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Record W3006755650 · doi:10.5070/g314342949

Do children want environmental rights? Ask the Children!

2019· article· en· W3006755650 on OpenAlexaff
Zen Makuch, Miriam R. Aczel, Sunya Zaman

Bibliographic record

VenueElectronic Green Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsUniversity of British Columbia
FundersImperial College London
KeywordsSafeguardingEnvironmental educationArgument (complex analysis)Rights of NaturePolitical scienceEnvironmental ethicsNatural (archaeology)SociologyHuman rightsPublic relationsFundamental rightsLawRight to propertyGeography

Abstract

fetched live from OpenAlex

In this paper, we argue for the importance of application and safeguarding of the ‘environmental rights of children,’ and further argue that an understanding of children’s perspectives towards nature and their rights to a viable and healthy environment can help both educational and policy development. To that end, we present a case study of preliminary qualitative research conducted in the United Kingdom that asks children themselves their views and degree of exposure to the natural environment. This research is underpinned by an environmental rights-based approach for environmental education, and a novel argument for incorporating children’s own understandings and perspectives in application of environmental rights. We conclude with recommendations for strengthening children’s environmental engagement, protection of rights, and education, and recognize that there is a need for further research to better understand children’s perspectives to their own environmental rights.

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)0.005
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.011
Scholarly communication0.0060.010
Open science0.0010.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0120.001

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 head0.006
GPT teacher head0.241
Teacher spread0.235 · 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 designQualitative
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

Citations4
Published2019
Admission routes1
Has abstractyes

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