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Record W1563959292

Economic Impact of Government Archives

2012· article· en· W1563959292 on OpenAlexaboutno aff
Elizabeth Yakel

Bibliographic record

VenueJournal of Korean Society of Archives and Records Management · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Economic impact analysisValue (mathematics)Work (physics)National archivesPolitical scienceLocal governmentState (computer science)PropositionValue propositionBusinessPublic administrationPublic relationsMarketingEconomicsLawEngineering
DOInot available

Abstract

fetched live from OpenAlex

Economic impact analyses have not been widely conducted in archives. This article reports on a two parallel surveys in the US and Canada to assess the economic impact of government archives (state, provincial, territorial, county, and municipal). The surveys utilize indirect measures of economic impact. Responses from 2,534 people in 66 archives were analyzed. Findings indicate that archives were the primary reason that respondents visited an area and that visitors exhibit specific patterns of visiting the archives in conjunction with other cultural organizations in an area. Furthermore, while many respondents used local eateries, fewer rented lodgings or spent money on theater or sporting events. As a result, the archives participating in this survey did have a modest impact on local economies. The article concludes by discussing three major questions about the evaluation of the economic impact of archives which were raised by the findings: 1) Are indirect measures the most appropriate means of assessing economic impact in archives or should archives employ direct measures as used by public libraries? 2) How should government archives formulate their value proposition and should those value propositions focus on other aspects of archives’ impact, such as the social impact, to demonstrate archives’ important role in society? and 3) Since visitors exhibited distinct visitation patterns, should archives work more with these other aligned organizations and work on larger forms of collective impact that benefit the entire cultural heritage sector in an area?

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.479
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.280
Teacher spread0.261 · 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 teacher head, 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

Citations2
Published2012
Admission routes1
Has abstractyes

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