Made in Canada! The Canadian Manufacturers’ Association’s Promotion of Canadian-Made Goods, 1911-1921
Bibliographic record
Abstract
Beginning just before WW1 and continuing into the postwar period, the Canadian Manufacturers’ Association mounted a campaign to sell Canadian consumers on the virtues of buying “Made in Canada” goods. Not simply an appeal to patriotism, this campaign had to convince Canadian consumers of the satisfactory quality of such goods — which manufacturers had to deliver the substance of — in an increasingly sophisticated retail and marketing environment. Such an encouragement of the demand side of the producer/consumer equation is an important example of the proactive stance taken by Canadian manufacturers in the early twentieth century to improve their own viability and success. This paper examines the “Made in Canada” campaign as part of a range of business strategies that also included support for scientific industrial research, technical standardization, and vocational education, alongside more traditional anti-competitive policies. The scope of these strategies suggests that the impact of the Second Industrial Revolution was being fully felt in Canada and business leaders recognized the implications of a new political economy in which an unimaginative defence of the protective tariff was no longer adequate.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.021 | 0.007 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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; 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".