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Record W3211824408 · doi:10.18162/ritpu-2021-v18n3-05

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

2021· article· fr· W3211824408 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueRevue internationale des technologies en pédagogie universitaire · 2021
Typearticle
Languagefr
FieldSocial Sciences
TopicInformation Technology and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakArtMedicineVirology

Abstract

fetched live from OpenAlex

Pour faire face la pandmie de COVID-19 l'chelle mondiale, les mesures de confinement et de fermeture des coles et universits ont engendr l'usage de formes diversifies d'enseignement distance grande chelle afin d'assurer une continuit pdagogique dans des conditions indites et improvises. Au Niger, le ministre de l'Enseignement suprieur propose une initiative comme solution alternative : organiser les enseignements sur les rseaux sociaux WhatsApp et Telegram. Ces offres n'ont permis aucune activit de voir le jour jusqu' la rouverture des coles et universits le 1 er juin 2020. Le prsent article analyse les conditions de l'offre et les raisons de l'chec afin de tirer les leons 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.

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)0.001
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.617
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.302
Teacher spread0.270 · 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