Extractive separations: A Polanyian note on the international investment treaty regime
Bibliographic record
Abstract
This paper examines the relationship between extractive industries and the In-ternational Investment Treaty Regime. This regime, I argue, works to separate extrac-tive investments from the social conditions that make those investments and extractions possible. Examining 3 recent cases— Bear Creek, Von Pezold and Rockhopper, I argue that international investment arbitration invokes novel and deeper separations . More-over, the kinds of separations now enabled in the investment treaty regime take diverse form. To explore this diversity, this paper foregrounds 3 techniques of separation made visible in these 3 cases including techniques of displacement, differentiation and ab-straction. This, in turn, signals a broader contradiction in international investment ar-bitration— a form of practice now deeply contested by those keen to rethread investment governance to social context but shaped by decisions that sever investments from those contexts in ever abstract ways. Read in Polanyian terms, I argue there is a tension be-tween investments deeply embedded in social contexts but increasingly disembedded as abstracted legal and financial objects.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.029 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.016 |
| Insufficient payload (model declined to judge) | 0.004 | 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".