Children's Rights in an Age of Information and Communication Technologies
Bibliographic record
Abstract
We live in a socio-cultural, informational and technological context that poses new educational challenges for society in general but above all for children. In this paper, we present a proposal that should help to maximise the capacity of children to face the challenges presented by today’s society. We draw attention to the fact that in an age of information technology such as ours, children as a group risk marginalization. The children’s bill of rights in the XXI century needs to build on those drawn up in the XX century and should be extended to include those rights that safeguard life styles and living conditions and a child’s right to play and learn, in keeping with the specific conditions of the XXI century. To this end, we frame a proposal concerning the rights of children in a society increasingly dominated by information and communication technologies. Throughout Europe, there is much current debate about children’s rights linked with mass media and information and communication technologies. We describe several projects that offer hope for the promotion of greater responsibility on the part of the mass media given their pervasive ability to shape thinking, projects that may help to mitigate the influence of the media, including information and communication technologies on children.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.028 |
| Scholarly communication | 0.008 | 0.015 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".