An assessment of the impact of targeted interventions in mitigating the adverse drivers of irregular migration and forced displacement
Bibliographic record
Abstract
Cet article discute de la manière dont les interventions publiques au nveau local ou sectoriel peuvent affecter la migration et le déplacement humain forcé. Il analyse l’évaluation empirique concernant l’impact des interventions ciblées sur la propension à émigrer, soit par choix, soit de manière forcée. La littérature académique sur les conséquences des interventions publiques locales ou sectorielles sur le comportement des individus en termes de mobilité humaine reste assez éparse et de nouvelles approches s’avèrent nécessaires pour appréhender de manière plus appropriée les différents canaux de transmission. L’article propose dès lors plusieurs pistes de recherche potentielles et d’options méthodologiques afin d’acquérir une meilleure compréhension de la manière dont les interventions publiques spécifiques peuvent atténuer les effets des conditions défavorables favorisant la migration illégale et le déplacement humain forcé.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".