The challenges for children’s rights in international child protection: Opportunities for transformation
Bibliographic record
Abstract
Children’s rights highlight the priority of child protection internationally and require us to think about how protection is defined and conceptualised, whether protection efforts are working, and how we are carrying them out. Many scholars have noted the apparent conflict between the idea of children’s rights as universal and the particular realities of local contexts, understandings, and experiences. Some argue that the failures of child protection are due to the structure of the children's rights framework itself. However, we contend that the issues lie in traditional child protection systems and frameworks, and how children's rights are (or are not) understood and operationalised by child protection actors. Relying on a narrative literature review, this conceptual paper presents several examples in support of this view, and argues that more work needs to be done to contextualize and secure the rights of children in need of protection. We explore the complex interplay between local and global interpretations of rights and recommend that dialogue among actors with different perspectives and socio-cultural experiences of children’s rights will produce richer understandings and practices of them. This dialogue can support the transformation of the current international child protection system to support the ability of children, their families and caregivers to realise children’s rights and support their thriving.
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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 | 0.035 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.055 |
| Scholarly communication | 0.023 | 0.031 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.010 | 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".