Technological change and mining labour : copper mining and milling operations at the Britannia mines, British Columbia, 1898-1937
Bibliographic record
Abstract
Most recent studies of the relationship between technological change and mining labour in the western metal-mining regions of North America have concentrated on the impact of the mechanization of the industry that took place during the second half of the nineteenth century. The distinct impression is left that the increased use of machinery — especially the machine drill — was the chief factor in reducing the skill levels associated with mining as a craft tradition. Preoccupation with machinery has led to the assumption that by the beginning of the twentieth century the transformation to modern forms of mining was essentially complete and the traditional miner an anachronism. Mining as practiced prior to 1900 differed qualitatively and quantitatively from the subsequent period of "modern mining;" but the introduction of machinery per se was less important to the reorganization of the patterns of work in the mines than the redesigning of the engineering systems in which workers and machines were employed — a process which gained its full momentum in the decades after 1900. This transformation involved the gradual abandonment of low-volume, high-value, selective mining methods in favour of higher volume, non-selective methods which emphasised the quantity rather than the quality of the ore mined. The change redefined the nature of work in and around the mines, putting an end to a tradition of mining practice that was at least as old as the methods described in Agricola's De Re Metalica, something the initial mechanization of mining had never been intended to accomplish. Under selective mining practices, machinery was used to assist the skilled miner in his traditional task. Under non-selective or mass mining techniques, a new generation of engineers trained in the applied sciences redefined the miner's work as solutions were sought to the problems of an increasingly complex geology in a climate of rapid economic expansion, chronic over-production, generally declining metal prices, and ever increasing production costs. The efforts and successes of these engineers were amply demonstrated in the fields of mining, metallurgical, and human engineering. The impact of the change is evident in varying degrees throughout the metal-mining community; but by focusing on copper mining — the technological leader from 1900 to 1930 — the full impact of the industrial sciences on mine labour is evident.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".