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Record W3047387111 · doi:10.1080/03088839.2020.1803430

Climate change adaptation by ports: the attitude of Chinese port organizations

2020· article· en· W3047387111 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

VenueMaritime Policy & Management · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMaritime Transport Emissions and Efficiency
Canadian institutionsUniversity of British ColumbiaUniversity of Manitoba
Fundersnot available
KeywordsPort (circuit theory)Adaptation (eye)Context (archaeology)Climate changeChinaBusinessClimate change adaptationEnvironmental resource managementPolitical scienceEconomicsEngineeringGeographyPsychology

Abstract

fetched live from OpenAlex

Climate change poses a potential risk to coastal infrastructure, thus threatening the economics or even the safety of human beings. Thus, a better understanding of the attitude of port organizations toward climate adaptation and mitigation is essential. This paper addresses this research gap by investigating 18 port organizations in China. The questions include the impediments and the impact of context, systems, and other factors on the implementation of adaptation strategies. The results indicate that port organizations are generally aware of climate change impacts and agree that some further steps are needed. However, policy support serves as a key factor in implementing adaptation plans. Apart from offering important insight on the attitude of port organizations, the study also serves as a platform for further research on climate adaptation planning in China.

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: none
Teacher disagreement score0.831
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.011
GPT teacher head0.235
Teacher spread0.224 · 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