Mammoth market: the transformation of food retailing in Canada, 1946‐1965
Bibliographic record
Abstract
Purpose The purpose of this paper is to appraise the spread of supermarkets in Canada during the mid‐twentieth century. It examines how corporate chains altered the organization of distribution, reconfigured shopping experiences, and promised gains realized through greater business volume. Design/methodology/approach The paper utilizes a mix of primary and secondary sources to compare how companies responded to opportunities for mass marketing that emerged in the post‐war era. The perspective is grounded in the theory of managerial capitalism, which was originally elaborated by Alfred D. Chandler. Findings The paper highlights how mass food retailing in Canada shared some attributes normally associated with the rise of managerial capitalism, but it also reviews the variations and highlights the difficulties faced by firms despite their jump to giant size. In particular, it stresses how the leading companies did not build secure positions. Research limitations/implications Corporate archives in Canadian retailing either did not survive or remain inaccessible. The essay therefore draws upon a mix of sources including company publications and government investigations. The paper highlights the inability of companies to realize permanent gains commonly associated with large firm size or mass retailing. It stresses that there was no one “model” of corporate development. Originality/value This paper illustrates the complexities associated with developing strategic leadership in retailing and therefore should be valuable to educators and practitioners.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".