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Record W1927265821 · doi:10.1080/2373518x.2015.1068641

‘We aint “<i>gentlemen</i>” merchants’: the country retailer in Upper Canada

2015· article· en· W1927265821 on OpenAlexaffabout
Douglas McCalla

Bibliographic record

VenueHistory of Retailing and Consumption · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsJudgementPaymentArgument (complex analysis)Variety (cybernetics)Competition (biology)Work (physics)BusinessMarketingPoint (geometry)CommerceLawFinancePolitical scienceComputer science

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score0.909

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.044
GPT teacher head0.238
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2015
Admission routes2
Has abstractyes

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