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Record W1517640044

MACNEIL, Trusting Records: Legal, Historical and Diplomatic Perspectives

2002· article· en· W1517640044 on OpenAlexvenueno aff
Livia Iacovino

Bibliographic record

VenueArchivaria · 2002
Typearticle
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceLawHistory
DOInot available

Abstract

fetched live from OpenAlex

A professional community must have a solid conceptual foundation on which to build its practices.For at least a decade, the archival community has been concerned with the nature and preservation of trustworthy electronic records.From the viewpoint of law, history, and diplomatics, Trusting Records: Legal, Historical, and Diplomatic Perspectives provides an interdisciplinary analysis of record trustworthiness, which is a foundational archival concept, and one of continuing relevance to the electronic environment.Each discipline is also studied in relation to its assumptions about records as evidence.The author, Heather MacNeil, is an Assistant Professor at the School of Library, Archival and Information Studies of the University of British Columbia, a colleague and co-researcher with Luciana Duranti, and a leading interpreter of diplomatics in Canada

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)0.012
metaresearch head score (Gemma)0.035
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: Empirical · Consensus signal: none
Teacher disagreement score0.049
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.035
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.005
Science and technology studies0.0270.060
Scholarly communication0.0370.027
Open science0.0030.007
Research integrity0.0180.011
Insufficient payload (model declined to judge)0.0120.001

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 head0.041
GPT teacher head0.225
Teacher spread0.184 · 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
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
Published2002
Admission routes1
Has abstractno

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