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Record W2300251258 · doi:10.3828/comma.2014.18

‘Plus c’est la même chose’: Surveying and identifying local government archives repositories in the United States and Canada

2015· article· en· W2300251258 on OpenAlexaboutno aff
David A. Evans, John H. Slate

Bibliographic record

VenueComma · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicDigital and Traditional Archives Management
Canadian institutionsnot available
Fundersnot available
KeywordsSafeguardingLocal governmentNational archivesState (computer science)Government (linguistics)Public administrationPolitical scienceLibrary scienceSnapshot (computer storage)LawDatabase

Abstract

fetched live from OpenAlex

The safeguarding of the permanent and historical records of local, municipal and territorial archives is a daunting challenge to governments, regardless of size. Proper environmental control, storage and security, and loss or alienation through theft and disaster are all important concerns each entity must address. The Local Government Records Round Table and the Government Records Section of the Society of American Archivists conducted a survey of local government archives in the United States and Canada in the autumn of 2014 to take a snapshot of the status of local government archives. The last survey of this nature was conducted in 1976 by the State and Local Records Committee of the Society of American Archivists. The survey instrument, in English, Spanish, and French, was designed to help better understand the location, needs, uses and best practices associated with local government archival records. It was created with the knowledge that the guardians of historic local records are important, whether they are held by a government, library, or historical organisation.

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)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.465

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.012
Science and technology studies0.0120.003
Scholarly communication0.0050.002
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.043
GPT teacher head0.211
Teacher spread0.168 · 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 designObservational
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
Published2015
Admission routes1
Has abstractyes

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