MétaCan
Menu
Back to cohort
Record W2612305863 · doi:10.5555/3076132.3076163

Icons for Kids: Can Young Children Understand Graphical Representations of App Store Categories?

2016· article· en· W2612305863 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

VenueGraphics Interface · 2016
Typearticle
Languageen
FieldComputer Science
TopicUsability and User Interface Design
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsComputer scienceSet (abstract data type)ImplementationGraphical user interfacePoint (geometry)Human–computer interactionApp storeWorld Wide WebProgramming languageMathematics

Abstract

fetched live from OpenAlex

This paper proposes the use of graphical representations - colloquially referred to as - of app-store program categories and provides evidence via a user study that these icons can be understood by young children (aged 4-8). Given the rapid growth of this user base, providing such graphical representations is important to aid young children in navigating (under usual parental supervision) and understanding the large number of apps available. This work further provides an initial set of candidate graphical representations that have been evaluated with children, which serve as a starting point for future implementations and exploration.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.835
Threshold uncertainty score0.693

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 studies0.0000.001
Scholarly communication0.0000.000
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 head0.032
GPT teacher head0.290
Teacher spread0.258 · 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