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.
Bibliographic record
Abstract
Alors que la littérature semble prétexter une pervasion numérique (Boullier, 2019) dans le champ de l’éducation en Afrique, qui s’est accentuée avec la récente pandémie (Alladatin et al., 2020), nous pensons que, dans les faits, la situation serait moins reluisante. Si, dans un pays aussi avancé que la France d’un point de vue technologique et économique, le numérique en éducation a des problématiques de dynamisation (Poteaux, 2013), comment expliquer que dans les pays d’Afrique où la moitié de la population peine à se nourrir, qu’il y ait une telle révolution? Nous ne nions pas qu’au-delà des résultats, ces travaux de recherche permettent de dévoiler la compétitivité du continent africain en termes de numérique en éducation. Mais des nuances sont à apporter sur plusieurs plans.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.013 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it