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Record W1822508077 · doi:10.1080/01639374.2015.1044632

Socially Responsive Design and Evaluation of a Workers’ Compensation Thesaurus for a Community Organization with Selective Application of Cognitive Work Analysis: A Case Study

2015· article· en· W1822508077 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

VenueCataloging & Classification Quarterly · 2015
Typearticle
Languageen
FieldPsychology
TopicCompetency Development and Evaluation
Canadian institutionsCanada Auto WorkersUniversity of Toronto
Fundersnot available
KeywordsThesaurusTerminologyRelevance (law)Context (archaeology)Computer scienceWork (physics)Knowledge managementCognitionKnowledge organizationPsychologyArtificial intelligenceEngineeringPolitical scienceLinguistics

Abstract

fetched live from OpenAlex

This article presents a case study of the evaluation of social responsiveness and relevance of terminology used in a specialized thesaurus constructed for a community legal clinic library. The thesaurus is intended to assist in meeting information discovery and educational needs of a small organization that advocates on behalf of injured workers for legal and social justice within Ontario's workers’ compensation system. The authors include an overview of the thesaurus project and the historical context of workers’ compensation. They discuss the use of Cognitive Work Analysis as an evaluation methodology particularly appropriate to both the material and the clinic's culture of collaboration, with examples of its application in practice and some lessons learned.

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)0.005
metaresearch head score (Gemma)0.001
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 score0.357
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.172
GPT teacher head0.386
Teacher spread0.215 · 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