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Record W2885645832 · doi:10.1108/lm-10-2017-0107

Testing, testing: a usability case study at University of Toronto Scarborough Library

2018· article· en· W2885645832 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

VenueLibrary Management · 2018
Typearticle
Languageen
FieldComputer Science
TopicUsability and User Interface Design
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsUsabilityComputer scienceCard sortingWorld Wide WebDigital libraryOriginalityKey (lock)Web usabilityTask (project management)Heuristic evaluationCognitive walkthroughQualitative researchHuman–computer interactionEngineeringSystems engineering

Abstract

fetched live from OpenAlex

Purpose With the rise of virtual library users and a steady increase in digital content, it is imperative that libraries build websites that provide seamless access to key resources and services. The paper aims to discuss these issues. Design/methodology/approach Usability testing is a valuable method for measuring user habits and expectations, as well as identifying problematic areas for improvement within a website. Findings In this paper, the authors provide an overview of user experience research carried out on the University of Toronto Scarborough Library website using a mixture of qualitative and quantitative research methods and detail insights gained from subsequent data analysis. Originality/value In particular, the authors discuss methods used for task-oriented usability testing and card sorting procedures using pages from the library website. Widely applicable results from this study include key findings and lessons learned from conducting usability testing in order to improve library websites.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.845

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.004
Open science0.0010.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.233
Teacher spread0.191 · 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