L’évaluation du crédit marchand à Montréal dans la seconde moitié du dix-neuvième siècle
Bibliographic record
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.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.000 |
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".