MétaCan
Menu
Back to cohort
Record W6998696310

Analyse d’une démarche de\n résolution de problèmes environnementaux en République de Guinée

2016· article· fr· W6998696310 on OpenAlexaff

Bibliographic record

VenueÉrudit (Université de Montréal) · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicInformation Technology and Learning
Canadian institutionsUniversité du Québec à MontréalUniversité de Sherbrooke
Fundersnot available
KeywordsContext (archaeology)Class (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

Cet article décrit l’impact de la mise en œuvre d’une démarche de résolution de problèmes environnementaux par trois groupes d’élèves de la République de Guinée. L’objectif poursuivi était de mieux comprendre les enjeux d’une telle démarche au regard d’un engagement citoyen des jeunes africains pour le développement durable. Une classe du primaire, une du secondaire et une autre de la formation professionnelle ont travaillé à poser et à formuler des solutions à la problématique de la qualité de l’eau dans la capitale Conakry. Les données recueillies ont permis de constater l’intérêt des élèves pour ces questions, particulièrement lorsqu’elles sont appréhendées par observation directe sur le terrain ; leur désir de passer à l’action a été également manifeste. Les principales limites observées sont l’accessibilité restreinte à des ressources documentaires ainsi que le manque de formation des enseignants en éducation à l’environnement et au développement durable.

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)0.006
metaresearch head score (Gemma)0.010
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 score0.134
Threshold uncertainty score0.266

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0050.003
Scholarly communication0.0060.003
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.194
Teacher spread0.187 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueÉrudit (Université de Montréal)Same topicInformation Technology and LearningFrench-language works237,207