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Record W4245198856 · doi:10.29085/9781783302086.002

Foreword to the second edition

2018· book-chapter· en· W4245198856 on OpenAlexvenueno aff
Geoffrey Yeo

Bibliographic record

VenueArchives · 2018
Typebook-chapter
Languageen
FieldArts and Humanities
TopicDigital and Traditional Archives Management
Canadian institutionsnot available
Fundersnot available
KeywordsBalance (ability)Face (sociological concept)HistoryPolitical scienceSociologyPsychologySocial science

Abstract

fetched live from OpenAlex

Seven years after Laura Millar's eloquent and wide-ranging book was first published, it is ever more apparent that in future the great majority of records will be created and used in digital form. At present, most record-making environments are hybrid – to varying extents, paper records continue to be created and kept alongside their digital counterparts – but the balance is firmly shifting towards the digital. Organizations are now disposing of their filing cabinets at an unprecedented rate. Even if the wholly paperless office may still prove to be a chimera, the ‘less-paper’ office is now a visible reality. It has also become clear that archivists will very soon face, if they are not already facing, a digital deluge. The world is creating massive amounts of digital content, and the archivists of the future will encounter quantities of records that exceed anything that archivists have experienced in the past. In this age of digital abundance, human society will still look for evidence of, and information about, actions that have been undertaken, events that have occurred, decisions that have been made, and rights that have been protected, abused or amended. Records and archives will still be needed, and the long-standing archival principles that Millar expounds will be no less valid, but the methods and techniques required to put those principles into practice will often be very different. In this new and extensively revised second edition, Millar provides greatly expanded coverage of digital concerns. In place of the separate chapter on digital archives that concluded the first edition, discussion of digital issues is now woven into every chapter of the book. Of course, we still have – and will continue to have – the legacy of many centuries of archives created using paper and other analogue media; the skills to manage records created in the past by non-digital means will remain essential, and Millar does not neglect them. But in recasting her book to take account of the fast-moving digital revolution, she offers us an archival manual for the twenty-first century.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.444
Threshold uncertainty score0.793

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0060.005
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.4440.360

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 head0.028
GPT teacher head0.190
Teacher spread0.161 · 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 designNot applicable
Domainnot available
GenreEditorial

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
Published2018
Admission routes1
Has abstractyes

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