From Craft To Industry To Jobber: The Rise And Decline Of George White And Sons Of London Ontario
Bibliographic record
Abstract
As a blacksmith White’s experience in Canada led him to shift into first the construction of small implements and later the manufacture of agricultural steam engines. His company, George White and Sons grew with the expanding industrial economy, survived the increasingly specialized field and the consolidation in the sector, but was unable to survive the transition from steam to internal combustion. In April 1857 a young blacksmith and his new wife left Shute, Devon in England bound for a new life in London, Upper Canada. George White left with a large tool box, a small amount of money and high hopes. George used his skills as a blacksmith and some rudimentary knowledge of steam engines to build a company that constructed large agricultural engines and the threshing machines they powered. For George’s family, however, the early 1930s, the beginnings of the Great Depression, would prove fatal to the firm. The timing of the failure would suggest that the general depression vanquished the company, but in fact decisions taken much earlier weakened the firm to the extent that it was unable to survive. Innovation and adaptation to change had helped of the White family succeed, but when the pace of change exceeded their capacity to adapt the seeds of failure were sown.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.033 | 0.011 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".