Roulement des usines et croissance de la productivite dans le secteur canadien de la fabrication
Bibliographic record
Abstract
Ce document donne un apercu de l'importance du roulement des usines dans le secteur canadien de la fabrication, c'est a dire le nombre d'entrees et de sorties, au cours des trois periodes suivantes : 1973 a 1979, 1979 a 1988 et 1988 a 1997. On examine aussi la contribution de ce roulement a la croissance de la productivite du travail dans le secteur de la fabrication au cours de ces trois periodes. Le roulement des usines contribue de facon importante a la croissance de la productivite, les usines entrantes plus productives remplacant les usines sortantes moins productives. Par ailleurs, on constate qu'une part proportionnellement plus elevee de l'effet des entrees et des sorties sur la croissance de la productivite est attribuable a la fermeture d'usines et a l'ouverture de nouvelles usines par des entreprises a etablissements multiples ou sous controle etranger. Habituellement, les usines ouvertes par des entreprises a etablissements multiples ou sous controle etranger sont beaucoup plus productives que celles ouvertes par des entreprises a une seule usine ou sous controle canadien.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".