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Identifying Resources: FRBR and Accessibility

2017· article· en· W2749941844 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.

Bibliographic record

VenueScientific and Technical Libraries · 2017
Typearticle
Languageen
FieldComputer Science
TopicLibrary Science and Information Systems
Canadian institutionsUniversity of OttawaLibrary and Archives Canada
Fundersnot available
KeywordsMetadataStructuringResource (disambiguation)Computer scienceContext (archaeology)GlobeData scienceWorld Wide WebConceptual modelGeographyPsychologyBusinessDatabase

Abstract

fetched live from OpenAlex

This paper will outline some of the key aspects of the FRBR family of conceptual models that support resource discovery especially for persons who are blind, visually impaired, or otherwise print disabled. The FRBR family of models have had a significant influence on the ways in which communities around the globe perceive and understand the bibliographic universe. This paper will focus on two areas where the conceptual models have had an important impact: bibliographic information as data and the precise delineation between content and carrier. The paper focuses on these two areas because they are of particular interest for a user with a print disability who approaches the task of discovering an appropriate resource. FRBR modeling, as expressed in the original models or in the new consolidated model, FRBR-LRM, offers a roadmap for structuring metadata in ways that allow more options for resource discovery in an increasingly global context.

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 categoriesScience and technology studies, Scholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0190.021
Open science0.0020.002
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 head0.042
GPT teacher head0.273
Teacher spread0.231 · 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