L'interdépendance spatiale de l'investissement américain dans les économies provinciales canadiennes
Bibliographic record
Abstract
L'étude empirique de l'investissement direct étranger à l'aide des modèles économétrique spatiale est maintenant bien établie. Cependant, peu d'études se sont penchées sur l'investissement direct étranger dans des économies développées et un nombre encore plus restreint traite du cas où ces économies sont celles de provinces d'un même pays. Ce mémoire tente de pallier cette lacune en étudiant l'investissement direct américain entre 2004 et 2011 dans les provinces canadiennes et en utilisant le modèle spatial SAC qui combine le modèle autorégressif spatial et le modèle d'erreur spatiale. Nos résultats démontrent une grande robustesse de la présence de l'interdépendance spatiale de l'investissement direc américain. De plus, ils proposent que l'argument de compétitivité utilisé pour justifier la baisse du niveau de taxation des entreprises est sans fondement dans le cas des provinces canadiennes.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".