De l’émigration interne à l’émigration internationale : Impact d’une stratégie de survie sur la pauvreté et les inégalités de revenu au Sénégal
Bibliographic record
Abstract
Cet article mesure l’impact des envois de fonds des migrants internes et internationaux sur la pauvreté et les inégalités de revenu, à l’aide des données de l’« Enquête migration et transferts de fonds au Sénégal » réalisée par le Consortium pour la Recherche Economique et Sociale avec le soutien de la Banque mondiale. En considérant les envois de fonds comme étant des substituts potentiels des gains produits localement par le ménage en absence de migration, il ressort des analyses que ces fonds améliorent significativement le bien-être des bénéficiaires, grâce notamment aux gains de consommation qu’ils génèrent. Cependant, seuls les transferts internationaux permettent une baisse significative du taux de pauvreté, au contraire des transferts internes qui eux n’ont pas d’impact. En outre, comme seuls les ménages les plus aisés bénéficient le plus de ces deux types de transferts, cela a pour conséquence un renforcement des inégalités.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
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".