Notice bibliographique
Résumé
Ontario's private sector has had zero productivity growth in the latest six year period. Ontario performed much worse than the rest of Canada or the United States. This is obviously a cause for concern. Productivity is an important measure of progress in the economy, as it is associated with rising standards of living in the long run.\n\nThe question is whether this observation about productivity is significant in its own right, or if it is more a symptom of the overall state of the economy. The Ontario economy has been hit by major external shocks, resulting in plunging exports and a declining private sector employment rate. Is productivity an independent causal factor, or merely the residual outcome of weak demand?\n\nThis paper examines the issue through detailed sectoral data. It examines the diversity of productivity performance in about 50 industrial sectors. The picture that emerges is that the overall productivity growth rate is not really representative. It is the random outcome of a wide range of underlying variation. There are some important sectors (e.g., retail trade and finance) that have maintained decent productivity growth. There are some sectors, especially in manufacturing, where the level of productivity is currently far below its previous level. This is not merely weak growth, but decline. In some industries (e.g., steel), some of the largest players have shut down, essentially changing the character of that sector even though the name remains the same.\n\nOverall, the implication is that the weakness of productivity is caused by weak aggregate demand. Historically, productivity growth has been pro-cyclical, being positively correlated with demand growth. Strong demand creates economies of scale and distributes overhead costs over a larger base. The weakness of demand in recent years has also been associated with compositional shifts in the economy. Employment and output have plunged in manufacturing (whose level of productivity is above the economy-wide average), while it has grown in some service sectors with below average productivity. Such compositional shifts would reduce the average productivity of the economy even if there was no change in the productivity of any individual sectors.\n\nOntario had positive productivity growth in the service sector, but underperformed the strong growth found in the rest of Canada. Here, too, the explanation is likely found in diseconomies of scale due to weaker demand. For example, the higher productivity growth in retail and wholesale trade in the rest of Canada was associated with growth in sales that was two-thirds higher than in Ontario over the past six years.\n\nThe weakness of demand in Ontario is largely due to falling exports, caused by the high Canadian dollar and the weak US economy. This can be considered in a positive light. While a strong rebound in exports does not appear to be around the corner, the worst is probably behind us. There should be a continuing gradual improvement in exports in the coming years, leading to some increase in productivity growth. The Ontario government should focus its policy levers, which are admittedly constrained, on helping to further the upward trend in exports.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,009 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».