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Record W7131409794 · doi:10.71895/prsm/revue-rise.n1.3

L’obligation scolaire et la transition école-collège au Burkina Faso : difficultés et suggestions d’amélioration des performances des élèves

2023· article· fr· W7131409794 on OpenAlexvenueno aff
Jean-Claude Bationo, Innocent Kiemdé

Bibliographic record

VenueRevue des sciences de l éducation · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicAfrican Studies and Ethnography
Canadian institutionsnot available
Fundersnot available
KeywordsObligationFace (sociological concept)Ile de france

Abstract

fetched live from OpenAlex

L’obligation scolaire au Burkina Faso a entrainé un grand effectif dans les écoles avec pour corolaire la baisse de la qualité des enseignements. Les statistiques annuelles montrent que le taux d’accès à la scolarisation est moyen et un taux d’achèvement peu reluisant (63% en 2019). En conséquence, le taux d’admission en 6ème reste faible (26,2% en 2019). Par ailleurs, dès la classe de 6ème la scolarité des élèves fait face à des obstacles. Cette situation suscite des questions relatives à la transition école-collège qui, en tant que moment clé de la scolarité, marqué par le changement d’établissement, est souvent difficilement vécue par les apprenants comme une rupture sur les plans affectif et pédagogique. Cette étude tente de mettre en lumière le rapport entre obligation scolaire, difficultés dans l’enseignement-apprentissage des contenus scolaires et transition école-collège. Elle permet de mettre en évidence des facteurs qui sont des obstacles à la transition école-collège et face auxquels les acteurs ont proposé des actions à entreprendre pour l’atteinte des objectifs de la loi d’orientation.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.248

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.179
GPT teacher head0.400
Teacher spread0.222 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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