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Record W2610722457 · doi:10.1145/3025453.3025908

Designing Cultural Values into Interaction

2017· article· en· W2610722457 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of British ColumbiaSimon Fraser University
Fundersnot available
KeywordsInterdependenceInteraction designCultural heritageComputer scienceNarrativeProcess (computing)Human–computer interactionValue (mathematics)Table (database)Design processUser experience designKnowledge managementSociologyEngineeringWork in process

Abstract

fetched live from OpenAlex

In this paper, we highlight possibilities for designing intangible cultural values into interactions with technologies in heritage spaces. We do this specifically through the design of elwkw -- Belongings, an interactive tangible table installed in a cultural heritage museum. The tabletop was collaboratively designed to communicate complex and narrative information and values about Musqueam culture. Rather than focusing only on content and interface design, we wanted visitors to also experience Musqueam values through their interactions with the system. We describe our value-sensitive design process, present five interdependent design goals, discuss the design strategies that enabled us to meet these goals, and evaluate our approach through a user study. From our design process and evaluation we offer recommendations for designing values into interactions more generally and for tangible interactions specifically in ways that support visitors' experience and understanding of specific cultural values through technology.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.744
Threshold uncertainty score0.575

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 studies0.0010.000
Scholarly communication0.0010.004
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 head0.056
GPT teacher head0.365
Teacher spread0.309 · 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

Citations48
Published2017
Admission routes1
Has abstractyes

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