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Record W2099643241 · doi:10.1080/00094056.2015.1090845

Early Childhood Education and Sustainability: A Living Curriculum

2015· article· en· W2099643241 on OpenAlexaff
Margaret MacDonald

Bibliographic record

VenueChildhood Education · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsSustainabilityOverpopulationSustainable developmentEducation for sustainable developmentSustainable livingEnvironmental ethicsCurriculumEconomic growthPolitical scienceFood securityGlobal citizenshipEnvironmental educationPublic relationsSociologyEconomicsPopulationLawGeographyEcologyAgriculture

Abstract

fetched live from OpenAlex

As climate change, overpopulation, and inequalities begin to take their toll on our planet and on global human development, sustainability has become increasingly important for a prosperous future. How can we ensure quality of life for future generations? How can we make choices and cultivate environments in which sustainable practices are the norm? Over the past several years, the international community has been developing global goals to promote human rights, equality, and security through 2030. These Sustainable Development Goals are designed to create conditions in which every person on earth is able to thrive in societies that are safe, progressive, nurturing, just, and peaceful. Children and their families will have a vital role to play in creating these societies and will need a strong foundation in sustainable thinking and practices to bring about a brighter future.

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0130.002

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 head0.009
GPT teacher head0.287
Teacher spread0.278 · 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

Citations21
Published2015
Admission routes1
Has abstractyes

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