Mining Money: the generative capacities of scientific and legal knowledge practices in the making of resource economies
Bibliographic record
Abstract
In 1997 a scandal associated with Bre-X, a junior mining firm, and its prospecting activities in Indonesia, exposed to public scrutiny the ways in which mineral exploration firms acquire, assess and report on scientific claims about the natural environment. At stake here was not just how investors understood the provisional nature of scientific knowledge, but also evidence of fraud. Contemporaneous mining scandals not only included the salting of cores, but also unreliable proprietary sample preparation and assay methods, mis-representations of visual field estimates as drilling results and ‘overly optimistic’ geological reports. This paper reports on initiatives taken in the wake of these scandals and prompted by the Mining Standards Task Force (TSE/OSC 1999). For regulators, mandated to increase investor confidence in Canada’s leading role within the global mining industry, efforts focused first and foremost upon identifying and removing sources of error and wilfulness within the production and circulation of scientific knowledge claims. A common goal cross-cutting these initiatives was ‘a faithful representation of nature’ (Daston and Galison 2010), however, as the paper argues, this was manifest in an assemblage of practices governed by distinct and rival regulative visions of science and the making of markets in claims about ‘nature’. These ‘practices of fidelity’, it is argued, can be consequential in shaping the spatial and temporal dynamics of the marketization of nature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".