L’évaluation du crédit marchand à\nMontréal dans la seconde moitié du\ndix-neuvième siècle
Bibliographic record
Abstract
Cet article présente l'une des plus importantes et puissantes firmes d'évaluation de crédit en Amérique du Nord, la Mercantile Agency et sa sœur montréalaise la Dun, Wiman & Co. L'étude examine notamment le contexte entourant les premières firmes d'évaluation de crédit en sol nord-américain, le parcours des dirigeants, les caractéristiques propres aux bureaux de Montréal et, enfin, les deux principaux modes de diffusion de l'information proposée par l'agence : le livre de référence et le dossier de crédit. Je soutiens que la publication du livre de référence aura comme effet d'augmenter l'accès au crédit des entreprises qui possèdent un taux de capitalisation élevé auprès des créditeurs qui possèdent un abonnement. Les dossiers de crédit laissent, quant à eux, beaucoup plus de place à l'interprétation qu'une cote de crédit. Ils offrent ainsi une plus grande marge de manœuvre aux commerçants débiteurs qui possèdent une faible capitalisation justement parce que le créditeur peut interpréter de plusieurs manières le contenu de l'évaluation écrite. Cet article est avant tout une introduction aux firmes d'évaluations de crédit et une présentation générale de la succursale montréalaise de la Mercantile Agency. Enfin, cette recherche vise à renforcer l'historiographie en présentant une institution de régulation du crédit qui n'a, encore à ce jour, reçu que très peu d'attention de la part du milieu historien canadien. Abstract: This article examines one of the most prominent and powerful credit rating agencies in North America, the Mercantile Agency and its Montréal-based counterpart, Dun, Wiman & Co. The paper considers the context surrounding the first North American credit rating agencies, their managers' profiles, the specific characteristics of the Montréal offices and, finally, the two primary methods of information transmission offered by the agency: the reference book and the credit report. I argue that issuing the reference book resulted in increasing access to credit for companies with high capitalization rates from creditors who possessed a subscription. Meanwhile, credit reports allow for greater flexibility in interpretation than a credit score. They thus offer additional leeway to debtor merchants who have little capitalization precisely because the creditor can interpret in various ways the content of the written evaluation. Foremost, the article provides an introduction to credit rating agencies as well as a general overview of the Montréal branch of the Mercantile Agency. Finally, the purpose of this research is to contribute to historiography by presenting an institution of credit regulation that has yet to receive much attention from the field of Canadian history.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".