique · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIntellectual Property Law
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This paper explores the layers of remediation and hidden labour embedded in the digitization of early modern texts, focusing on how metadata traces in digital archives can both reveal and obscure the material history of books. Using a bibliographic workflow, this study examines the challenges of distinguishing between material artifacts of the original printing process and distortions introduced through digitization. Through a case study of Thomas May’s The Tragedie of Cleopatra, I analyze metadata from the English Short Title Catalogue (ESTC) and Internet Archive, alongside correspondence with archivists, to reconstruct the provenance and digitization history of the text. I thus contend that the digitization of early modern texts introduces ambiguities: digital anomalies that can obscure or distort the material history of these works, thereby challenging the reliability of digital surrogates for historical inquiry. This research highlights the stakes of providing scholars with opportunities for in-person archival study, particularly in cases where digital surrogates present anomalies that resist easy categorization. These stakes are especially high for scholars relying on digital scans to conduct research, as addressing these uncertainties requires innovation in digitization processes, and sustained investment in methodologies that bridge the gap between digital and physical archives, ensuring the reliability of digital surrogates for historical inquiry. Cet article examine les strates de remédiation et le travail invisible impliqués dans la numérisation des textes de la première modernité, en s’attachant à la manière dont les traces de métadonnées dans les archives numériques peuvent à la fois révéler et masquer l’histoire matérielle des livres. En mobilisant un protocole bibliographique, cette étude analyse les difficultés à distinguer les artefacts matériels issus du processus d’impression d’origine des altérations induites par la numérisation. À travers une étude de cas portant sur The Tragedie of Cleopatra de Thomas May, j’analyse les métadonnées issues du English Short Title Catalogue (ESTC) et de l’Internet Archive, ainsi que des échanges avec des archivistes, pour reconstruire la provenance et l’histoire de la numérisation du texte. Je soutiens ainsi que la numérisation des textes anciens introduit des ambiguïtés : des anomalies numériques susceptibles d’obscurcir ou de déformer l’histoire matérielle de ces œuvres, remettant en cause la fiabilité des substituts numériques dans la recherche historique. Cette recherche souligne l’importance de garantir aux chercheurs un accès physique aux archives, en particulier lorsque les substituts numériques présentent des anomalies difficiles à classer. Ces enjeux sont d’autant plus cruciaux pour les chercheurs dépendant des scans numériques, car surmonter ces incertitudes exige à la fois des innovations dans les processus de numérisation et un investissement durable dans des méthodologies capables de relier archives physiques et numériques, afin d’assurer la fiabilité des substituts numériques dans la recherche historique.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.289
Teacher spread0.260 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2025
Admission routes1
Has abstractyes

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