Economic development of the Canadian Arctic and the impact of mining on Inuit
Bibliographic record
Abstract
The bachelor thesis analyses and compares three main periods of the economic development in the Canadian Arctic, starting from the years 1950's until the end of the administrative of Prime Minister Harper in 2015. Mining of natural resources, as the base of the North's development, has been seen by the federal government also as a tool for cultural assimilation of Inuit into the dominant society. Nevertheless, participation of Inuit in mining activities and in fact in the whole employment culture has had serious impact on Aboriginal communities who have never been consulted about the federal strategy. However, while the first phase of development is characterized by strict colonialist approach of the government, the situation started to change during the second phase, characterized by a rising of Inuit's political participation and their first demonstrations of discontent. Although during the third, neoliberal era, several new mechanisms in order to improve the dialogue between Inuit, mining companies and the government were accepted, social conditions in Inuit communities remain below the Canadian average and with the government "laissez-faire" attitude they are not to be changed any time soon.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".