Large scale projects in the Arctic : socio-economic impacts of mining in Greenland
Bibliographic record
Abstract
Changes in the Arctic environment in the last decades are highly relevant to understanding changes in the socio-economic development in the Arctic. The main focus of this thesis will be on those changes, with a certain concentration on the changes in relation to Greenland. The thesis starts out by providing an overview of the physical and historical background of Greenland, followed by an overview of the economy of Greenland and a discussion of the obstacles for economic development. With Self-Government, Greenland is looking for new sources of income. The importance of the mineral sector has grown as it begins to show its potential as this new source. Case studies of four different mines, in three different countries, along with large scale projects in four different countries will be analysed and compared. Two of the mines are in Greenland, the Maarmorilik mine (closed operation in 1990) and the ISUA Iron Ore mine (that has not started operating yet). The other two mines are the Mir mine in Russia (closed operation in 2001) and the Red Dog mine in Alaska, which is still operating. The other case studies are the Eastern Siberia-Pacific Ocean Pipeline in Russia, The Snøhvit (Snow white) gas field in Norway, Kárahnjúkar hydro power and Alcoa Fjarðarál in Iceland and the Ekati diamond mine in Canada. These case studies will be analysed and discussed to gain a better understanding of the impacts that large scale resource exploitation have on their environment and the surrounding society, with the goal to gain knowledge about best practices.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".