Multinational Firms' Strategies when Facing the State: The Case of Nickel Mining in New Caledonia
Bibliographic record
Abstract
This paper presents an analysis, based on the case of nickel mining in New Caledonia and the relationship between states and multinational firms (MNF). It aims at showing that the partners' objectives differ and that, to a large extent, MNFs can impose their own choices. The paper focuses on an innovating mining project by INCO, a Canadian MNF. It shows that the economic repercussions for the area will be small. However, MNFs can negotiate considerable tax exemptions. The paper then raises the question of why the project has been stopped by the firm, and it makes it clear that once gains have been obtained through negotiation, it may be profitable to not exploit the resource. Finally, the paper presents an analysis the importance for the firm to have projects in at least two countries so as to maximize concessions by the host countries by creating competition between them.
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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".