Confiage d’enfants et nivellement des inégalités scolaires au Cameroun, 1960-1995
Bibliographic record
Abstract
La pratique du confiage d’enfants peut-elle servir à niveler les inégalités scolaires en Afrique ? Nous postulons que cet effet de nivellement dépend de trois paramètres du confiage, à savoir sa prévalence, sa distribution et son effet bénéfique sur l’éducation des enfants confiés. Nous utilisons des biographies familiales pour évaluer ces trois paramètres au Cameroun. On constate que, bien que le confiage reste courant, son effet sur la réduction des inégalités scolaires est limité, puisque, en termes d’accès et en termes d’impact scolaire, cette pratique ne profite pas d’abord aux plus pauvres. Ces résultats laissent croire que les politiques de réduction des inégalités scolaires en Afrique ne peuvent pas miser exclusivement sur les solidarités informelles mises en oeuvre à travers le confiage.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".