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Record W4404293164 · doi:10.5860/dttp.v52i3.8343

Visualizing the International Government Information Collection at University of Illinois in Urbana-Champaign

2024· article· en· W4404293164 on OpenAlexaboutno aff
Uyen Nguyen

Bibliographic record

VenueDttP Documents to the People · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicE-Government and Public Services
Canadian institutionsnot available
Fundersnot available
KeywordsLibrary scienceGovernment (linguistics)Regional sciencePolitical sciencePublic administrationData scienceMedia studiesSociologyComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

The University of Illinois at Urbana-Champaign (UIUC) has been a Federal Depository Library Program (FDLP) Library since 1907. Over the course of time, the Library has amassed one of the largest collections of government information with materials covering areas of agriculture, education, the environment, health, natural resources, and transportation.1 In addition to federal and state publications in the United States, the Library also possesses an impressive collection of international government publications. The University Library became a United Nations depository in 1946 and Canadian depository in 1927, along with an extensive collection of British government resources.2 The collection not only serves as a preservation of original documents from international agencies and governments for research, but also represents the diversity of the library collection and history at UIUC. While there have been many efforts to promote and focus on the federal information collection, the international government collection can be explored more to enhance visibility and usage of the materials.

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)0.002
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.198
Threshold uncertainty score0.393

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0110.022
Science and technology studies0.0030.001
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0590.013

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 head0.009
GPT teacher head0.260
Teacher spread0.251 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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