Panel: Broadening the Discussion of Ethics in the Interaction Design and Children Community
Bibliographic record
Abstract
Interaction Design and Children (IDC) as an academic field, and as a community, has a responsibility to engage with the many and diverse ethical challenges that arise from work that concerns the creation of digital technology for and with children – both in terms of research and industry contexts. This panel builds on a short history of similar events at previous conferences and aims to foster and strengthen the debate about ethical conduct and moral responsibilities in IDC. In this year’s panel, we seek to broaden the discussion by collecting ethical concerns, issues or dilemmas from within the community to be discussed at the conference. To this end, we will issue an open call for input that will be publicised via the usual channels. The organisers then will synthesise the responses and facilitate the discussion and debate at the panel.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.018 | 0.025 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".