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Record W2899577025 · doi:10.32920/ryerson.14637102

Author identifier analysis: Name authority control in two institutional repositories

2021· article· en· W2899577025 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicLibrary Science and Information Systems
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAuthority controlIdentifierScopusMetadataInstitutionWorld Wide WebLibrary scienceControl (management)Political scienceDatabaseComputer scienceLawMEDLINE

Abstract

fetched live from OpenAlex

The aim of this poster is to analyze name authority control in two institutional repositories to determine the extent to which faculty researchers are represented in researcher identifier databases. A purposive sample of 50 faculty authors from Florida Southern College (FSC) and Ryerson University (RU) were compared against five different authority databases: Library of Congress Name Authority File (LCNAF), Scopus, Open Researcher and Contributor ID (ORCID), Virtual International Authority File (VIAF), and International Standard Name Identifier (ISNI). We first analyzed the results locally, then compared them between the two institutions. The findings show that while LCNAF and Scopus results are comparable between the two institutions, the difference in the ORCID, VIAF, and ISNI are considerable. Additionally, the results show that the majority of authors at each institution are represented in two or three external databases. This has implications for enhancing local authority data by linking to external identifier authority data to augment institutional repository metadata.

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.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.941
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0010.007
Open science0.0010.000
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 head0.017
GPT teacher head0.280
Teacher spread0.263 · 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

Quick stats

Citations6
Published2021
Admission routes2
Has abstractyes

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