Training Center for Artisanal Miners: Moving towards Effective Formalization and Mercury Reduction in Antioquia, Colombia
Bibliographic record
Abstract
Artisanal gold mining (AGM) activities encompass small, medium, informal, legal and illegal miners in numbers close to 16 million and are responsible for producing around 380-450 tonnes/a or almost 12% of total mined gold. AGM is considered the main anthropogenic source of mercury pollution emitting and releasing around 1400 tonnes/a into the environment. In 2013, The AGM sector in Colombia produced 72% of the country's gold or around 40 tonnes/a of gold. In the Department of Antioquia, artisanal miners take their ores to Processing Centres to be amalgamated in small ball mills. On average, 50% of the mercury introduced in the process is lost: 46% lost to the tailings as mercury droplets and 4% lost as fumes when amalgam is burned. Miners usually do not need to pay for the amalgamation service as the Centres retain the Hg-contaminated tailings to leach with cyanide extracting the non-amalgamated gold which is usually around 75% of the gold in the ore. By 2010, 5 municipalities in Antioquia were emitting and releasing to the environment up to 110 tonnes/a of mercury. By 2013, thanks to an educational project implemented by UNIDO and local partners, 46-70 tonnes of mercury have been prevented from polluting the environment. The project adopted a strategy of educating the owners of the Processing Centres on cleaner methods to produce more gold consequently reducing the amount of mercury entering the amalgamation process. The success of this project motivated the Government of Colombia to invest in the idea of creating Training Centres for Artisanal Miners (TCAM), in which miners could be trained and educated. In 2014, the Government of the province of Antioquia in cooperation with the National Centre of Learning (SENA) created a US$6.5 million TCAM in the town of El Bagre, Antioquia to train conventional and artisanal gold miners in sustainable gold mining and processing techniques, legalization of informal miners, economic diversification, food security, ethics, accounting, business management, health and environmental issues in mining, social responsibility, etc. The SENA is also investing in training its trainers to run 3 other Centres in different locations in Antioquia. The Canadian International Resources and Development Institute (CIRDI) are working together with SENA to implement these Training Centers. The steps for the development of curriculum for the miners and implementation of the Centres are discussed in the presentation. Currently, there are 39 new mercury-free processing plants operating in Antioquia.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".