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Record W2551282186 · doi:10.1145/2987592.2987608

Arguing about design

2016· article· en· W2551282186 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsnot available
Fundersnot available
KeywordsRhetorical questionMetisSituatedNormativeContext (archaeology)NegotiationUser experience designComputer scienceBridge (graph theory)Taxonomy (biology)SociologyHuman–computer interactionEpistemologyLinguisticsWorld Wide WebArtificial intelligence

Abstract

fetched live from OpenAlex

The design of technology occurs in a rich, nuanced and complex rhetorical space. Technical teams engage in negotiations, and at times argue, about design. We claim that user experience (UX) practice, at its heart, is a rhetorical endeavor, and this aspect of UX practice has been underexplored. To bridge the gap between UX theory and practice, we pose the research question: What strategies and tactics do UX practitioners use to convince or persuade others about design? To answer this question, we interviewed experienced UX practitioners and present the results of these interviews as a taxonomy of rhetorical strategies situated by an awareness of rhetorical complexity and the impact of context. The results of the study demonstrate that normative UX methods and practices discussed in the literature are chosen, adapted or dismissed as savvy rhetors flex their metis.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.807
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.035
GPT teacher head0.268
Teacher spread0.234 · 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

Quick stats

Citations19
Published2016
Admission routes1
Has abstractyes

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