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Record W2004752787 · doi:10.1080/14733280701791827

Ethics in child research: rights, reason and responsibilities

2008· article· en· W2004752787 on OpenAlexfundno aff
Nancy M. Bell

Bibliographic record

VenueChildren s Geographies · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsnot available
FundersMedical Research Council CanadaUniversity of GlasgowJohns Hopkins University
KeywordsHuman rightsEngineering ethicsResearch ethicsPolitical scienceConventionPerspective (graphical)Convention on the Rights of the ChildLawSociologyEnvironmental ethicsPhilosophyComputer science

Abstract

fetched live from OpenAlex

This paper explores the nature of the relationship between research ethics and children's rights by examining the historical origins of both concepts and then analysing several contemporary research ethics guidelines from a rights-based perspective. The analysis demonstrates that while many research ethics guidelines may contain references to human rights principles, implicit or otherwise, there is often a lack definition about what is meant by ‘rights’ and about the correlation between human rights principles and research ethics in practice. Within social sciences research, in particular, research ethics guidelines, including those guidelines specific to child research, noticeably lack direct reference to human rights principles such as those articulated within the UN Convention on the Rights of the Child (UNCRC). The paper argues that as child researchers do not stand apart from their obligations to protect and promote children's rights, research ethics guidelines relied upon by child researchers need to be informed by human rights principles and that those researchers may draw upon the UNCRC, in particular, to inform their consideration of inevitable ethical dilemmas arising within child research.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.092
metaresearch head score (Gemma)0.081
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.092
Threshold uncertainty score0.488

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0920.081
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0090.113
Scholarly communication0.0160.016
Open science0.0020.013
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.122
GPT teacher head0.387
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), 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

Citations109
Published2008
Admission routes1
Has abstractyes

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