Shareholder Employment at Red Dog Mine
Bibliographic record
Abstract
Under the Alaska Native Claims Settlement Act of 1971, Iñupiat of northwest Alaska organized as shareholders in the NANA1 Regional Corporation, Inc., and received title to 2,258,836 acres, including rights to the rich Red Dog zinc deposit. In 1982, NANA signed a joint-venture agreement with Teck2 to develop the mine, including provisions for preferential hire for qualified NANA shareholders. The agreement aimed for 100% shareholder hire by 2001. As of 2010, Teck had 220 NANA shareholders in full-time employment, which is 53 percent of the workforce. Other mines around the world have similar indigenous or local hire agreements with mixed success. The Voisey’s Bay mine sets the high mark for Canada with an Aboriginal hire rate of 54 percent (AETG 2008), followed by Ekati diamond mine at 50 percent (BHP Billiton 2011). So the track record for indigenous employment at Red Dog is high by global standards, although it falls short of NANA and Teck’s goal. What are the continuing barriers to increasing shareholder hire, retention and promotion?
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 0.006 |
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".