Les marchés financiers des pays émergents sur la scène internationale : facteur de stabilisation ou de crise ?
Bibliographic record
Abstract
Les marchés boursiers des pays émergents sont réputés pour leur instabilité et la fréquence de leur crise. Néanmoins, depuis quelques années, ils affichent des performances remarquables. Ils attirent les investisseurs, qui ont avantage à diversifier géographiquement leurs placements. De plus, les pays émergents se sont désendettés au point de devenir créditeurs nets, ce qui rend impossible des crises comparables à celles qui ont eu lieu dans les années 1990. Les liens entre les marchés financiers se sont cependant récemment resserrés, ce qui limite les bénéfices de la diversification. De plus, les marchés émergents sont moins efficients que les marchés occidentaux. Le risque subsiste ainsi du côté des institutions financières – sans compter des poches d'investissement spéculatif, qui éclateront peut être dans les mois à venir.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".