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The new vampires of the global economy

2015· article· en· W2323499555 on OpenAlexaboutno aff
Nick Dearden

Bibliographic record

VenueSocialist Lawyer · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Illicit Activities, and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsBusiness

Abstract

fetched live from OpenAlex

In the village of Rosia Montana, located in the mountains of Transylvania, a new sort of vampire is trying to drain the blood of Romania's people.A Canadian mining company, Gabriel Resources, is claiming billions of dollars in a secret tribunal because Romania's parliament and court system have decided that Gabriel can't create Europe's largest gold mine.Mining in mineral-rich Rosia Montana ended in 2006 when Romania joined the European Union.For years Gabriel Resources have been trying to open a new mine but local communities, united under the Save Rosia Montana campaign, have fought back on social, environmental, economic and cultural grounds.The project was expected to release over 300 tonnes of gold and 1500 tonnes of silver.But in the process, it would create a cyanide lake, blast away four mountain tops and relocate thousands of people from their homes.Many Romanian institutions including the Romanian Geological Institute and Romanian Academy have spoken against the project and its methods, as the mine threatens some of the best-preserved Roman mining galleries in Europe.In 2013 Gabriel Resources attempted to pressure Romania's government to approve the mine by passing a law to declare their mine to be of overriding national interest.But this backfired, triggering protests which spread into Bucharest and attracted the interest of international solidarity groups.The campaign remains the biggest social mobilisation in Romania since the fall of communism in 1989.The parliament rejected the change in mining laws, and since that time the country's courts have not given the project a vital environmental permit that it requires to proceed.But that's not the end of the story, because in an era of globalised investment rules multinational corporations have gained new international legal avenues that allow them to seek redress in secret tribunals, without appeal, which are not available to ordinary people.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0090.007
Open science0.0000.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0200.003

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.

Opus teacher head0.044
GPT teacher head0.329
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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