Les chaines de valeur mondiales et la productivite des entreprises manufacturieres au Canada
Bibliographic record
Abstract
Le present document a pour objectif de determiner si l'integration des entreprises manufacturieres canadiennes dans une chaine de valeur mondiale (CVM) ameliore leur productivite. Pour tenir compte de l'effet d'autoselection (les entreprises plus productives choisissent elles-memes de se joindre a une CVM), on utilise la methode d'appariement par scores de propension et celle de la difference des differences. Une entreprise qui commence a participer a une CVM peut voir sa productivite s'ameliorer immediatement ainsi qu'au cours du temps. L'ampleur des effets ainsi que le moment ou ils se produisent varient en fonction du secteur d'activite, du processus d'internationalisation et du pays d'origine des importations ou du pays de destination des exportations, ce qui peut signifier que les avantages les plus importants de la participation a une CVM decoulent des ameliorations technologiques.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| 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) | 0.008 | 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".