Bibliographic record
Abstract
Le marché financier américain et canadien présentent beaucoup de similitudes. La question qu'on se pose est que les incohérences détectées chez le premier vont-elles se généraliser partout. En effet une évaluation des données boursières américaines a montré que les primes de risque constatées sont trop excessives par rapport aux prévisions du modèle de CAPM de consommation. Ce modèle qui fait partie des plus parfaits dont disposent les économistes et financiers, va nous permettre de faire des prévisions de primes de risque avec les données canadiennes. Pour la période retenue, les résultats obtenus ont confirmé la tendance constatée dans les précédentes études. C'est à dire des primes de risques anormalement élevées. ______________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : CAPM, CAPM de consommation, MEDAF, MEDAF de consommation, CCAPM, Énigme de la prime de risque, Prime de risque excédentaire.
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 | 0.015 | 0.118 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 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".