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Record W2324614083 · doi:10.3167/hrrh.2011.370208

Archives, Heritage, and Communities

2011· article· en· W2324614083 on OpenAlexvenueno aff
Elizabeth C. Macknight

Bibliographic record

VenueHistorical Reflections/Réflexions Historiques · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicDigital and Traditional Archives Management
Canadian institutionsnot available
Fundersnot available
KeywordsInterpretation (philosophy)Value (mathematics)Archival scienceSociologyLibrary sciencePolitical scienceMedia studiesPublic relationsComputer science

Abstract

fetched live from OpenAlex

This article presents two case studies, from Scotland and the Scottish Islands, of communities' engagement with archives and their attitudes toward heritage. The case studies arise out of knowledge transfer between an historian employed in an academic role at a Scottish university and two “third sector“ organizations. By comparing the perspectives of historians, archivists, and community organizations the article shows the different ways in which these separate interest groups perceive the value of archives. It then points to some of the possibilities and challenges of working collaboratively to deepen understanding about the past and to create wider opportunities, now and in the future, for historical interpretation, teaching, learning, and research. In the era of digital technologies, it is recommended that undergraduate students be taught the key concepts of archival theory and practice, while also being encouraged to experience working with original archival documents.

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)0.004
metaresearch head score (Gemma)0.006
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: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0190.036
Scholarly communication0.0140.008
Open science0.0010.015
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.113
GPT teacher head0.250
Teacher spread0.137 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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