The Industrialization of Tree Harvesting Systems in the Eastern Canadian Forest, 1955-1995
Bibliographic record
Abstract
1 Richard A. Rajala, Forest as Factory: Technological Change and Worker Control in the West Coast Industry, 1880-1930, Labour/Le Travail, 32 (Fall 1993), 73-104, and Richard A. Rajala, Clearcutting the Pacific Rain Forest: Production, Science, and Reg ulation (Vancouver 1998). To the sources he cites in Clearcutting, xx, we would add the following which deal specifi cally with the history of mechanization: C.R. Silversides (accompanying essay by Richard A. Rajala), Broadaxe to Flying Shear: The Mechanization of Forest Harvesting East of the Rockies (Ottawa 1997); C.R. Silversides, Logging Mechanization in Eastern Canada, un published and undated manuscript, Forest Engineering Research Institute of Canada [FERIC] Library, L/C SD 388 S561; and Ken Drushka and Hannu Konttinen, Tracks in the Forest: The Evolution of Machinery (Helsinki 1997). Harry Braverman, Labour and Monopoly Capital: The Degradation of Work in the Twenti eth Century (New York 1974).
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".