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Record W2074256768 · doi:10.1145/333329.333332

The UI design process

2000· article· en· W2074256768 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

VenueACM SIGCHI Bulletin · 2000
Typearticle
Languageen
FieldComputer Science
TopicUsability and User Interface Design
Canadian institutionsIBM (Canada)
Fundersnot available
KeywordsProcess (computing)Plan (archaeology)Computer scienceFocus (optics)User interfaceWork (physics)Engineering design processDesign processHuman–computer interactionWorld Wide WebWork in processEngineeringOperations management

Abstract

fetched live from OpenAlex

The root cause of many user interface (UI) design deficiencies is not a lack of knowledge about human-computer interaction principles nor a lack of information on user needs. Rather, many UI deficiencies arise because the UI design process is ad hoc and the design is not communicated successfully to the programmers who will implement it. Many UI designers are seeking and discovering ways to plan, manage, and document UI design work more effectively. This workshop provided an opportunity for participants to share lessons learned and obtain advice from other participants.In the weeks leading up to the workshop, participants selected the specific topics that were of prime concern to them. As a result, we narrowed the focus of the workshop to the following topics:• Division of UI design activities into stages• Division of labor and interdisciplinary collaboration• Collaborating in geographically-dispersed projects• Writing the UI specification• Defining the maturity of the UI design process.The following sections summarize the results of the workshop activities for each of these topics.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.799
Threshold uncertainty score0.997

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 communication0.0000.000
Open science0.0030.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.004

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 head0.025
GPT teacher head0.255
Teacher spread0.230 · 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