Initiatives at Natural Resources Canada to deal with orphan and abandoned mines
Bibliographic record
Abstract
The legacy of orphaned/abandoned mines, with their associated environmental liability, human health concerns and the financial costs of clean up, is a serious issue facing Canada. Canada’s long history in mining has resulted in more than 10,000 orphaned or abandoned sites, requiring varying degrees of rehabilitation. Mining regions have become less remote, and are often located close to populated areas, including many Aboriginal communities. A key priority of the federal Department of Natural Resources Canada (NRCan) is to promote the participation of Aboriginal communities in mining activities, including orphan and abandoned mines. Mining is generally regulated at the provincial level, although the federal department of Indian and Northern Affairs Canada maintains most of the responsibility for mines in northern Canada. The National Orphaned/Abandoned Mines Initiative (NOAMI) was established in 2002, in response to the request of the Canadian Mines Ministers that a multi-stakeholder advisory committee be set-up to study various issues and initiatives concerning the development of partnerships in the implementation of remediation programs across Canada. NOAMI is a co-operative Canadian program that is guided by an Advisory Committee consisting of the mining industry, federal/provincial/territorial governments, environmental non-government organizations and Aboriginal Canadians1. This paper will present an overview of the scope of issues surrounding abandoned mines in Canada, and programs that have been initiated to address the problem.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.018 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 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".