Bibliographic record
Abstract
À travers l’expérience mozambicaine des trente dernières années, cet article interroge la pertinence des modèles économiques extractivistes comme stratégie de développement reposant sur l’exploitation massive des matières premières. Soutenu par la communauté des bailleurs de fonds, le projet mozambicain fait fi de sa population, grande perdante de l’épopée extractiviste. Les personnes vivant en dessous du seuil de pauvreté représentent encore près de la moitié de la population en 2014. Quant aux inégalités, elles se sont accrues depuis 1996. Sa spécialisation extractiviste rend enfin le modèle mozambicain particulièrement vulnérable aux chocs économiques externes. L’instabilité inhérente aux économies primo-exportatrices ne peut pas garantir de ressources stables, sans lesquelles tout projet de développement économique et social s’avère illusoire.
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 | 0.000 |
| 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) | 0.004 | 0.002 |
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; both teacher heads agree on what is shown here.
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".