MétaCan
Menu
Back to cohort
Record W3130281398 · doi:10.1163/19426720-02701001

Corporate Governance and the Environmental Politics of Shipping

2021· article· en· W3130281398 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGlobal Governance A Review of Multilateralism and International Organizations · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMaritime Transport Emissions and Efficiency
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCorporate governanceBusinessPoliticsInternational tradeProfit marginIndustrial organizationFinanceLaw

Abstract

fetched live from OpenAlex

Abstract A handful of companies dominate the world’s shipping industry. These firms have gained political leverage over the global governance of container shipping in particular. Intriguingly, in recent years the Danish conglomerate Maersk—the world’s biggest container and shipping vessel company since the mid-1990s—has been using its influence to push for higher environmental standards for the industry as a whole. To some extent these initiatives are helping to promote environmental efficiencies, cleaner fuels, and greener technology. But they are also raising costs for small and midsized companies with extremely low profit margins, further enhancing the competitiveness of the biggest shipping conglomerates in an increasingly oligopolistic market. While voluntary self-governance by companies such as Maersk is incrementally improving the environmental management of global shipping, it is also further concentrating governance power within a few transnational corporations, potentially taking more ambitious regulation off the agenda.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.007
GPT teacher head0.220
Teacher spread0.213 · 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