Bibliographic record
Abstract
1. Introduction The World Commission on Environment and Development (1987) headed by G.H. Brundtland defined sustainable development as one that meets the needs of the present without compromising the ability of future generations to meet their own needs. The United Nations 2005 World Summit Outcome Document identified three interdependent and mutually reinforcing pillars of sustainability as economic development, social development, and environmental protection. These pillars are influenced by various interrelated factors in almost every industrial activity related to products or services. The mining industry is witnessing an epoch-making revolution due to a growing demand for metals (copper, iron, aluminum, nickel, gold), minerals (clays, gemstones), and energy resources (oil, coal, uranium) all over the world and especially in the emerging economies of China, India, and Brazil. For example, the online data of World Bureau of Metal Statistics indicates that China is currently consuming approximately 25% of the entire world production of base metals. In addition to a general price hike in most of the afore-mentioned commodities, there is a gradual depletion in their available reserves in different parts of the globe. The industry is actively employing improved exploration, enhanced recovery, and novel recycling technologies to address the sustainability issues pertaining to economic development. Since the companies simultaneously work at mine sites in several countries, the mining industry is essentially global in nature. The employment growth in the industry has been phenomenal over the last five years or so. For example, the average annual employment growth in the Canadian mining sector (that includes surface mining of oil sand in Alberta and Saskatchewan) has stayed above 7% since the year 2001. According to the online data of the Organization for Economic Co-operation and Development, this is the highest among the G-8 and OECD countries. In the Canadian context in particular (and elsewhere in general), there is an acute shortage of skilled professionals in the industry. This is attributed to an aging workforce and a low previous enrolment in Mining, Materials, Environmental, and Geological engineering programs in the universities. These contributing factors, in turn, resulted from the skepticism among the public about the abandonment of mining communities after project completion. A renewed emphasis on the socio-economic well being of the local communities is fundamental for attracting and retaining skilled professionals. Whereas economic and social development is in the interest of the mining industry, the third pillar of sustainability, namely environmental protection, has to be imposed by the regulatory authorities. The main environmental issues associated with the industry include greenhouse gas emission, energy consumption, water use and recycling, metal leaching and acid rock drainage (ARD), and the geotechnical stability of large volumes of solid wastes. Interestingly, all of the environmental problems are variably affected by climate change that was brought about by industrialization, including the global mining industry, in the first place. Continued pressure from various stakeholders has resulted in stringent environmental criteria and obtaining public licensure for mining is increasingly becoming more costly. The main objective of this paper is to develop a clear understanding of sustainable development in the mining industry through innovation in waste disposal. First, the generation of waste rocks and slurry tailings in conventional mining operations is described. Next, the inherent challenges in the mining industry to effective waste management are highlighted. This is followed by a description of two most promising innovative waste disposal methods, namely: tailings thickening and co-mixing of tailings and waste rock. The economic, social, and environmental benefits of the two engineering methods are highlighted. …
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".