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Record W4297852801 · doi:10.1080/13504622.2022.2120185

How do students at the end of secondary school consider the challenges of sustainable development of the Seine in France? What avenues for education?

2022· article· en· W4297852801 on OpenAlexaff
Agnieszka Jeziorski, Marco Barroca-Paccard, Faouzia Kalali

Bibliographic record

VenueEnvironmental Education Research · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsTransformative learningEnvironmental educationAgency (philosophy)Context (archaeology)Education for sustainable developmentSociologySustainable developmentPedagogySet (abstract data type)Outdoor educationPolitical scienceSocial scienceGeographyComputer science

Abstract

fetched live from OpenAlex

This article aims to understand how students aged 14–17 from different contexts in France consider the issues related to the Seine. 20 interviews were carried out focusing on the implementation of an educational approach enabling students to grasp the priority issues associated with the sustainable development of the Seine. The analysis brings out the way in which the students have experienced the educational approach; it aims to characterise their relationship with the river, and to define their eco-citizen engagement. Several specificities emerge depending on the context studied, but the students of the three schools underline the interest of approaches that go beyond the traditional education form and that are rooted in their local reality. Our article set the interest in valorising another way of learning where students feel more free and autonomous and also requires training teachers in the development of their agency for a transformative-sociocritical approach of ESE.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.242
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.019
GPT teacher head0.335
Teacher spread0.315 · 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 teacher head, not a consensus.

Study designObservational
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

Citations1
Published2022
Admission routes1
Has abstractyes

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