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Record W3214699411 · doi:10.29085/9781783302086.009

Types of archival institution

2018· book-chapter· en· W3214699411 on OpenAlexvenueno aff
Laura Millar

Bibliographic record

VenueArchives · 2018
Typebook-chapter
Languageen
FieldArts and Humanities
TopicDigital and Traditional Archives Management
Canadian institutionsnot available
Fundersnot available
KeywordsInstitutionConventionDemocracyState (computer science)Political sciencePublic administrationLibrary scienceLawGenealogyHistoryPoliticsComputer science

Abstract

fetched live from OpenAlex

Wise and prudent men have long known that in a changing world worthy institutions can be conserved only by adjusting them to the changing time. Franklin D. Roosevelt (1882–1945) Address at the Democratic State Convention, Syracuse, New York, 29 September 1936 Today, archival institutions can be found in virtually every corner of the world, from governments, universities, corporations and clubs to historical societies, religious organizations, political groups and co-operatives. There are over 1000 self-proclaimed archival institutions in Canada, thousands in the USA and countless more around the globe. These institutions have been established to serve the needs of their society, and they are governed by the laws, cultures and priorities of that society. Too often, archivists attempt to categorize archival institutions in relation to administrative placement rather than scope of service. For example, archivists might distinguish between church archives, government archives and university archives. But this approach does not account for the fact that one government archives might only manage the records of that government, while another government archives might also acquire private papers, or that one university archives cares only for its institutional records while another university archives has a broad responsibility for acquiring and preserving manuscripts and special collections. Ultimately, archival institutions will always represent whatever their society decides they should represent. Therefore, a more useful way to understand the different ‘types’ of institution that might exist in different societies is to focus on the services they might provide rather than on the adjective attached to the name: church archives versus special collections department versus business archives. A distinction can be made at the start between those institutions that manage only the archives of the sponsor agency itself and those that acquire and manage non-sponsor archives (private and personal papers, the archives of other corporations or associations and so on). In practice these two services often merge and overlap; rarely can an archival institution claim it focuses on one duty to the exclusion of the other.

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)0.007
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: Other · Consensus signal: Other
Teacher disagreement score0.035
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0060.006
Science and technology studies0.0040.010
Scholarly communication0.0180.019
Open science0.0020.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0350.009

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 head0.034
GPT teacher head0.195
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.

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
Published2018
Admission routes1
Has abstractyes

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