The Contribution of Post-Secondary Education to Human Capital Stocks in Canada and the United States
Notice bibliographique
Résumé
In this paper the authors suggest that human capital is the dominant component of total wealth in both Canada and the US. To understand the creation of wealth in these countries it is therefore essential to understand how human capital is created. Assessing the possible reasons for a difference in human capital in the two countries is the major focus of this paper. Post-secondary education is an important contributor to the quantity of human capital; quantifying this contribution and evaluating the post-secondary systems that produced it is therefore of major policy importance, but it raises many difficult problems. The study found that while Canada has a higher fraction of workers with a post-secondary education, this is not generally reflected in a higher share of efficiency units supplied. The authors also offer the hypothesis that post-secondary schooling in the US has added substantially more efficiency units of human capital to those making the investment than occurs in Canada. They suggest that the data supports a further hypothesis that a large part of this may be due to the larger fraction of university educated at both the undergraduate and post-graduate degree level in the post-secondary group for the US. In addition, the gap across countries in the efficiency units difference associated with a post-secondary education grew substantially from 1980 to 2000. The evidence suggests that an important part of this increasing gap is due to large relative gains for those with a post-graduate degree in the US. Finally, using estimates of the human capital price series in each country, the results suggest that the post-secondary systems of both countries have resulted in increases in the mean efficiency units supplied at all levels, but especially so at the university level, and for the US, even more so at the post-graduate degree level. Relative to the no post-secondary sector, the US shows higher amounts of human capital per capita for those with post-secondary education than is the case for Canada. The level measures used in this paper are not directly comparable across countries, so it may still be the case that the absolute difference in human capital between those with and without a post-secondary education in Canada is greater than in the US and/or that Canada’s workers with a post-secondary education have more human capital on average. An answer to this question depends on being able to estimate the relative price of human capital in the two countries.
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 | 0,000 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».