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Record W4289856131 · doi:10.1017/9781009026055

The Transformation of Historical Research in the Digital Age

2022· book· en· W4289856131 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCambridge University Press eBooks · 2022
Typebook
Languageen
FieldArts and Humanities
TopicDigital and Traditional Archives Management
Canadian institutionsUniversity of Waterloo
FundersUniversity of Cambridge
KeywordsWhirlwindDigital transformationWorkflowComparative historical researchWorld Wide WebDigital mediaDigital ArchivesHistoryDigital humanitiesWork (physics)Data scienceComputer scienceMedia studiesSociologySocial scienceEngineering

Abstract

fetched live from OpenAlex

Historians make research queries on Google, ProQuest, and the HathiTrust. They garner information from keyword searches, carried out across millions of documents, their research shaped by algorithms they rarely understand. Historians often then visit archives in whirlwind trips marked by thousands of digital photographs, subsequently explored on computer monitors from the comfort of their offices. They may then take to social media or other digital platforms, their work shaped through these new forms of pre- and post-publication review. Almost all aspects of the historian's research workflow have been transformed by digital technology. In other words, all historians – not just Digital Historians – are implicated in this shift. The Transformation of Historical Research in the Digital Age equips historians to be self-conscious practitioners by making these shifts explicit and exploring their long-term impact. This title is also available as Open Access on Cambridge Core.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.821
Threshold uncertainty score0.462

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.077
GPT teacher head0.216
Teacher spread0.139 · 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