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Record W4411558420 · doi:10.1145/3713043.3734470

Pushing the Boundaries of Computational Empowerment of Children

2025· article· en· W4411558420 on OpenAlexaff
Netta Iivari, Ole Sejer Iversen, Yasmin B. Kafai, Alissa N. Antle, Marianne Graves Petersen, Marianne Kinnula, Christian Dindler, Fares Kayali, Elizabeth Bonsignore, Charu Monga, Marie-Monique Schaper, Sumita Sharma

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsComputer scienceEmpowermentHuman–computer interactionPolitical science

Abstract

fetched live from OpenAlex

Emerging technologies such as artificial intelligence (AI) and mixed reality (MR) increasingly pervade the world of children, from their schoolwork to leisure activities and social relationships. This has led to Child Computer Interaction (CCI) research supporting children's critical understanding of digital technologies and their ability to influence the design of future digital technologies. Despite these efforts, there are several limitations and challenges in terms of Computational Empowerment (CE) of children. This workshop unites such research 1) to create a shared manifesto for CE of children and 2) to jointly develop a research ‘roadmap’ to push the boundaries of CE of children.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.661
Threshold uncertainty score0.126

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 communication0.0000.000
Open science0.0000.000
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 head0.008
GPT teacher head0.276
Teacher spread0.268 · 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 designTheoretical or conceptual
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

Citations5
Published2025
Admission routes1
Has abstractyes

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