Productivite urbaine: qui profite des economies d'agglomeration?
Bibliographic record
Abstract
Il existe de nombreuses preuves qu'un grand nombre d'entreprises se regroupent au niveau spatial et qu'il y a une association entre la formation de grappes et la productivite. Au lieu de determiner les vastes effets de la formation de grappes, le present document explore comment les differents types d'entreprises profitent de l'agglomeration. Il fait progresser la recherche sur l'agglomeration en demontrant tout d'abord que les entreprises ne profitent pas au meme degre de la colocalisation et, en deuxieme lieu, que les entreprises ayant des capacites internes differentes profitent de formes differentes d'externalites geographiques. L'analyse empirique est axee sur les etablissements du secteur canadien de la fabrication qui etaient en activite au cours de la periode allant de 1989 a 1999.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".