The demise of a local champion: MacMillan Bloedel’s acquisition by Weyerhaeuser
Bibliographic record
Abstract
In 1999, MacMillan Bloedel (MB), a forest product giant based in British Columbia (BC), was acquired by Weyerhaeuser (Weyco), an even bigger forest product giant, headquartered in Tacoma, Washington State. Apparently, MB had simply been another corporate name lost to ‘globalization’. Tom Stephens, MB’s last chief executive officer (CEO), who recommended the Weyco acquisition, certainly reinforced this view by emphasizing a ‘global’ trend toward bigger forest companies that could achieve efficiencies simply not available to the ‘smaller’ MB. Coincidentally, the acquisition apparently revealed another well-established trend: the Americanization of the Canadian economy. Yet this simple globalization account has already been publicly abused. Thus Weyco apparently did not find sufficient efficiencies in the former MB operations and in 2005 it sold its interests to Brascan, a giant fund and asset manager (but not forest product manufacturer) headquartered in Toronto, Ontario. The growth of big land asset companies with extensive forestland in their portfolios is, by the way, a global trend.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".