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Record W4404670578 · doi:10.1093/hwj/dbae029

Archivists and historians: Alan Betteridge (1942–2024)

2024· article· en· W4404670578 on OpenAlexaboutno aff
Jill Liddington

Bibliographic record

VenueHistory Workshop Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIrish and British Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLibrary scienceHistoryArtClassicsArt historyComputer science

Abstract

fetched live from OpenAlex

Dr Alan Betteridge, who died on 7 July 2024, developed extraordinarily wide intellectual interests. The philosophy he lived by was rooted in three traditions: existentialism, ecology and humanism; and his funeral, held on 28 July, was conducted beautifully by a humanist celebrant – just as Alan would have wanted. As the Halifax Archivist, Alan brought to this post both his deep knowledge of West Yorkshire history and up-to-date professional policies and practices. I worked with Alan in many contexts. But probably his greatest contribution for me was his conservation of the Anne Lister diaries (1791–1840), stored within the extensive Shibden Hall papers. Her journals came to international attention and acclaim in 2019 with Sally Wainwright’s TV drama series ‘Gentleman Jack’ (BBC1/HBO). Alan had an impressively mobile academic journey. He was born on 1 November 1942 in the West Yorkshire pit village of Ferry Fryston. His father, a jazz drummer, left the family during Alan’s childhood. An only child, he was brought up by his mother. Always quietly studious, Alan went from grammar school to King’s College London, where he studied French and German. After two years in Germany and a spell teaching in a secondary modern school in Wakefield, he decided it would suit him better to do a postgraduate degree in librarianship at Leeds University.

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)0.003
metaresearch head score (Gemma)0.008
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.080
Threshold uncertainty score0.267

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0050.003
Scholarly communication0.0070.006
Open science0.0010.007
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0800.041

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 head0.027
GPT teacher head0.285
Teacher spread0.258 · 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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Same venueHistory Workshop JournalSame topicIrish and British StudiesFrench-language works237,207