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Record W4317812162 · doi:10.1017/asjcl.2022.30

China's New Global Health Governance

2023· article· en· W4317812162 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

VenueAsian Journal of Comparative Law · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Security and Public Health
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsChinaGlobal governanceCorporate governanceCoronavirus disease 2019 (COVID-19)Global healthNorm (philosophy)Political sciencePandemicBusinessGreenhouse gasInternational tradeEconomic growthDevelopment economicsHealth careEconomicsMedicineLaw

Abstract

fetched live from OpenAlex

Abstract This article analyses China's global health governance (GHG) practices and GHG legal infrastructure in the wake of COVID-19. It posits that China has pursued a mix of bilateral and multilateral strategies during the pandemic to promote global cooperation and domestic regulation to shape an effective GHG response. It demarcates China's proactive role in norm-setting to respond to the global health crisis. It first considers China's responses to COVID-19 and its interaction model with multilateral institutions including WHO and GAVI. It then examines China's bilateral health strategies, taking its interactions with African countries as an example, before analysing and comparing existing norms and practices on the ‘right to regulate’ under the rules of the World Trade Organisation and treaties that China participates in that call for more regulatory recognition. The article then proceeds to examine China's new initiatives in shaping GHG strategy during COVID-19. Finally, it concludes and calls for a coordinated multilateral approach to handle global health crises.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.955
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.048
GPT teacher head0.415
Teacher spread0.367 · 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