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Three Pillars in the Biden Administration’s China Strategy: Allies, Values, and High-Tech

2022· article· en· W4360985126 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Relations and Diplomacy · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobalization, Economics, and Policies
Canadian institutionsnot available
FundersUniversity of TorontoU.S. Department of State
KeywordsAdministration (probate law)ChinaPolitical scienceLaw

Abstract

fetched live from OpenAlex

The Biden Administration has inherited its predecessor's strategic perception about the growing competition among great powers.As a result, its policy toward China has been largely an extension of its predecessor's, retaining the elements of competition and revising the instruments to outcompete China.The Biden Administration's China policy has revolved around three pillars-allies, values, and high-tech, which it believes are America's strengths in its relations with China.Since Biden took office, the United States has spent most of its diplomatic resources consolidating and building smaller security, economic, and tech alliances with membership restricted to democratic allies only, in an attempt to delink from China and consolidate its hegemonic status in the world.This policy carries the pernicious effect of plunging the world into Cold War-like confrontations.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.748

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)0.0010.000

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 head0.022
GPT teacher head0.250
Teacher spread0.229 · 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