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Record W6957954145 · doi:10.60692/rgkrw-32h62

COVID-19 et offre de cours en ligne au Niger : prospection sur les raisons d'un échec

2021· article· fr· W6957954145 on OpenAlexaboutno aff

Bibliographic record

VenueGreater South Information System · 2021
Typearticle
Languagefr
FieldSocial Sciences
TopicInformation Technology and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsFace (sociological concept)LimitingLigneQuarter (Canadian coin)

Abstract

fetched live from OpenAlex

Pour faire face à la pandémie de COVID-19 à l'échelle mondiale, les mesures de confinement et de fermeture des écoles et universités ont engendré l'usage de formes diversifiées d'enseignement à distance à grande échelle afin d'assurer une continuité pédagogique dans des conditions inédites et improvisées.Au Niger, le ministère de l'Enseignement supérieur propose une initiative comme solution alternative : organiser les enseignements sur les réseaux sociaux WhatsApp et Telegram.Ces offres n'ont permis à aucune activité de voir le jour jusqu'à la réouverture des écoles et universités le 1 er juin 2020.Le présent article analyse les conditions de l'offre et les raisons de l'échec afin de tirer les leçons qui s'imposent et d'anticiper des offres porteuses dans les crises futures.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.034
GPT teacher head0.267
Teacher spread0.234 · 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 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
Published2021
Admission routes1
Has abstractyes

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