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Record W4400991906 · doi:10.69554/duhs3211

Delivering a consistent user experience through our faculty sites: For our audiences and our internal web users

2019· article· en· W4400991906 on OpenAlexaff
Anju Visen-Singh

Bibliographic record

VenueJournal of education advancement & marketing. · 2019
Typearticle
Languageen
FieldComputer Science
TopicWeb and Library Services
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsWorld Wide WebUser experience designComputer scienceInternet privacyHuman–computer interaction

Abstract

fetched live from OpenAlex

This paper provides insights into building a user-first responsive web system that delivers a superior and consistent user experience across all faculty websites1, in collaboration with faculties as well as IT colleagues. Fulfilling this objective can be a nontrivial challenge in higher education institutions where haphazard development of websites creates many ‘monsters’ making it painful, if not impossible, to revamp the family of websites. Here, we share UCalgary’s journey of moving to a collaborative, systembased approach for our faculty websites that enables the uniqueness of each faculty to come through while providing a consistent user experience across all sites. Our ‘system’ includes not just the web platform but a full offering of support, best practices and measurement.

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 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
Threshold uncertainty score0.592

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 studies0.0000.000
Scholarly communication0.0000.003
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 head0.027
GPT teacher head0.324
Teacher spread0.297 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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