MétaCan
Menu
← Back to cohort
Record W7029156260

International Trade and Investment Law and Carbon Management Technologies

2012· article· en· W7029156260 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
FundersWorld Resources InstituteMcGill University
KeywordsGreenhouse gasInvestment (military)International trade lawTrade barrierEmissions tradingInternational investmentInternational lawEmerging technologies
DOInot available

Abstract

fetched live from OpenAlex

Reducing emissions of greenhouse gases will require the development of carbon management technologies that are not currently available or that are not currently cost-effective. While market mechanisms such as carbon pricing must play a central role in stimulating the development of these technologies, governmental policy aimed at fostering carbon management technologies and lowering their costs must also play a part. Both types of policies will form part of an optimal greenhouse gas control portfolio. This article develops a framework of international trade and investment law insofar as they may affect carbon management technologies. While it is commonly perceived that international trade law and investment law usually constrains the development of environmental policy, the flipside is often ignored. In addition to discussing how carbon management policy might be constrained, this article also identifies opportunities within the framework of international trade and investment law in which carbon management technologies might be advanced or supported.

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)0.003
metaresearch head score (Gemma)0.006
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: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.011
Scholarly communication0.0050.005
Open science0.0010.002
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.021
GPT teacher head0.287
Teacher spread0.265 · 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
GenreEmpirical

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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same topicSchizophrenia research and treatment→French-language works237,207→