Looking East and West for Pulpwood, Pulp and Paper: Great Britain as an Anomaly in Europe, 1860–1960
Bibliographic record
Abstract
Abstract The years 1860 to 1960 witnessed the birth and rapid expansion of the modern pulp and paper industry. Its sine qua non was access to enormous volumes of conifer trees that grew in the northern hemisphere’s temperate and boreal forests. Predictably, countries in northern Europe with large swaths of these woodlands became home to substantial pulp and paper industries. This article explains why Great Britain represented Europe’s glaring exception to this rule. Unique circumstances allowed it to become Europe’s largest newsprint producer even though it suffered from a dearth of conifers. Britain’s newspaper publishers grew their circulations and created the largest newsprint market in Europe for most of the period under examination. To meet their exploding demand for paper, they gained control over their country’s newsprint industry. Like producers in other western European countries, they looked to Scandinavia to address their lack of domestic wood supplies, but they also exploited their imperial connection to access a prodigious supply of fibre and pulps in Canada and Newfoundland. Britain’s competitive advantage in this regard was political and not economic because tapping this distant source of raw materials was costly. Nevertheless, British producers were able to absorb the higher costs because their business was vertically integrated. However, British producers could not outrun their resource deficit forever. Changing global industry conditions after World War II caused them to lose their preponderant standing.
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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 | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".