‘We aint “<i>gentlemen</i>” merchants’: the country retailer in Upper Canada
Bibliographic record
Abstract
Country stores were universal in Upper Canada, and they are a necessary component of every living history site. Yet systematic explorations of the actual work of such stores in nineteenth-century North America, based on direct primary evidence, are uncommon; and powerful (and often conflicting) stereotypes of them persist, in living history settings and in the historical literature. This article goes beyond such standard images by using evidence from seven country stores. The starting point is that no one bought all his or her goods at a single store; besides local stores, rural families had access to retailers in towns and well-located villages. Competition demonstrates that retail success was not automatic; it involved relationships, decisions and strategies. Merchants did not need to write these down, however. Hence, the argument of the article must sometimes be indirect. What is clear is that selecting and knowing a wide variety of goods, pricing them, hiring and working with clerks, attending to and working with customers, managing credit and securing and making payments, handling goods taken in payment, and integrating non-retail elements (a crucial component of many Upper Canadian rural businesses) all involved judgement, strategy, daily decision-making and hard work.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.028 | 0.012 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".